record_id,study_id,model_id,table,column,page,var_name_printed,taxonomy_id,taxonomy_group,x_transform,x_unit,beta,se,t,p,p_stars,ci_lo,ci_hi,confidence,notes,dep_var,dep_transform,estimator,n_obs,r2,paren,sample_subset,family,es,es_se,es_formula,se_source,partial_r,partial_r_se,partial_r_formula,t_used,df_used,x_unit_norm,harm_flags,year,country,continent,income_group,sample_start,sample_end,property_type,price_type,document_type,time_fe,location_fe,se_type,ai_methods,data_mid_year,estimator_class,pub_type,usable,usable_partial_r,extreme
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c1,7,1,35,No. of rooms,bedrooms,A_structural,level,count,0.0499,0.0029,,,***,,,medium,Total number of rooms (jian) of the estate; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,498.0,0.522,se,"All available contracts (Inner and Outer City); 8 period dummies (25-year periods) included, not reported",semi_elasticity,4.99,0.29,100*b/1 (per unit count),reported,0.6145017307898943,0.035712525436687244,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.20689655172414,488.0,count,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c2,7,2,35,No. of rooms,bedrooms,A_structural,level,count,0.0502,0.0035,,,***,,,medium,Total number of rooms (jian) of the estate; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,331.0,0.583,se,"Outer City contracts only; 8 period dummies (25-year periods) included, not reported",semi_elasticity,5.0200000000000005,0.35000000000000003,100*b/1 (per unit count),reported,0.6249521663145041,0.04357236219324231,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.342857142857143,321.0,count,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c3,7,3,35,No. of rooms,bedrooms,A_structural,level,count,0.0626,0.0039,,,***,,,medium,Total number of rooms (jian) of the estate; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,488.0,0.513,se,"All contracts, outliers (room number > 100 or = 1) dropped; 8 period dummies (25-year periods) included, not reported",semi_elasticity,6.260000000000001,0.38999999999999996,100*b/1 (per unit count),reported,0.5918013878394601,0.036869415536324196,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.05128205128205,478.0,count,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c4,7,4,35,No. of rooms,bedrooms,A_structural,level,count,0.0682,0.0052,,,***,,,medium,Total number of rooms (jian) of the estate; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,325.0,0.583,se,"Outer City only, outliers dropped; 8 period dummies (25-year periods) included, not reported",semi_elasticity,6.819999999999999,0.52,100*b/1 (per unit count),reported,0.5943066832462751,0.04531370605396819,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.115384615384615,315.0,count,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c1,7,1,35,Close to commercial center,commercial_distance,D_location,binary,binary,-0.261,0.0851,,,***,,,medium,Reference: inside commercial district; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,498.0,0.522,se,"All available contracts (Inner and Outer City); 8 period dummies (25-year periods) included, not reported",pct_premium,-23.25032276985106,6.555090625924323,100*(exp(b - se^2/2) - 1),reported,-0.137516647889639,0.04483780358393976,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.066980023501763,488.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c2,7,2,35,Close to commercial center,commercial_distance,D_location,binary,binary,-0.264,0.0944,,,***,,,medium,Reference: inside commercial district; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,331.0,0.583,se,"Outer City contracts only; 8 period dummies (25-year periods) included, not reported",pct_premium,-23.54406926725341,7.2496702143593055,100*(exp(b - se^2/2) - 1),reported,-0.15422406320285761,0.05514678623617333,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.7966101694915255,321.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c3,7,3,35,Close to commercial center,commercial_distance,D_location,binary,binary,-0.245,0.0842,,,***,,,medium,Reference: inside commercial district; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,488.0,0.513,se,"All contracts, outliers (room number > 100 or = 1) dropped; 8 period dummies (25-year periods) included, not reported",pct_premium,-22.006509663062722,6.59037221199653,100*(exp(b - se^2/2) - 1),reported,-0.1319251170632093,0.045339162680498875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.9097387173396676,478.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c4,7,4,35,Close to commercial center,commercial_distance,D_location,binary,binary,-0.216,0.0917,,,**,,,medium,Reference: inside commercial district; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,325.0,0.583,se,"Outer City only, outliers dropped; 8 period dummies (25-year periods) included, not reported",pct_premium,-19.764525622257057,7.388592718179809,100*(exp(b - se^2/2) - 1),reported,-0.13156416069053833,0.05585385895982576,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3555070883315157,315.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c1,7,1,35,Far from commercial center,commercial_distance,D_location,binary,binary,-0.318,0.127,,,**,,,medium,Reference: inside commercial district; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,498.0,0.522,se,"All available contracts (Inner and Outer City); 8 period dummies (25-year periods) included, not reported",pct_premium,-27.824136750146078,9.240555412865364,100*(exp(b - se^2/2) - 1),reported,-0.1126267118021554,0.044979850310923705,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5039370078740157,488.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c2,7,2,35,Far from commercial center,commercial_distance,D_location,binary,binary,-0.853,0.215,,,***,,,medium,Reference: inside commercial district; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,331.0,0.583,se,"Outer City contracts only; 8 period dummies (25-year periods) included, not reported",pct_premium,-58.360148144807766,9.161894084860197,100*(exp(b - se^2/2) - 1),reported,-0.21620355655828638,0.05449444860496082,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.967441860465116,321.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,True
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c3,7,3,35,Far from commercial center,commercial_distance,D_location,binary,binary,-0.278,0.128,,,**,,,medium,Reference: inside commercial district; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,488.0,0.513,se,"All contracts, outliers (room number > 100 or = 1) dropped; 8 period dummies (25-year periods) included, not reported",pct_premium,-24.888161262898944,9.693399315383495,100*(exp(b - se^2/2) - 1),reported,-0.09885269432673126,0.045514909618063315,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.171875,478.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c4,7,4,35,Far from commercial center,commercial_distance,D_location,binary,binary,-0.817,0.216,,,***,,,medium,Reference: inside commercial district; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,325.0,0.583,se,"Outer City only, outliers dropped; 8 period dummies (25-year periods) included, not reported",pct_premium,-56.84310544025713,9.541906561340475,100*(exp(b - se^2/2) - 1),reported,-0.20843377012776135,0.0551061130325538,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.782407407407407,315.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c1,7,1,35,Forbidden city,cbd_distance,D_location,binary,binary,-0.0142,0.156,,,,,,medium,Adjacent to Forbidden City (political centre); reference: elsewhere in Inner City; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,498.0,0.522,se,"All available contracts (Inner and Outer City); 8 period dummies (25-year periods) included, not reported",pct_premium,-2.602339973814116,15.38004537380447,100*(exp(b - se^2/2) - 1),reported,-0.0041205021791301645,0.04526748872847222,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.09102564102564104,488.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c3,7,3,35,Forbidden city,cbd_distance,D_location,binary,binary,-0.0428,0.154,,,,,,medium,Adjacent to Forbidden City (political centre); reference: elsewhere in Inner City; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,488.0,0.513,se,"All contracts, outliers (room number > 100 or = 1) dropped; 8 period dummies (25-year periods) included, not reported",pct_premium,-5.319109876726092,14.754786069170056,100*(exp(b - se^2/2) - 1),reported,-0.012710833022198737,0.045735240313518825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2779220779220779,478.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c1,7,1,35,Outer city,cbd_distance,D_location,binary,binary,-0.302,0.107,,,***,,,medium,Located in Outer City (vs Inner City); parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,498.0,0.522,se,"All available contracts (Inner and Outer City); 8 period dummies (25-year periods) included, not reported",pct_premium,-26.48821849281302,7.910917294317992,100*(exp(b - se^2/2) - 1),reported,-0.12673517364624606,0.04490285953691499,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.822429906542056,488.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,True
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c3,7,3,35,Outer city,cbd_distance,D_location,binary,binary,-0.22,0.108,,,**,,,medium,Located in Outer City (vs Inner City); parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,488.0,0.513,se,"All contracts, outliers (room number > 100 or = 1) dropped; 8 period dummies (25-year periods) included, not reported",pct_premium,-20.214787043521763,8.667203017994767,100*(exp(b - se^2/2) - 1),reported,-0.09277010668104858,0.04554168873433294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.037037037037037,478.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c1,7,1,35,Clay material,roof_materials,A_structural,binary,binary,-0.675,0.204,,,***,,,medium,Built with clay (vs brick and tile); parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,498.0,0.522,se,"All available contracts (Inner and Outer City); 8 period dummies (25-year periods) included, not reported",pct_premium,-50.132864129883515,10.386790980394004,100*(exp(b - se^2/2) - 1),reported,-0.14813095613116642,0.04476846674186362,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.308823529411765,488.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c2,7,2,35,Clay material,roof_materials,A_structural,binary,binary,-0.679,0.257,,,***,,,medium,Built with clay (vs brick and tile); parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,331.0,0.583,se,"Outer City contracts only; 8 period dummies (25-year periods) included, not reported",pct_premium,-50.93501293698479,13.03308327269835,100*(exp(b - se^2/2) - 1),reported,-0.14588571892443797,0.055217422332224673,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.642023346303502,321.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,True
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c3,7,3,35,Clay material,roof_materials,A_structural,binary,binary,-0.473,0.21,,,**,,,medium,Built with clay (vs brick and tile); parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,488.0,0.513,se,"All contracts, outliers (room number > 100 or = 1) dropped; 8 period dummies (25-year periods) included, not reported",pct_premium,-39.045957048710456,13.085731494730814,100*(exp(b - se^2/2) - 1),reported,-0.10247911468237811,0.04549812702600296,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.2523809523809524,478.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c4,7,4,35,Clay material,roof_materials,A_structural,binary,binary,-0.466,0.258,,,*,,,medium,Built with clay (vs brick and tile); parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,325.0,0.583,se,"Outer City only, outliers dropped; 8 period dummies (25-year periods) included, not reported",pct_premium,-39.30336948957128,16.18968792842139,100*(exp(b - se^2/2) - 1),reported,-0.1012449962285544,0.05605409662439278,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.806201550387597,315.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c1,7,1,35,Broken,condition,A_structural,binary,binary,-0.333,0.143,,,**,,,medium,Property in poor repair; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,498.0,0.522,se,"All available contracts (Inner and Outer City); 8 period dummies (25-year periods) included, not reported",pct_premium,-29.052108433665314,10.249813776426494,100*(exp(b - se^2/2) - 1),reported,-0.10483314838351987,0.04501843909562564,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.328671328671329,488.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c2,7,2,35,Broken,condition,A_structural,binary,binary,-0.291,0.186,,,,,,medium,Property in poor repair; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,331.0,0.583,se,"Outer City contracts only; 8 period dummies (25-year periods) included, not reported",pct_premium,-26.530365412722922,13.903791611136493,100*(exp(b - se^2/2) - 1),reported,-0.08699173725448243,0.055602966080184654,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.564516129032258,321.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c3,7,3,35,Broken,condition,A_structural,binary,binary,-0.391,0.14,,,***,,,medium,Property in poor repair; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,488.0,0.513,se,"All contracts, outliers (room number > 100 or = 1) dropped; 8 period dummies (25-year periods) included, not reported",pct_premium,-33.02159955559637,9.46932218455005,100*(exp(b - se^2/2) - 1),reported,-0.12671264126600423,0.045370255184758554,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.7928571428571427,478.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d,008c3229443d60b36b8e1525b5af0589f63eb75d:T7-c4,7,4,35,Broken,condition,A_structural,binary,binary,-0.325,0.18,,,*,,,medium,Property in poor repair; parentheses assumed standard errors (no explicit legend; consistent with star pattern),log price of transacted estate,log,OLS,325.0,0.583,se,"Outer City only, outliers dropped; 8 period dummies (25-year periods) included, not reported",pct_premium,-28.908328935500137,13.0054923655573,100*(exp(b - se^2/2) - 1),reported,-0.101209156553874,0.056054302091376365,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8055555555555556,315.0,binary,,2012.0,China,Asia,Upper middle income,,,mixed,transaction,working_paper,True,False,unknown,,2009.0,ols,other,True,True,False
00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78:T4-c1,4,1,11,mk,living_area,A_structural,level,m2,0.002,,7.75,,***,,,high,"dwelling size in m2 (mean 163.9); robust SE printed as 0.000 (rounded) -> se null; columns: Katsayi (coef+stars), t istatistik, Direncli Standart Hata (White robust SE); table note says *,**,*** = 1%,5%,10% but t-values show the conventional reading (*** = 1%, * = 10%) is intended","lnp (log of listing price, TL)",log,OLS,1000.0,0.6664,se,"Full sample of 1,000 listings, five provinces; stepwise variable selection (AIC/R2), VIF>5 variables dropped; robust SE in separate column",semi_elasticity,0.2,0.025806451612903226,100*b/1 (X per m2->m2),|b/t|,0.2391630745985124,0.030859751561098374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.75,990.0,m2,,2021.0,Turkey,Asia,Upper middle income,2021.0,2021.0,mixed,listing,journal,False,True,robust,,2021.0,ols,journal,True,True,False
00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78:T4-c1,4,1,11,yas,age,A_structural,level,years,-0.019,0.002,-11.65,,***,,,high,"age of dwelling in years; columns: Katsayi (coef+stars), t istatistik, Direncli Standart Hata (White robust SE); table note says *,**,*** = 1%,5%,10% but t-values show the conventional reading (*** = 1%, * = 10%) is intended","lnp (log of listing price, TL)",log,OLS,1000.0,0.6664,se,"Full sample of 1,000 listings, five provinces; stepwise variable selection (AIC/R2), VIF>5 variables dropped; robust SE in separate column",semi_elasticity,-1.9,0.2,100*b/1 (per year),reported,-0.3472244127837892,0.029804670625217956,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.65,990.0,years,,2021.0,Turkey,Asia,Upper middle income,2021.0,2021.0,mixed,listing,journal,False,True,robust,,2021.0,ols,journal,True,True,False
00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78:T4-c1,4,1,11,oda,bedrooms,A_structural,level,count,0.096,0.02,4.9,,***,,,high,"number of rooms (oda sayisi), all rooms; columns: Katsayi (coef+stars), t istatistik, Direncli Standart Hata (White robust SE); table note says *,**,*** = 1%,5%,10% but t-values show the conventional reading (*** = 1%, * = 10%) is intended","lnp (log of listing price, TL)",log,OLS,1000.0,0.6664,se,"Full sample of 1,000 listings, five provinces; stepwise variable selection (AIC/R2), VIF>5 variables dropped; robust SE in separate column",semi_elasticity,9.6,2.0,100*b/1 (per unit count),reported,0.15387744302758405,0.03140355980154776,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.9,990.0,count,,2021.0,Turkey,Asia,Upper middle income,2021.0,2021.0,mixed,listing,journal,False,True,robust,,2021.0,ols,journal,True,True,False
00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78:T4-c1,4,1,11,kbk,floor_level,A_structural,level,count,0.024,0.005,4.69,,***,,,high,"floor on which the dwelling is located; columns: Katsayi (coef+stars), t istatistik, Direncli Standart Hata (White robust SE); table note says *,**,*** = 1%,5%,10% but t-values show the conventional reading (*** = 1%, * = 10%) is intended","lnp (log of listing price, TL)",log,OLS,1000.0,0.6664,se,"Full sample of 1,000 listings, five provinces; stepwise variable selection (AIC/R2), VIF>5 variables dropped; robust SE in separate column",semi_elasticity,2.4,0.5,100*b/1 (per unit count),reported,0.1474291709350446,0.031434791244145964,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.69,990.0,count,,2021.0,Turkey,Asia,Upper middle income,2021.0,2021.0,mixed,listing,journal,False,True,robust,,2021.0,ols,journal,True,True,False
00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78:T4-c1,4,1,11,bks,storeys,A_structural,level,count,0.023,0.004,5.35,,***,,,high,"number of floors in the building; columns: Katsayi (coef+stars), t istatistik, Direncli Standart Hata (White robust SE); table note says *,**,*** = 1%,5%,10% but t-values show the conventional reading (*** = 1%, * = 10%) is intended","lnp (log of listing price, TL)",log,OLS,1000.0,0.6664,se,"Full sample of 1,000 listings, five provinces; stepwise variable selection (AIC/R2), VIF>5 variables dropped; robust SE in separate column",semi_elasticity,2.3,0.4,100*b/1 (per unit count),reported,0.16762822624471183,0.03133237873732932,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.35,990.0,count,,2021.0,Turkey,Asia,Upper middle income,2021.0,2021.0,mixed,listing,journal,False,True,robust,,2021.0,ols,journal,True,True,False
00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78:T4-c1,4,1,11,bs,bathrooms,A_structural,level,count,0.184,0.028,6.63,,***,,,high,"number of bathrooms; columns: Katsayi (coef+stars), t istatistik, Direncli Standart Hata (White robust SE); table note says *,**,*** = 1%,5%,10% but t-values show the conventional reading (*** = 1%, * = 10%) is intended","lnp (log of listing price, TL)",log,OLS,1000.0,0.6664,se,"Full sample of 1,000 listings, five provinces; stepwise variable selection (AIC/R2), VIF>5 variables dropped; robust SE in separate column",semi_elasticity,18.4,2.8000000000000003,100*b/1 (per unit count),reported,0.206187489378034,0.031099168835299243,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.63,990.0,count,,2021.0,Turkey,Asia,Upper middle income,2021.0,2021.0,mixed,listing,journal,False,True,robust,,2021.0,ols,journal,True,True,False
00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78:T4-c1,4,1,11,kombi,heating,A_structural,dummy,binary,0.05,0.051,0.97,,,,,high,"1 if heating by individual combi boiler (kombi); reference = other heating types; columns: Katsayi (coef+stars), t istatistik, Direncli Standart Hata (White robust SE); table note says *,**,*** = 1%,5%,10% but t-values show the conventional reading (*** = 1%, * = 10%) is intended","lnp (log of listing price, TL)",log,OLS,1000.0,0.6664,se,"Full sample of 1,000 listings, five provinces; stepwise variable selection (AIC/R2), VIF>5 variables dropped; robust SE in separate column",pct_premium,4.990480693746169,5.361482591517722,100*(exp(b - se^2/2) - 1),reported,0.03081398432884509,0.031766994153448545,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.97,990.0,binary,,2021.0,Turkey,Asia,Upper middle income,2021.0,2021.0,mixed,listing,journal,False,True,robust,,2021.0,ols,journal,True,True,False
00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78:T4-c1,4,1,11,soba,heating,A_structural,dummy,binary,0.007,0.091,0.08,,,,,high,"1 if heating by stove (soba); columns: Katsayi (coef+stars), t istatistik, Direncli Standart Hata (White robust SE); table note says *,**,*** = 1%,5%,10% but t-values show the conventional reading (*** = 1%, * = 10%) is intended","lnp (log of listing price, TL)",log,OLS,1000.0,0.6664,se,"Full sample of 1,000 listings, five provinces; stepwise variable selection (AIC/R2), VIF>5 variables dropped; robust SE in separate column",pct_premium,0.28635922698105887,9.163923471128323,100*(exp(b - se^2/2) - 1),reported,0.002542558686296684,0.031781983578708546,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.08,990.0,binary,,2021.0,Turkey,Asia,Upper middle income,2021.0,2021.0,mixed,listing,journal,False,True,robust,,2021.0,ols,journal,True,True,False
00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78:T4-c1,4,1,11,kalorifer,heating,A_structural,dummy,binary,0.065,0.113,0.56,,,,,high,"1 if central heating (kalorifer); columns: Katsayi (coef+stars), t istatistik, Direncli Standart Hata (White robust SE); table note says *,**,*** = 1%,5%,10% but t-values show the conventional reading (*** = 1%, * = 10%) is intended","lnp (log of listing price, TL)",log,OLS,1000.0,0.6664,se,"Full sample of 1,000 listings, five provinces; stepwise variable selection (AIC/R2), VIF>5 variables dropped; robust SE in separate column",pct_premium,6.036745106268393,12.058896975541376,100*(exp(b - se^2/2) - 1),reported,0.017795150091572516,0.03177705373495092,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.56,990.0,binary,,2021.0,Turkey,Asia,Upper middle income,2021.0,2021.0,mixed,listing,journal,False,True,robust,,2021.0,ols,journal,True,True,False
00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78:T4-c1,4,1,11,yer,heating,A_structural,dummy,binary,-0.032,0.132,-0.25,,,,,high,"1 if underfloor heating (yerden isitma); columns: Katsayi (coef+stars), t istatistik, Direncli Standart Hata (White robust SE); table note says *,**,*** = 1%,5%,10% but t-values show the conventional reading (*** = 1%, * = 10%) is intended","lnp (log of listing price, TL)",log,OLS,1000.0,0.6664,se,"Full sample of 1,000 listings, five provinces; stepwise variable selection (AIC/R2), VIF>5 variables dropped; robust SE in separate column",pct_premium,-3.9894399452920837,12.784286883445409,100*(exp(b - se^2/2) - 1),reported,-0.007945270783315908,0.03178108313326363,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.25,990.0,binary,,2021.0,Turkey,Asia,Upper middle income,2021.0,2021.0,mixed,listing,journal,False,True,robust,,2021.0,ols,journal,True,True,False
00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78,00a2fd8a3af8f6e0e127c590fbea4879d95d7c78:T4-c1,4,1,11,daire,dwelling_type,A_structural,dummy,binary,-0.34,0.07,-5.91,,***,,,high,"1 if apartment flat (daire), reference = detached house (mustakil); columns: Katsayi (coef+stars), t istatistik, Direncli Standart Hata (White robust SE); table note says *,**,*** = 1%,5%,10% but t-values show the conventional reading (*** = 1%, * = 10%) is intended","lnp (log of listing price, TL)",log,OLS,1000.0,0.6664,se,"Full sample of 1,000 listings, five provinces; stepwise variable selection (AIC/R2), VIF>5 variables dropped; robust SE in separate column",pct_premium,-28.997138007097334,4.982392259338267,100*(exp(b - se^2/2) - 1),reported,-0.18460386130862488,0.03123584793716157,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.91,990.0,binary,,2021.0,Turkey,Asia,Upper middle income,2021.0,2021.0,mixed,listing,journal,False,True,robust,,2021.0,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,Ln(SQM),living_area,A_structural,log,m2,0.777,0.005,,,***,,,high,"floor area in m2, log; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,elasticity,0.777,0.005,b (log-log),reported,0.8589548098449802,0.005527379728732177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),155.4,8582.0,m2,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,LIFT,accessibility,B_interior,binary,binary,0.026,0.004,,,***,,,high,"building has a lift; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,pct_premium,2.6332737778697046,0.4105363793893768,100*(exp(b - se^2/2) - 1),reported,0.06999269049417632,0.010768106229873281,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.5,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,FIREPLACE,fireplace,B_interior,binary,binary,0.108,0.01,,,***,,,high,"stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,pct_premium,11.399204439173483,1.1140477453864677,100*(exp(b - se^2/2) - 1),reported,0.11579720493223722,0.010721963419651596,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.799999999999999,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,BALCONY,terrace_balcony,C_exterior,binary,binary,0.033,0.004,,,***,,,high,"one or more balconies; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,pct_premium,3.3542270870065005,0.41342021569652226,100*(exp(b - se^2/2) - 1),reported,0.08870422908145113,0.010752027767448621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.25,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,GTERRACE,terrace_balcony,C_exterior,binary,binary,0.105,0.015,,,***,,,high,"garden terrace; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,pct_premium,11.058566244049217,1.6660659155335578,100*(exp(b - se^2/2) - 1),reported,0.07534726310073978,0.01076389472867711,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,ISHOUSE,dwelling_type,A_structural,binary,binary,0.133,0.013,,,***,,,high,"single family house (vs apartment); stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,pct_premium,14.21534822838957,1.4849249978301624,100*(exp(b - se^2/2) - 1),reported,0.10976949368794675,0.01072934900709254,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.230769230769232,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,Ln(CARTT_CBD),cbd_distance,D_location,log,minutes,-0.294,0.007,,,***,,,high,"average car travel time to Zürich CBD in minutes, log; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,elasticity,-0.294,0.007,b (log-log),reported,-0.4129172757223733,0.009831363707675555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-42.0,8582.0,minutes,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,Ln(RAILSTATION),transit_distance,D_location,log,km,-0.012,0.002,,,***,,,high,"Euclidean distance to next rail station in km, log; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,elasticity,-0.012,0.002,b (log-log),reported,-0.06463206107370717,0.010772010178951196,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,8582.0,km,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,AUTOBAHN,highway_distance,D_location,binary,binary,-0.06,0.013,,,***,,,high,"Autobahn within 100 m; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,pct_premium,-5.8315042156716785,1.2242938936595231,100*(exp(b - se^2/2) - 1),reported,-0.04975942116321067,0.010781207918695645,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.615384615384616,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,AIRNOISE,noise,E_environment,binary,binary,-0.039,0.006,,,***,,,high,"daily average aircraft noise above 52 dB; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,pct_premium,-3.826660221059519,0.57705042548782,100*(exp(b - se^2/2) - 1),reported,-0.06999269049417632,0.010768106229873281,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.5,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,Ln(HOTREST_JOBS),neighbourhood_amenities,F_neighbourhood,log,count,0.02,0.002,,,***,,,high,"jobs in hotel and restaurant industry within 1 km, log; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,elasticity,0.02,0.002,b (log-log),reported,0.10732233407321959,0.010732233407321958,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.0,8582.0,count,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,Ln(POP_DENS),density,F_neighbourhood,log,per_hectare,-0.028,0.002,,,***,,,high,"inhabitants per hectare, log; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,elasticity,-0.028,0.002,b (log-log),reported,-0.14942740258847478,0.01067338589917677,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.0,8582.0,per_hectare,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,Ln(TAXLEVEL),public_services,F_neighbourhood,log,index,-0.13,0.014,,,***,,,high,"local income tax level for individuals (index), log; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,elasticity,-0.13,0.014,b (log-log),reported,-0.0997356084648765,0.010740757834679007,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.285714285714286,8582.0,index,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,Ln(VIEW_LAKE),view,E_environment,log,hectare,0.008,0.001,,,***,,,high,"visibility of lake surface (>1 km2) in hectares, log; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,elasticity,0.008,0.001,b (log-log),reported,0.08603642800727886,0.010754553500909857,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,8582.0,ha,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,Ln(VIEW_ALL),view,E_environment,log,hectare,0.005,0.002,,,**,,,high,"total visibility of terrain surface in hectares, log; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,elasticity,0.005,0.002,b (log-log),reported,0.026976628401263626,0.01079065136050545,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5,8582.0,ha,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c1,2,Model 1,14,Ln(SOLAR_EVE),sunlight,E_environment,log,index,0.037,0.003,,,***,,,high,"evening solar exposure index, log; stars: *** p<0.01, ** p<0.05, * p<0.1","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.854,se,Model 1: with Ln(CARTT_CBD); adj R2; quarterly time dummies,elasticity,0.037,0.003,b (log-log),reported,0.13196875303582847,0.010700169165067174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.333333333333332,8582.0,index,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,Ln(SQM),living_area,A_structural,log,m2,0.776,0.005,,,***,,,high,"floor area in m2, log","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,elasticity,0.776,0.005,b (log-log),reported,0.8586645444503753,0.005532632374035926,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),155.2,8582.0,m2,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,LIFT,accessibility,B_interior,binary,binary,0.024,0.005,,,***,,,high,building has a lift,"Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,pct_premium,2.4277514341670248,0.5121451589453108,100*(exp(b - se^2/2) - 1),reported,0.05174457099579829,0.010780118957457977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.8,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,FIREPLACE,fireplace,B_interior,binary,binary,0.118,0.011,,,***,,,high,,"Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,pct_premium,12.51760361579004,1.2377685225040767,100*(exp(b - se^2/2) - 1),reported,0.11502777784526268,0.010722928443202454,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.727272727272727,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,BALCONY,terrace_balcony,C_exterior,binary,binary,0.033,0.004,,,***,,,high,one or more balconies,"Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,pct_premium,3.3542270870065005,0.41342021569652226,100*(exp(b - se^2/2) - 1),reported,0.08870422908145113,0.010752027767448621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.25,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,GTERRACE,terrace_balcony,C_exterior,binary,binary,0.107,0.016,,,***,,,high,garden terrace,"Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,pct_premium,11.279180801152066,1.7806948071669213,100*(exp(b - se^2/2) - 1),reported,0.07200138940313028,0.010766562901402658,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.6875,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,ISHOUSE,dwelling_type,A_structural,binary,binary,0.125,0.013,,,***,,,high,single family house (vs apartment),"Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,pct_premium,13.305270606790987,1.473092988986874,100*(exp(b - se^2/2) - 1),reported,0.10323941760862675,0.010736899431297181,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.615384615384615,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,Ln(RAILSTATION),transit_distance,D_location,log,km,-0.012,0.003,,,***,,,high,"Euclidean distance to next rail station in km, log","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,elasticity,-0.012,0.003,b (log-log),reported,-0.043138125634160994,0.010784531408540248,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,8582.0,km,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,AUTOBAHN,highway_distance,D_location,binary,binary,-0.067,0.013,,,***,,,high,Autobahn within 100 m,"Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,pct_premium,-6.488381931906673,1.2157537617378096,100*(exp(b - se^2/2) - 1),reported,-0.05554770766976833,0.010777913428462512,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.153846153846154,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,AIRNOISE,noise,E_environment,binary,binary,-0.096,0.006,,,***,,,high,daily average aircraft noise above 52 dB,"Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,pct_premium,-9.155233613641279,0.5450784096412237,100*(exp(b - se^2/2) - 1),reported,-0.17019350567269406,0.010637094104543379,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.0,8582.0,binary,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,Ln(HOTREST_JOBS),neighbourhood_amenities,F_neighbourhood,log,count,0.032,0.002,,,***,,,high,"jobs in hotel and restaurant industry within 1 km, log","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,elasticity,0.032,0.002,b (log-log),reported,0.17019350567269406,0.010637094104543379,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.0,8582.0,count,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,Ln(POP_DENS),density,F_neighbourhood,log,per_hectare,-0.026,0.002,,,***,,,high,"inhabitants per hectare, log","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,elasticity,-0.026,0.002,b (log-log),reported,-0.13896790499819134,0.010689838846014718,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.0,8582.0,per_hectare,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,Ln(TAXLEVEL),public_services,F_neighbourhood,log,index,-0.223,0.015,,,***,,,high,"local income tax level for individuals (index), log","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,elasticity,-0.223,0.015,b (log-log),reported,-0.1584520325647806,0.010658208468482998,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.866666666666667,8582.0,index,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,True
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,Ln(VIEW_LAKE),view,E_environment,log,hectare,0.012,0.001,,,***,,,high,"visibility of lake surface (>1 km2) in hectares, log","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,elasticity,0.012,0.001,b (log-log),reported,0.1284616931266385,0.01070514109388654,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,8582.0,ha,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,Ln(VIEW_ALL),view,E_environment,log,hectare,-0.001,0.002,,,,,,high,"total visibility of terrain surface in hectares, log","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,elasticity,-0.001,0.002,b (log-log),reported,-0.005397211333671679,0.010794422667343357,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5,8582.0,ha,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,True
03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3,03ae226b461f39ce77988b8e944f5ba8259156d3:T2-c2,2,Model 2,14,Ln(SOLAR_EVE),sunlight,E_environment,log,index,0.018,0.003,,,***,,,high,"evening solar exposure index, log","Ln(RENT), monthly net asking rent in CHF",log,OLS,8592.0,0.836,se,Model 2: with CARACC instead of CARTT_CBD; adj R2,elasticity,0.018,0.003,b (log-log),reported,0.06463206107370716,0.010772010178951196,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.999999999999999,8582.0,index,,2010.0,Switzerland,Europe,High income,2004.0,2005.0,rental,rent,journal,True,False,OLS,,2004.5,ols,journal,True,True,False
03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f:T2-c1,2,1 (HMA),7,Effect of wood,roof_materials,A_structural,dummy,binary,0.017,0.025,,0.498,,,,high,wooden structure dummy (fully wooden or wooden-frame building); Std. err. printed in [brackets]; p-value from text (p.6-8); stars *p<0.05 **p<0.01 ***p<0.001; other hedonic coefficients not printed (Table 3 lists only which were significant),ln(transaction price of dwelling),log,OLS,27954.0,0.907,se,"Helsinki metropolitan area (Helsinki+Espoo+Vantaa), 137 postal-code dummies; housing, neighbourhood characteristics and distance to CBD included; apartment-building dwellings built 1990-2020, sold 1999-2018; stepwise OLS, SE clustered by postal code; only the wood coefficient is printed",pct_premium,1.6827514072139893,2.5428633058131016,100*(exp(b - se^2/2) - 1),reported,0.004067813499162229,0.005982078675238571,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.68,27944.0,binary,,2021.0,Finland,Europe,High income,1999.0,2018.0,condo_apartment,transaction,journal,False,True,clustered,,2008.5,ols,journal,True,True,False
03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f:T2-c2,2,2 (Helsinki),7,Effect of wood,roof_materials,A_structural,dummy,binary,0.085,0.02,,0.0,***,,,high,wooden structure dummy (fully wooden or wooden-frame building); Std. err. printed in [brackets]; p-value from text (p.6-8); stars *p<0.05 **p<0.01 ***p<0.001; other hedonic coefficients not printed (Table 3 lists only which were significant),ln(transaction price of dwelling),log,OLS,14867.0,0.91,se,"City of Helsinki, 79 postal codes; full controls; apartment-building dwellings built 1990-2020, sold 1999-2018; stepwise OLS, SE clustered by postal code; only the wood coefficient is printed",pct_premium,8.849934505794877,2.1774341333967975,100*(exp(b - se^2/2) - 1),reported,0.034846529414940805,0.008199183391750778,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.25,14857.0,binary,,2021.0,Finland,Europe,High income,1999.0,2018.0,condo_apartment,transaction,journal,False,True,clustered,,2008.5,ols,journal,True,True,False
03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f:T2-c3,2,3 (Espoo),7,Effect of wood,roof_materials,A_structural,dummy,binary,0.029,0.037,,0.443,,,,high,wooden structure dummy (fully wooden or wooden-frame building); Std. err. printed in [brackets]; p-value from text (p.6-8); stars *p<0.05 **p<0.01 ***p<0.001; other hedonic coefficients not printed (Table 3 lists only which were significant),ln(transaction price of dwelling),log,OLS,7422.0,0.891,se,"City of Espoo, 33 postal codes; full controls; apartment-building dwellings built 1990-2020, sold 1999-2018; stepwise OLS, SE clustered by postal code; only the wood coefficient is printed",pct_premium,2.872019444862506,3.8088709995579837,100*(exp(b - se^2/2) - 1),reported,0.009103545596555393,0.011614868519743086,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7837837837837839,7412.0,binary,,2021.0,Finland,Europe,High income,1999.0,2018.0,condo_apartment,transaction,journal,False,True,clustered,,2008.5,ols,journal,True,True,False
03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f:T2-c4,2,4 (Vantaa),7,Effect of wood,roof_materials,A_structural,dummy,binary,-0.011,0.022,,0.613,,,,high,wooden structure dummy (fully wooden or wooden-frame building); Std. err. printed in [brackets]; p-value from text (p.6-8); stars *p<0.05 **p<0.01 ***p<0.001; other hedonic coefficients not printed (Table 3 lists only which were significant),ln(transaction price of dwelling),log,OLS,5665.0,0.876,se,"City of Vantaa, 25 postal codes; distance to CBD excluded (multicollinearity); apartment-building dwellings built 1990-2020, sold 1999-2018; stepwise OLS, SE clustered by postal code; only the wood coefficient is printed",pct_premium,-1.1179044852767994,2.175932613305811,100*(exp(b - se^2/2) - 1),reported,-0.006648812719476,0.013297625438951998,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5,5655.0,binary,,2021.0,Finland,Europe,High income,1999.0,2018.0,condo_apartment,transaction,journal,False,True,clustered,,2008.5,ols,journal,True,True,False
03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f:T4-c1,4,1 (Helsinki),8,Wood,roof_materials,A_structural,dummy,binary,-0.259,0.079,,,**,,,high,"wooden structure dummy; printed with decimal commas (e.g. '−0, 259', '[0, 079]'); stars *p<0.05 **p<0.01 ***p<0.001 (Table 2 legend); specification: wood only",ln(transaction price of dwelling),log,OLS,14888.0,0.003,se,"Helsinki only, gradually adding variable groups: wood only; SE clustered by 79 postal codes",pct_premium,-23.058169678425912,6.097401882045257,100*(exp(b - se^2/2) - 1),reported,-0.02686850960149904,0.008195414125553762,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.278481012658228,14878.0,binary,,2021.0,Finland,Europe,High income,1999.0,2018.0,condo_apartment,transaction,journal,False,True,clustered,,2008.5,ols,journal,True,True,False
03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f:T4-c2,4,2 (Helsinki),8,Wood,roof_materials,A_structural,dummy,binary,-0.167,0.07,,,*,,,high,"wooden structure dummy; printed with decimal commas (e.g. '−0, 259', '[0, 079]'); stars *p<0.05 **p<0.01 ***p<0.001 (Table 2 legend); specification: wood + age & size",ln(transaction price of dwelling),log,OLS,14888.0,0.574,se,"Helsinki only, gradually adding variable groups: wood + age & size; SE clustered by 79 postal codes",pct_premium,-15.587104012678743,5.923397279360318,100*(exp(b - se^2/2) - 1),reported,-0.01955523770297933,0.008196806222805707,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3857142857142857,14878.0,binary,,2021.0,Finland,Europe,High income,1999.0,2018.0,condo_apartment,transaction,journal,False,True,clustered,,2008.5,ols,journal,True,True,False
03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f:T4-c3,4,3 (Helsinki),8,Wood,roof_materials,A_structural,dummy,binary,0.043,0.024,,,,,,high,"wooden structure dummy; printed with decimal commas (e.g. '−0, 259', '[0, 079]'); stars *p<0.05 **p<0.01 ***p<0.001 (Table 2 legend); specification: + housing characteristics + CBD Euclidean distance",ln(transaction price of dwelling),log,OLS,14888.0,0.85,se,"Helsinki only, gradually adding variable groups: + housing characteristics + CBD Euclidean distance; SE clustered by 79 postal codes",pct_premium,4.363728402693212,2.5054509476414704,100*(exp(b - se^2/2) - 1),reported,0.014687168932021606,0.008197489636477175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7916666666666665,14878.0,binary,,2021.0,Finland,Europe,High income,1999.0,2018.0,condo_apartment,transaction,journal,False,True,clustered,,2008.5,ols,journal,True,True,False
03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f:T4-c4,4,4 (Helsinki),8,Wood,roof_materials,A_structural,dummy,binary,0.041,0.02,,,*,,,high,"wooden structure dummy; printed with decimal commas (e.g. '−0, 259', '[0, 079]'); stars *p<0.05 **p<0.01 ***p<0.001 (Table 2 legend); specification: + neighbourhood characteristics",ln(transaction price of dwelling),log,OLS,14867.0,0.894,se,"Helsinki only, gradually adding variable groups: + neighbourhood characteristics; SE clustered by 79 postal codes",pct_premium,4.1643755960023565,2.083704211090959,100*(exp(b - se^2/2) - 1),reported,0.016816162099116762,0.008203005902008178,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.05,14857.0,binary,,2021.0,Finland,Europe,High income,1999.0,2018.0,condo_apartment,transaction,journal,False,True,clustered,,2008.5,ols,journal,True,True,False
03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f,03bfeba917085bc65a0ab641e5a03916b687b20f:T4-c5,4,5 (Helsinki),8,Wood,roof_materials,A_structural,dummy,binary,0.085,0.02,,,***,,,high,"wooden structure dummy; printed with decimal commas (e.g. '−0, 259', '[0, 079]'); stars *p<0.05 **p<0.01 ***p<0.001 (Table 2 legend); specification: + postal codes [79]; identical to Table 2 col 2",ln(transaction price of dwelling),log,OLS,14867.0,0.91,se,"Helsinki only, gradually adding variable groups: + postal codes [79]; identical to Table 2 col 2; SE clustered by 79 postal codes",pct_premium,8.849934505794877,2.1774341333967975,100*(exp(b - se^2/2) - 1),reported,0.034846529414940805,0.008199183391750778,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.25,14857.0,binary,,2021.0,Finland,Europe,High income,1999.0,2018.0,condo_apartment,transaction,journal,False,True,clustered,,2008.5,ols,journal,True,True,False
03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee:T2-OLS,2,OLS,14,AGE,age,A_structural,level,years,-0.063,,,0.02,,,,medium,Age in years adjusted for major rehabilitation; magnitude per year seems large but recorded as printed; p-value in parentheses (0.000 = <0.0005); no SE or t printed,"log(PRICE) (asking price, thousand EUR)",log,OLS,296.0,,p,Structural characteristics only; cross-validation R2 0.596 (not in-sample),semi_elasticity,-6.3,2.7081074461391577,100*b/1 (per year),|b/z(p)| (two-sided normal),-0.13627651569786828,0.05857959474528523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3263478740408408,286.0,years,,2020.0,Spain,Europe,High income,2013.0,2013.0,condo_apartment,listing,journal,False,False,unknown,,2013.0,ols,journal,True,True,True
03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee:T2-OLS,2,OLS,14,BATH,bathrooms,A_structural,level,count,0.148,,,0.005,,,,medium,p-value in parentheses (0.000 = <0.0005); no SE or t printed,"log(PRICE) (asking price, thousand EUR)",log,OLS,296.0,,p,Structural characteristics only; cross-validation R2 0.596 (not in-sample),semi_elasticity,14.799999999999999,5.272469525271241,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.16374311063194216,0.05833314599865084,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8070337683438042,286.0,count,,2020.0,Spain,Europe,High income,2013.0,2013.0,condo_apartment,listing,journal,False,False,unknown,,2013.0,ols,journal,True,True,False
03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee:T2-RK,2,RK,14,BATH,bathrooms,A_structural,level,count,0.128,,,0.002,,,,medium,p-value in parentheses; no SE or t printed,"log(PRICE) (asking price, thousand EUR)",log,other,296.0,,p,"Regression-kriging (GLS regression + kriging of residuals, spherical variogram); cross-validation R2 0.733",semi_elasticity,12.8,4.1420834202180865,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.17975293395632158,0.05816809745906533,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.090232306167813,286.0,count,,2020.0,Spain,Europe,High income,2013.0,2013.0,condo_apartment,listing,journal,False,False,unknown,,2013.0,other,journal,True,True,False
03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee:T2-OLS,2,OLS,14,PENT,dwelling_type,A_structural,binary,binary,0.169,,,0.016,,,,medium,Penthouse; p-value in parentheses (0.000 = <0.0005); no SE or t printed,"log(PRICE) (asking price, thousand EUR)",log,OLS,296.0,,p,Structural characteristics only; cross-validation R2 0.596 (not in-sample),pct_premium,18.12096781089658,8.307319192894656,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.14101872759968734,0.058540336893359184,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.408915545815461,286.0,binary,,2020.0,Spain,Europe,High income,2013.0,2013.0,condo_apartment,listing,journal,False,False,unknown,,2013.0,ols,journal,True,True,False
03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee:T2-RK,2,RK,14,PENT,dwelling_type,A_structural,binary,binary,0.124,,,0.02,,,,medium,Penthouse; p-value in parentheses; no SE or t printed,"log(PRICE) (asking price, thousand EUR)",log,other,296.0,,p,"Regression-kriging (GLS regression + kriging of residuals, spherical variogram); cross-validation R2 0.733",pct_premium,13.04088996388506,6.033919929613821,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.13627651569786828,0.05857959474528523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3263478740408408,286.0,binary,,2020.0,Spain,Europe,High income,2013.0,2013.0,condo_apartment,listing,journal,False,False,unknown,,2013.0,other,journal,True,True,False
03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee:T2-OLS,2,OLS,14,HEAT,heating,A_structural,binary,binary,0.112,,,0.029,,,,medium,Central heating; p-value in parentheses (0.000 = <0.0005); no SE or t printed,"log(PRICE) (asking price, thousand EUR)",log,OLS,296.0,,p,Structural characteristics only; cross-validation R2 0.596 (not in-sample),pct_premium,11.704237644303994,5.73731226574661,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.12804938612267644,0.058644458978906876,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1834865280065587,286.0,binary,,2020.0,Spain,Europe,High income,2013.0,2013.0,condo_apartment,listing,journal,False,False,unknown,,2013.0,ols,journal,True,True,False
03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee:T2-RK,2,RK,14,HEAT,heating,A_structural,binary,binary,0.084,,,0.03,,,,medium,Central heating; p-value in parentheses; no SE or t printed,"log(PRICE) (asking price, thousand EUR)",log,other,296.0,,p,"Regression-kriging (GLS regression + kriging of residuals, spherical variogram); cross-validation R2 0.733",pct_premium,8.681439396911417,4.210001022244586,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.12727654111504583,0.05865034121607055,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1700903775845606,286.0,binary,,2020.0,Spain,Europe,High income,2013.0,2013.0,condo_apartment,listing,journal,False,False,unknown,,2013.0,other,journal,True,True,False
03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee,03c7319d6d03a3326e49bd775951ee9918110cee:T2-OLS,2,OLS,14,AIRCON,air_conditioning,A_structural,binary,binary,0.141,,,0.001,,,,medium,p-value in parentheses (0.000 = <0.0005); no SE or t printed,"log(PRICE) (asking price, thousand EUR)",log,OLS,296.0,,p,Structural characteristics only; cross-validation R2 0.596 (not in-sample),pct_premium,15.03680407908925,4.933887143723051,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.19099117814265545,0.058042737144415116,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,286.0,binary,,2020.0,Spain,Europe,High income,2013.0,2013.0,condo_apartment,listing,journal,False,False,unknown,,2013.0,ols,journal,True,True,False
05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6:T2-c1,2,1,44,log(Median Household Income),income,F_neighbourhood,log,currency,0.041,0.019,,,**,,,high,,log(Transaction Price_jt),log,OLS,37564.0,0.793,se,block group x year; year-specific test-score coefficients,elasticity,0.041,0.019,b (log-log),reported,0.011134615671620387,0.005159943847824082,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1578947368421053,37554.0,currency,,2019.0,United States,North America,High income,2005.0,2012.0,unknown,transaction,working_paper,False,False,unknown,,2008.5,ols,other,True,True,False
05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6:T2-c1,2,1,44,Median Number of Rooms,bedrooms,A_structural,level,count,0.032,0.01,,,***,,,high,Median rooms in block group,log(Transaction Price_jt),log,OLS,37564.0,0.793,se,block group x year; year-specific test-score coefficients,semi_elasticity,3.2,1.0,100*b/1 (per unit count),reported,0.01651059312176734,0.0051595603505522935,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2,37554.0,count,,2019.0,United States,North America,High income,2005.0,2012.0,unknown,transaction,working_paper,False,False,unknown,,2008.5,ols,other,True,True,False
05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6:T2-c1,2,1,44,log(Offenses Per Capita),crime,F_neighbourhood,log,rate,-0.376,0.686,,,,,,high,,log(Transaction Price_jt),log,OLS,37564.0,0.793,se,block group x year; year-specific test-score coefficients,elasticity,-0.376,0.686,b (log-log),reported,-0.0028283548195284698,0.005160243101586517,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5481049562682215,37554.0,rate,,2019.0,United States,North America,High income,2005.0,2012.0,unknown,transaction,working_paper,False,False,unknown,,2008.5,ols,other,True,True,False
05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6:T3-c1,3,1,45,log(Median Household Income),income,F_neighbourhood,log,currency,0.044,0.022,,,**,,,high,,log(Transaction Price_jt),log,OLS,37564.0,0.772,se,block group x year; amenities only,elasticity,0.044,0.022,b (log-log),reported,0.01031997789050305,0.005159988945251525,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,37554.0,currency,,2019.0,United States,North America,High income,2005.0,2012.0,unknown,transaction,working_paper,False,False,unknown,,2008.5,ols,other,True,True,False
05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6:T3-c1,3,1,45,Median Number of Rooms,bedrooms,A_structural,level,count,0.05,0.012,,,***,,,high,,log(Transaction Price_jt),log,OLS,37564.0,0.772,se,block group x year; amenities only,semi_elasticity,5.0,1.2,100*b/1 (per unit count),reported,0.021496130696474634,0.005159071367153912,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.166666666666667,37554.0,count,,2019.0,United States,North America,High income,2005.0,2012.0,unknown,transaction,working_paper,False,False,unknown,,2008.5,ols,other,True,True,False
05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6:T3-c2,3,2,45,log(Median Household Income),income,F_neighbourhood,log,currency,0.001,0.019,,,,,,high,,log(Transaction Price_jt),log,OLS,37564.0,0.788,se,adds Trading Opportunities r and E(V) controls,elasticity,0.001,0.019,b (log-log),reported,0.00027159281849000307,0.005160263551310058,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.052631578947368425,37554.0,currency,,2019.0,United States,North America,High income,2005.0,2012.0,unknown,transaction,working_paper,False,False,unknown,,2008.5,ols,other,True,True,False
05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6:T3-c2,3,2,45,Median Number of Rooms,bedrooms,A_structural,level,count,0.002,0.011,,,,,,high,,log(Transaction Price_jt),log,OLS,37564.0,0.788,se,adds Trading Opportunities r and E(V) controls,semi_elasticity,0.2,1.0999999999999999,100*b/1 (per unit count),reported,0.000938229358255109,0.005160261470403099,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.18181818181818182,37554.0,count,,2019.0,United States,North America,High income,2005.0,2012.0,unknown,transaction,working_paper,False,False,unknown,,2008.5,ols,other,True,True,False
05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6:T3-c2,3,2,45,log(Offenses per Capita),crime,F_neighbourhood,log,rate,-3.338,0.664,,,***,,,high,,log(Transaction Price_jt),log,OLS,37564.0,0.788,se,adds Trading Opportunities r and E(V) controls,elasticity,-3.338,0.664,b (log-log),reported,-0.02593248126176429,0.0051585283276846874,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.02710843373494,37554.0,rate,,2019.0,United States,North America,High income,2005.0,2012.0,unknown,transaction,working_paper,False,False,unknown,,2008.5,ols,other,True,True,True
05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6:T3-c3,3,3,45,log(Median Household Income),income,F_neighbourhood,log,currency,0.005,0.015,,,,,,high,,log(Transaction Price_jt),log,OLS,37564.0,0.844,se,"adds credit-friction interactions and log balance, approval rate, interest cost controls",elasticity,0.005,0.015,b (log-log),reported,0.0017200853692673167,0.005160256107801949,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.33333333333333337,37554.0,currency,,2019.0,United States,North America,High income,2005.0,2012.0,unknown,transaction,working_paper,False,False,unknown,,2008.5,ols,other,True,True,False
05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6:T3-c3,3,3,45,Median Number of Rooms,bedrooms,A_structural,level,count,0.011,0.008,,,,,,high,,log(Transaction Price_jt),log,OLS,37564.0,0.844,se,"adds credit-friction interactions and log balance, approval rate, interest cost controls",semi_elasticity,1.0999999999999999,0.8,100*b/1 (per unit count),reported,0.007095184046405893,0.005160133851931558,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.375,37554.0,count,,2019.0,United States,North America,High income,2005.0,2012.0,unknown,transaction,working_paper,False,False,unknown,,2008.5,ols,other,True,True,False
05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6,05133875334147dc5ac7d37a0479720642327db6:T3-c3,3,3,45,log(Offenses per Capita),crime,F_neighbourhood,log,rate,-2.329,0.549,,,***,,,high,,log(Transaction Price_jt),log,OLS,37564.0,0.844,se,"adds credit-friction interactions and log balance, approval rate, interest cost controls",elasticity,-2.329,0.549,b (log-log),reported,-0.021885930007393826,0.005159027726088111,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.242258652094717,37554.0,rate,,2019.0,United States,North America,High income,2005.0,2012.0,unknown,transaction,working_paper,False,False,unknown,,2008.5,ols,other,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c1,3,1,34,Green (<500m),green_space,E_environment,binary,binary,0.006,0.014,,,,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample (Turin, 2017-2018); coefficients for dwellings < 1 year on the market in a fully interacted specification; month-year and urban macro-area fixed effects; two-way clustered SE",pct_premium,0.5919451117272434,1.408425250475691,100*(exp(b - se^2/2) - 1),reported,0.00517774203628168,0.012081398084657254,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.42857142857142855,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c2,3,2,34,Green (<500m),green_space,E_environment,binary,binary,0.075,0.007,,,***,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 1)",pct_premium,7.785774304643223,0.7545189056192421,100*(exp(b - se^2/2) - 1),reported,0.12837422954369088,0.01198159475741115,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.714285714285714,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c3,3,3,34,Green (<500m),green_space,E_environment,binary,binary,0.021,0.023,,,,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,Central subsample (OMI central districts); coefficients for dwellings < 1 year on the market (fully interacted specification),pct_premium,2.0951974124196138,2.3488107187663156,100*(exp(b - se^2/2) - 1),reported,0.02164829965254311,0.023710042476594834,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9130434782608696,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c4,3,4,34,Green (<500m),green_space,E_environment,binary,binary,0.085,0.014,,,***,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,"Central subsample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 3)",pct_premium,8.861037765371083,1.5242038933777584,100*(exp(b - se^2/2) - 1),reported,0.14251778273016852,0.023473517155557164,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.071428571428572,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c1,3,1,34,Transport stop (<500m),transit_distance,D_location,binary,binary,0.245,0.041,,,***,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample (Turin, 2017-2018); coefficients for dwellings < 1 year on the market in a fully interacted specification; month-year and urban macro-area fixed effects; two-way clustered SE",pct_premium,27.654792364629046,5.238247384140036,100*(exp(b - se^2/2) - 1),reported,0.07200727828890503,0.012050197591204515,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.975609756097561,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,True
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c2,3,2,34,Transport stop (<500m),transit_distance,D_location,binary,binary,0.11,0.041,,,***,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 1)",pct_premium,11.534023292208605,4.5767400888813725,100*(exp(b - se^2/2) - 1),reported,0.032396926884166025,0.012075218202280066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6829268292682924,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c3,3,3,34,Transport stop (<500m),transit_distance,D_location,binary,binary,-1.028,0.233,,,***,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,Central subsample (OMI central districts); coefficients for dwellings < 1 year on the market (fully interacted specification),pct_premium,-65.18578828645508,8.334915353244584,100*(exp(b - se^2/2) - 1),reported,-0.10406552131137958,0.023586835083221253,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.412017167381974,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,True
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c4,3,4,34,Transport stop (<500m),transit_distance,D_location,binary,binary,0.05,0.079,,,,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,"Central subsample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 3)",pct_premium,4.799571798675273,8.305041661370591,100*(exp(b - se^2/2) - 1),reported,0.015008183041349188,0.023712929205331714,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6329113924050633,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c1,3,1,34,Distance train station (>1km),transit_distance,D_location,binary,binary,0.01,0.02,,,,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample (Turin, 2017-2018); coefficients for dwellings < 1 year on the market in a fully interacted specification; month-year and urban macro-area fixed effects; two-way clustered SE",pct_premium,0.9848177250407986,2.020100334168336,100*(exp(b - se^2/2) - 1),reported,0.006040669802439581,0.012081339604879164,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c2,3,2,34,Distance train station (>1km),transit_distance,D_location,binary,binary,-0.093,0.019,,,***,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 1)",pct_premium,-8.897095528809995,1.731267650562667,100*(exp(b - se^2/2) - 1),reported,-0.05903292585708897,0.012060490228867638,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.894736842105263,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c3,3,3,34,Distance train station (>1km),transit_distance,D_location,binary,binary,0.02,0.024,,,,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,Central subsample (OMI central districts); coefficients for dwellings < 1 year on the market (fully interacted specification),pct_premium,1.9907564346556716,2.448483216064214,100*(exp(b - se^2/2) - 1),reported,0.019759141878785764,0.023710970254542916,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8333333333333334,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c4,3,4,34,Distance train station (>1km),transit_distance,D_location,binary,binary,-0.155,0.037,,,***,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,"Central subsample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 3)",pct_premium,-14.417083811865316,3.16873615668937,100*(exp(b - se^2/2) - 1),reported,-0.09886243577027844,0.023599420151614852,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.1891891891891895,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c1,3,1,34,Car park,parking,A_structural,binary,binary,0.077,0.027,,,***,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample (Turin, 2017-2018); coefficients for dwellings < 1 year on the market in a fully interacted specification; month-year and urban macro-area fixed effects; two-way clustered SE",pct_premium,7.964847279436893,2.916113606260021,100*(exp(b - se^2/2) - 1),reported,0.034434386290731415,0.012074395192853875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8518518518518516,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c2,3,2,34,Car park,parking,A_structural,binary,binary,0.186,0.026,,,***,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 1)",pct_premium,20.401523444487978,3.1314978769818373,100*(exp(b - se^2/2) - 1),reported,0.08610860112331188,0.012036686178527467,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.153846153846154,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c3,3,3,34,Car park,parking,A_structural,binary,binary,0.135,0.048,,,***,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,Central subsample (OMI central districts); coefficients for dwellings < 1 year on the market (fully interacted specification),pct_premium,14.321903714386552,5.49377656488631,100*(exp(b - se^2/2) - 1),reported,0.06655224768512036,0.023663021399153907,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8125,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c4,3,4,34,Car park,parking,A_structural,binary,binary,0.159,0.044,,,***,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,"Central subsample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 3)",pct_premium,17.12036726255437,5.158286965395157,100*(exp(b - se^2/2) - 1),reported,0.08538657198965882,0.02362898847512571,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6136363636363638,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c1,3,1,34,Commercial,commercial_distance,D_location,binary,binary,0.344,0.037,,,***,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample (Turin, 2017-2018); coefficients for dwellings < 1 year on the market in a fully interacted specification; month-year and urban macro-area fixed effects; two-way clustered SE",pct_premium,40.961342481272034,5.21914095137841,100*(exp(b - se^2/2) - 1),reported,0.11162387803853778,0.01200605664949389,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.297297297297296,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c2,3,2,34,Commercial,commercial_distance,D_location,binary,binary,0.374,0.084,,,***,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 1)",pct_premium,44.84181066928754,12.209712063837562,100*(exp(b - se^2/2) - 1),reported,0.05371405181222328,0.012064118588841596,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.452380952380952,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c3,3,3,34,Commercial,commercial_distance,D_location,binary,binary,0.3,0.057,,,***,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,Central subsample (OMI central districts); coefficients for dwellings < 1 year on the market (fully interacted specification),pct_premium,34.766774211786625,7.694195203183218,100*(exp(b - se^2/2) - 1),reported,0.12385783947578168,0.02353298950039852,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.263157894736842,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c4,3,4,34,Commercial,commercial_distance,D_location,binary,binary,0.406,0.028,,,***,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,"Central subsample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 3)",pct_premium,50.021435315205245,4.202247146882456,100*(exp(b - se^2/2) - 1),reported,0.3251864992173418,0.022426655118437364,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.5,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c1,3,1,34,View river/mountains,view,E_environment,binary,binary,0.144,0.021,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample (Turin, 2017-2018); coefficients for dwellings < 1 year on the market in a fully interacted specification; month-year and urban macro-area fixed effects; two-way clustered SE",pct_premium,15.462948465229754,2.4252566279023187,100*(exp(b - se^2/2) - 1),reported,0.08256214353922148,0.012040312599469801,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.857142857142856,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c2,3,2,34,View river/mountains,view,E_environment,binary,binary,0.131,0.012,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 1)",pct_premium,13.988570658646138,1.3679613375743884,100*(exp(b - se^2/2) - 1),reported,0.1307579947648053,0.01197783158150888,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.916666666666666,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c3,3,3,34,View river/mountains,view,E_environment,binary,binary,0.117,0.031,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,Central subsample (OMI central districts); coefficients for dwellings < 1 year on the market (fully interacted specification),pct_premium,12.357942005227596,3.484770232040664,100*(exp(b - se^2/2) - 1),reported,0.08915085965084166,0.023621167941675993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.774193548387097,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c4,3,4,34,View river/mountains,view,E_environment,binary,binary,0.188,0.027,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,"Central subsample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 3)",pct_premium,20.639370469362195,3.2584504914439343,100*(exp(b - se^2/2) - 1),reported,0.16292445817469367,0.02339872537615282,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.962962962962963,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c1,3,1,34,Number of baths+,bathrooms,A_structural,log,count,0.449,0.036,,,***,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample (Turin, 2017-2018); coefficients for dwellings < 1 year on the market in a fully interacted specification; month-year and urban macro-area fixed effects; two-way clustered SE",elasticity,0.449,0.036,b (log-log),reported,0.14900180565220641,0.011946692658083366,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.472222222222223,6851.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,True
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c2,3,2,34,Number of baths+,bathrooms,A_structural,log,count,0.11,0.016,,,***,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 1)",elasticity,0.11,0.016,b (log-log),reported,0.082775677843489,0.012040098595416581,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.875,6851.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c3,3,3,34,Number of baths+,bathrooms,A_structural,log,count,0.386,0.069,,,***,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,Central subsample (OMI central districts); coefficients for dwellings < 1 year on the market (fully interacted specification),elasticity,0.386,0.069,b (log-log),reported,0.1315174893622056,0.023509603020705146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.594202898550725,1778.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c4,3,4,34,Number of baths+,bathrooms,A_structural,log,count,0.06,0.028,,,**,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,"Central subsample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 3)",elasticity,0.06,0.028,b (log-log),reported,0.05075364788740703,0.02368503568078995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.142857142857143,1778.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c1,3,1,34,Economic building,condition,A_structural,binary,binary,-0.277,0.028,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample (Turin, 2017-2018); coefficients for dwellings < 1 year on the market in a fully interacted specification; month-year and urban macro-area fixed effects; two-way clustered SE",pct_premium,-24.224260201712553,2.122552591909423,100*(exp(b - se^2/2) - 1),reported,-0.11867648842781392,0.011996179335663498,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.892857142857144,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c2,3,2,34,Economic building,condition,A_structural,binary,binary,-0.327,0.009,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 1)",pct_premium,-27.89454602736148,0.6489753687239463,100*(exp(b - se^2/2) - 1),reported,-0.4019431994693699,0.011062656866129445,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-36.333333333333336,6851.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c3,3,3,34,Economic building,condition,A_structural,binary,binary,-0.364,0.051,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,Central subsample (OMI central districts); coefficients for dwellings < 1 year on the market (fully interacted specification),pct_premium,-30.601192387568375,3.5439450931888437,100*(exp(b - se^2/2) - 1),reported,-0.16689042860836664,0.023382999612710707,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.137254901960785,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c4,3,4,34,Economic building,condition,A_structural,binary,binary,-0.389,0.016,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,"Central subsample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 3)",pct_premium,-32.23524744208284,1.0843748320223539,100*(exp(b - se^2/2) - 1),reported,-0.4995030416328341,0.020545112252250246,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-24.3125,1778.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c1,3,1,34,Age+,age,A_structural,log,years,-0.047,0.015,,,***,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample (Turin, 2017-2018); coefficients for dwellings < 1 year on the market in a fully interacted specification; month-year and urban macro-area fixed effects; two-way clustered SE",elasticity,-0.047,0.015,b (log-log),reported,-0.03782845956891839,0.012072912628378209,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.1333333333333333,6851.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c2,3,2,34,Age+,age,A_structural,log,years,-0.016,0.008,,,**,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 1)",elasticity,-0.016,0.008,b (log-log),reported,-0.024156069257723893,0.012078034628861947,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,6851.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c3,3,3,34,Age+,age,A_structural,log,years,-0.064,0.02,,,***,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,Central subsample (OMI central districts); coefficients for dwellings < 1 year on the market (fully interacted specification),elasticity,-0.064,0.02,b (log-log),reported,-0.07567232466537065,0.023647601457928328,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2,1778.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c4,3,4,34,Age+,age,A_structural,log,years,0.01,0.017,,,,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,"Central subsample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 3)",elasticity,0.01,0.017,b (log-log),reported,0.01394899584409664,0.023713292934964283,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5882352941176471,1778.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c1,3,1,34,Total surface+,living_area,A_structural,log,m2,1.028,0.029,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample (Turin, 2017-2018); coefficients for dwellings < 1 year on the market in a fully interacted specification; month-year and urban macro-area fixed effects; two-way clustered SE",elasticity,1.028,0.029,b (log-log),reported,0.3936855625607998,0.011105915675353302,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.44827586206897,6851.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c2,3,2,34,Total surface+,living_area,A_structural,log,m2,0.961,0.014,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 1)",elasticity,0.961,0.014,b (log-log),reported,0.6383561685653841,0.00929967363154566,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),68.64285714285714,6851.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c3,3,3,34,Total surface+,living_area,A_structural,log,m2,1.093,0.04,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,Central subsample (OMI central districts); coefficients for dwellings < 1 year on the market (fully interacted specification),elasticity,1.093,0.04,b (log-log),reported,0.5438249108041516,0.019902101035833546,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.325,1778.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c4,3,4,34,Total surface+,living_area,A_structural,log,m2,0.948,0.026,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,"Central subsample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 3)",elasticity,0.948,0.026,b (log-log),reported,0.6540837336321846,0.017939005352781437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),36.46153846153846,1778.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c1,3,1,34,Floor level+,floor_level,A_structural,log,count,-0.011,0.01,,,,,,high,Log of floor level (1-9),"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample (Turin, 2017-2018); coefficients for dwellings < 1 year on the market in a fully interacted specification; month-year and urban macro-area fixed effects; two-way clustered SE",elasticity,-0.011,0.01,b (log-log),reported,-0.013288542599919302,0.012080493272653911,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0999999999999999,6851.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,True
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c2,3,2,34,Floor level+,floor_level,A_structural,log,count,0.02,0.005,,,***,,,high,Log of floor level (1-9),"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,6861.0,0.865,se,"Full sample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 1)",elasticity,0.02,0.005,b (log-log),reported,0.04826990761706643,0.01206747690426661,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,6851.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c3,3,3,34,Floor level+,floor_level,A_structural,log,count,0.001,0.014,,,,,,high,Log of floor level (1-9),"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,Central subsample (OMI central districts); coefficients for dwellings < 1 year on the market (fully interacted specification),elasticity,0.001,0.014,b (log-log),reported,0.0016939690175866119,0.023715566246212568,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.07142857142857142,1778.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T3-c4,3,4,34,Floor level+,floor_level,A_structural,log,count,0.024,0.011,,,**,,,high,Log of floor level (1-9),"log(price), real transaction price (EUR, CPI-deflated)",log,OLS,1788.0,0.873,se,"Central subsample; coefficients for dwellings >= 1 year on the market (fully interacted specification, same regression as column 3)",elasticity,0.024,0.011,b (log-log),reported,0.051673999382555645,0.023683916383671334,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.181818181818182,1778.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,ols,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c1,4,1,35,Green (<500m),green_space,E_environment,binary,binary,0.108,0.027,,,***,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.10; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.612; SE type not stated",pct_premium,11.36417489806143,3.0079289125434627,100*(exp(b - se^2/2) - 1),reported,0.11634594543263002,0.029086486358157505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c2,4,2,35,Green (<500m),green_space,E_environment,binary,binary,0.118,0.023,,,***,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.20; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.616; SE type not stated",pct_premium,12.494652365759528,2.5880614561448874,100*(exp(b - se^2/2) - 1),reported,0.14857902666275702,0.0289603187563001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.130434782608695,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c3,4,3,35,Green (<500m),green_space,E_environment,binary,binary,0.116,0.024,,,***,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.30; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.624; SE type not stated",pct_premium,12.267249589049456,2.695190093119811,100*(exp(b - se^2/2) - 1),reported,0.1401489603533298,0.028996336624826854,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.833333333333333,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c4,4,4,35,Green (<500m),green_space,E_environment,binary,binary,0.105,0.021,,,***,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.40; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.635; SE type not stated",pct_premium,11.046572566565116,2.332492281746981,100*(exp(b - se^2/2) - 1),reported,0.14488189694993614,0.028976379389987234,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.999999999999999,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c5,4,5,35,Green (<500m),green_space,E_environment,binary,binary,0.115,0.021,,,***,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.50; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.643; SE type not stated",pct_premium,12.162609174983285,2.3559342189010706,100*(exp(b - se^2/2) - 1),reported,0.15834888669511268,0.028915883657368406,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.476190476190476,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c6,4,6,35,Green (<500m),green_space,E_environment,binary,binary,0.099,0.021,,,***,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.60; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.65; SE type not stated",pct_premium,10.382287977784621,2.3185392290736524,100*(exp(b - se^2/2) - 1),reported,0.13676238010276626,0.02901020183998072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.714285714285714,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c7,4,7,35,Green (<500m),green_space,E_environment,binary,binary,0.086,0.021,,,***,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.70; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.654; SE type not stated",pct_premium,8.956605250111839,2.2885932894407706,100*(exp(b - se^2/2) - 1),reported,0.11907725846659677,0.029077004974401535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.095238095238095,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c8,4,8,35,Green (<500m),green_space,E_environment,binary,binary,0.044,0.025,,,*,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.80; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.658; SE type not stated",pct_premium,4.465584892175545,2.6124558872211097,100*(exp(b - se^2/2) - 1),reported,0.05147392475219968,0.029246548154658915,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7599999999999998,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c9,4,9,35,Green (<500m),green_space,E_environment,binary,binary,0.055,0.03,,,*,,,high,Dummy = 1 if a green area lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.90; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.661; SE type not stated",pct_premium,5.606527835758324,3.1696218440264827,100*(exp(b - se^2/2) - 1),reported,0.05361262989388799,0.02924325266939345,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8333333333333335,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c1,4,1,35,Transport (<500m),transit_distance,D_location,binary,binary,0.381,0.203,,,*,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.10; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.612; SE type not stated",pct_premium,43.389640845945166,29.714076389817492,100*(exp(b - se^2/2) - 1),reported,0.05488133115242958,0.029241234183577967,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.876847290640394,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,True
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c2,4,2,35,Transport (<500m),transit_distance,D_location,binary,binary,0.103,0.167,,,,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.20; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.616; SE type not stated",pct_premium,9.314132398626839,18.51180653156932,100*(exp(b - se^2/2) - 1),reported,0.018059288951974936,0.02928059470854189,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6167664670658682,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c3,4,3,35,Transport (<500m),transit_distance,D_location,binary,binary,0.109,0.16,,,,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.30; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.624; SE type not stated",pct_premium,10.097923782342665,17.842597605463165,100*(exp(b - se^2/2) - 1),reported,0.019946689460298025,0.02927954416190536,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.68125,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c4,4,4,35,Transport (<500m),transit_distance,D_location,binary,binary,-0.08,0.15,,,,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.40; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.635; SE type not stated",pct_premium,-8.721051499903309,13.846745195799537,100*(exp(b - se^2/2) - 1),reported,-0.01561695958345289,0.02928179921897417,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5333333333333333,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c5,4,5,35,Transport (<500m),transit_distance,D_location,binary,binary,-0.057,0.125,,,,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.50; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.643; SE type not stated",pct_premium,-6.2756820000294695,11.807425867081541,100*(exp(b - se^2/2) - 1),reported,-0.013352938428474168,0.029282759711566155,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.456,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c6,4,6,35,Transport (<500m),transit_distance,D_location,binary,binary,-0.037,0.106,,,,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.60; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.65; SE type not stated",pct_premium,-4.172261788193254,10.214967034699967,100*(exp(b - se^2/2) - 1),reported,-0.010221717970983117,0.02928384067362731,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3490566037735849,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c7,4,7,35,Transport (<500m),transit_distance,D_location,binary,binary,-0.12,0.098,,,,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.70; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.654; SE type not stated",pct_premium,-11.732834572884677,8.691820279828145,100*(exp(b - se^2/2) - 1),reported,-0.035836603524221494,0.029266559544780895,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2244897959183672,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c8,4,8,35,Transport (<500m),transit_distance,D_location,binary,binary,-0.001,0.09,,,,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.80; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.658; SE type not stated",pct_premium,-0.5037270187532417,8.991004498500374,100*(exp(b - se^2/2) - 1),reported,-0.00032539298980549807,0.02928536908249482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.011111111111111112,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c9,4,9,35,Transport (<500m),transit_distance,D_location,binary,binary,-0.025,0.102,,,,,,high,Dummy = 1 if a bus/metro stop lies within 500 m,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.90; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.661; SE type not stated",pct_premium,-2.9750476651571933,9.948161102688992,100*(exp(b - se^2/2) - 1),reported,-0.007177602024931401,0.029284616261720114,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2450980392156863,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c1,4,1,35,Trainstation (>1km),transit_distance,D_location,binary,binary,-0.211,0.062,,,***,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.10; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.612; SE type not stated",pct_premium,-19.17808241463338,5.020599214663913,100*(exp(b - se^2/2) - 1),reported,-0.0991733986066375,0.029140998642708648,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.403225806451613,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c2,4,2,35,Trainstation (>1km),transit_distance,D_location,binary,binary,-0.168,0.056,,,***,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.20; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.616; SE type not stated",pct_premium,-15.597064146745787,4.733981474234089,100*(exp(b - se^2/2) - 1),reported,-0.08751899489873673,0.029172998299578912,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c3,4,3,35,Trainstation (>1km),transit_distance,D_location,binary,binary,-0.128,0.049,,,***,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.30; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.624; SE type not stated",pct_premium,-12.120225106820282,4.311281557808755,100*(exp(b - se^2/2) - 1),reported,-0.0762776843237997,0.029200051030204576,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6122448979591835,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c4,4,4,35,Trainstation (>1km),transit_distance,D_location,binary,binary,-0.134,0.045,,,***,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.40; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.635; SE type not stated",pct_premium,-12.629500969260288,3.935655290715003,100*(exp(b - se^2/2) - 1),reported,-0.08687561704349152,0.029174647514605363,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.977777777777778,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c5,4,5,35,Trainstation (>1km),transit_distance,D_location,binary,binary,-0.124,0.046,,,***,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.50; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.643; SE type not stated",pct_premium,-11.755428075142337,4.063547268060654,100*(exp(b - se^2/2) - 1),reported,-0.07869832892690214,0.029194541376108857,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6956521739130435,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c6,4,6,35,Trainstation (>1km),transit_distance,D_location,binary,binary,-0.126,0.049,,,***,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.60; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.65; SE type not stated",pct_premium,-11.944289680252496,4.319912749238739,100*(exp(b - se^2/2) - 1),reported,-0.07509261920093487,0.029202685244808006,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.571428571428571,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c7,4,7,35,Trainstation (>1km),transit_distance,D_location,binary,binary,-0.111,0.059,,,*,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.70; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.654; SE type not stated",pct_premium,-10.66175372125886,5.280138618681283,100*(exp(b - se^2/2) - 1),reported,-0.055012770876958515,0.029241022358022995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.88135593220339,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c8,4,8,35,Trainstation (>1km),transit_distance,D_location,binary,binary,-0.144,0.06,,,**,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.80; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.658; SE type not stated",pct_premium,-13.56694479904139,5.19532648835523,100*(exp(b - se^2/2) - 1),reported,-0.07011192760364504,0.029213303168185437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c9,4,9,35,Trainstation (>1km),transit_distance,D_location,binary,binary,-0.158,0.08,,,**,,,high,Dummy = 1 if the train station is more than 1 km away (reverse-coded proximity),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.90; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.661; SE type not stated",pct_premium,-14.887817028236384,6.830798255747854,100*(exp(b - se^2/2) - 1),reported,-0.05774210517854627,0.02923650895116267,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.975,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c1,4,1,35,Car park,parking,A_structural,binary,binary,-0.134,0.132,,,,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.10; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.612; SE type not stated",pct_premium,-13.299626998319336,11.54458885276401,100*(exp(b - se^2/2) - 1),reported,-0.02971595950969347,0.02927243772596671,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0151515151515151,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,True
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c2,4,2,35,Car park,parking,A_structural,binary,binary,0.045,0.142,,,,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.20; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.616; SE type not stated",pct_premium,3.553479146516003,14.85359561070378,100*(exp(b - se^2/2) - 1),reported,0.009280175562689267,0.02928410955337502,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.31690140845070425,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c3,4,3,35,Car park,parking,A_structural,binary,binary,0.206,0.097,,,**,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.30; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.624; SE type not stated",pct_premium,22.29861108286095,11.918906078754526,100*(exp(b - se^2/2) - 1),reported,0.06207373732880237,0.029228895732494323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1237113402061856,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c4,4,4,35,Car park,parking,A_structural,binary,binary,0.181,0.067,,,***,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.40; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.635; SE type not stated",pct_premium,19.572835284223068,8.029381701264438,100*(exp(b - se^2/2) - 1),reported,0.07886777622378689,0.02919414920991007,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7014925373134324,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c5,4,5,35,Car park,parking,A_structural,binary,binary,0.221,0.056,,,***,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.50; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.643; SE type not stated",pct_premium,24.536915997348487,6.985011211158763,100*(exp(b - se^2/2) - 1),reported,0.1148084169992712,0.029091725574475962,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.946428571428571,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,True
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c6,4,6,35,Car park,parking,A_structural,binary,binary,0.207,0.045,,,***,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.60; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.65; SE type not stated",pct_premium,22.873784467625804,5.534921573013387,100*(exp(b - se^2/2) - 1),reported,0.13350674393288844,0.029023205202801834,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.6,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c7,4,7,35,Car park,parking,A_structural,binary,binary,0.206,0.046,,,***,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.70; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.654; SE type not stated",pct_premium,22.745387057406695,5.652264738378435,100*(exp(b - se^2/2) - 1),reported,0.13003402546614728,0.029036724133217357,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.478260869565217,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c8,4,8,35,Car park,parking,A_structural,binary,binary,0.216,0.056,,,***,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.80; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.658; SE type not stated",pct_premium,23.91578553753253,6.950173322403761,100*(exp(b - se^2/2) - 1),reported,0.11224404025854419,0.02910030673369664,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.857142857142857,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c9,4,9,35,Car park,parking,A_structural,binary,binary,0.218,0.064,,,***,,,high,Dummy = 1 if a car park / parking facility is included or nearby,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.90; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.661; SE type not stated",pct_premium,24.104280751620678,7.958957232761996,100*(exp(b - se^2/2) - 1),reported,0.09926065871134777,0.029140743841863565,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.40625,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c1,4,1,35,Commercial,commercial_distance,D_location,binary,binary,0.066,0.075,,,,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.10; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.612; SE type not stated",pct_premium,6.522655048600634,8.01170037874495,100*(exp(b - se^2/2) - 1),reported,0.02576257245852626,0.029275650521052566,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8800000000000001,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c2,4,2,35,Commercial,commercial_distance,D_location,binary,binary,0.111,0.063,,,*,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.20; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.616; SE type not stated",pct_premium,11.517963549183774,7.0395879131830865,100*(exp(b - se^2/2) - 1),reported,0.05152948462271119,0.029246464245322568,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7619047619047619,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c3,4,3,35,Commercial,commercial_distance,D_location,binary,binary,0.197,0.07,,,***,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.30; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.624; SE type not stated",pct_premium,21.47642195775923,8.52420828494136,100*(exp(b - se^2/2) - 1),reported,0.08213890284169346,0.02918641217725149,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.814285714285714,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c4,4,4,35,Commercial,commercial_distance,D_location,binary,binary,0.274,0.077,,,***,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.40; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.635; SE type not stated",pct_premium,31.132162147586364,10.12715397723818,100*(exp(b - se^2/2) - 1),reported,0.10364899687435224,0.029127637807755916,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.558441558441559,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c5,4,5,35,Commercial,commercial_distance,D_location,binary,binary,0.465,0.073,,,***,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.50; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.643; SE type not stated",pct_premium,58.777791336518305,11.621703578875838,100*(exp(b - se^2/2) - 1),reported,0.18338039489783087,0.028788750166756232,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.369863013698631,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c6,4,6,35,Commercial,commercial_distance,D_location,binary,binary,0.529,0.058,,,***,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.60; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.65; SE type not stated",pct_premium,69.43818770232564,9.84395850785941,100*(exp(b - se^2/2) - 1),reported,0.25805599571764365,0.028293474010630117,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.120689655172415,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c7,4,7,35,Commercial,commercial_distance,D_location,binary,binary,0.593,0.052,,,***,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.70; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.654; SE type not stated",pct_premium,80.6963839382382,9.40892423492299,100*(exp(b - se^2/2) - 1),reported,0.3167676740542835,0.027777266527525706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.403846153846153,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c8,4,8,35,Commercial,commercial_distance,D_location,binary,binary,0.667,0.062,,,***,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.80; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.658; SE type not stated",pct_premium,94.46421975127895,12.07997704251789,100*(exp(b - se^2/2) - 1),reported,0.3004933471633239,0.027931915328524855,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.758064516129034,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c9,4,9,35,Commercial,commercial_distance,D_location,binary,binary,0.773,0.093,,,***,,,high,"Dummy = 1 if commercial activities/services lie within 500 m (proximity, not distance)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.90; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.661; SE type not stated",pct_premium,115.69075369848987,20.14617411535208,100*(exp(b - se^2/2) - 1),reported,0.2365091029228773,0.02845452337881965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.311827956989248,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,True
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c1,4,1,35,View river/mountains,view,E_environment,binary,binary,0.195,0.054,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.10; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.612; SE type not stated",pct_premium,21.354035417604766,6.562679327044545,100*(exp(b - se^2/2) - 1),reported,0.10516629141209013,0.029122973006424954,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.611111111111111,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c2,4,2,35,View river/mountains,view,E_environment,binary,binary,0.22,0.042,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.20; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.616; SE type not stated",pct_premium,24.497817544503665,5.2335222684669995,100*(exp(b - se^2/2) - 1),reported,0.15162594640085109,0.028946771585617027,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.238095238095238,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c3,4,3,35,View river/mountains,view,E_environment,binary,binary,0.215,0.036,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.30; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.624; SE type not stated",pct_premium,23.905872671209472,4.463502829077822,100*(exp(b - se^2/2) - 1),reported,0.17228355019094516,0.028847478171507093,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.972222222222222,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c4,4,4,35,View river/mountains,view,E_environment,binary,binary,0.219,0.035,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.40; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.635; SE type not stated",pct_premium,24.40690509860106,4.356909468406359,100*(exp(b - se^2/2) - 1),reported,0.1802416635142635,0.028805745310498735,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.257142857142856,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c5,4,5,35,View river/mountains,view,E_environment,binary,binary,0.229,0.037,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.50; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.643; SE type not stated",pct_premium,25.64816828746168,4.6521655443364045,100*(exp(b - se^2/2) - 1),reported,0.17834680021663873,0.0288158585502866,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.1891891891891895,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c6,4,6,35,View river/mountains,view,E_environment,binary,binary,0.195,0.038,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.60; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.65; SE type not stated",pct_premium,21.443384864235114,4.618181748660977,100*(exp(b - se^2/2) - 1),reported,0.1486114303120719,0.028960176163378114,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.131578947368421,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c7,4,7,35,View river/mountains,view,E_environment,binary,binary,0.172,0.039,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.70; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.654; SE type not stated",pct_premium,18.67749475875222,4.631943549534233,100*(exp(b - se^2/2) - 1),reported,0.12809204319854556,0.02904412607408882,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.41025641025641,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c8,4,8,35,View river/mountains,view,E_environment,binary,binary,0.142,0.045,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.80; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.658; SE type not stated",pct_premium,15.141025526659902,5.186594918416523,100*(exp(b - se^2/2) - 1),reported,0.09201953021957955,0.029161118731556898,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1555555555555554,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c9,4,9,35,View river/mountains,view,E_environment,binary,binary,0.149,0.045,,,***,,,high,Dummy = 1 if the dwelling enjoys a panoramic view of the river and/or mountains,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.90; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.661; SE type not stated",pct_premium,15.949840254235603,5.223028451440884,100*(exp(b - se^2/2) - 1),reported,0.09651443335888903,0.02914865437013427,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.311111111111111,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c1,4,1,35,Number of baths+,bathrooms,A_structural,log,count,0.036,0.055,,,,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.10; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.612; SE type not stated",elasticity,0.036,0.055,b (log-log),reported,0.01916508558973059,0.029279991873199518,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6545454545454545,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c2,4,2,35,Number of baths+,bathrooms,A_structural,log,count,0.041,0.05,,,,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.20; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.616; SE type not stated",elasticity,0.041,0.05,b (log-log),reported,0.024007082805774353,0.02927693025094433,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.82,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c3,4,3,35,Number of baths+,bathrooms,A_structural,log,count,0.043,0.044,,,,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.30; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.624; SE type not stated",elasticity,0.043,0.044,b (log-log),reported,0.028608080092289552,0.02927338428048233,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9772727272727273,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c4,4,4,35,Number of baths+,bathrooms,A_structural,log,count,0.075,0.04,,,*,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.40; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.635; SE type not stated",elasticity,0.075,0.04,b (log-log),reported,0.054827476552053105,0.029241320827761656,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.875,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c5,4,5,35,Number of baths+,bathrooms,A_structural,log,count,0.12,0.038,,,***,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.50; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.643; SE type not stated",elasticity,0.12,0.038,b (log-log),reported,0.09208716512464571,0.02916093562280447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1578947368421053,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c6,4,6,35,Number of baths+,bathrooms,A_structural,log,count,0.101,0.037,,,***,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.60; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.65; SE type not stated",elasticity,0.101,0.037,b (log-log),reported,0.07968692924032748,0.029192241404872442,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.72972972972973,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c7,4,7,35,Number of baths+,bathrooms,A_structural,log,count,0.095,0.041,,,**,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.70; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.654; SE type not stated",elasticity,0.095,0.041,b (log-log),reported,0.0677006622935388,0.02921818056879043,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.317073170731707,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c8,4,8,35,Number of baths+,bathrooms,A_structural,log,count,0.092,0.045,,,**,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.80; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.658; SE type not stated",elasticity,0.092,0.045,b (log-log),reported,0.05976528898700784,0.029233021787123406,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0444444444444443,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c9,4,9,35,Number of baths+,bathrooms,A_structural,log,count,0.106,0.052,,,**,,,high,Log of number of bathrooms (+ = logarithmic form),"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.90; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.661; SE type not stated",elasticity,0.106,0.052,b (log-log),reported,0.05959101255407085,0.02923332691331778,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0384615384615383,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c1,4,1,35,Economic Building,condition,A_structural,binary,binary,-0.381,0.032,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.10; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.612; SE type not stated",pct_premium,-31.717180792937384,2.186169246783679,100*(exp(b - se^2/2) - 1),reported,-0.3292389239515902,0.027652613035304162,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.90625,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c2,4,2,35,Economic Building,condition,A_structural,binary,binary,-0.361,0.025,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.20; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.616; SE type not stated",pct_premium,-30.32387734415152,1.742447496167182,100*(exp(b - se^2/2) - 1),reported,-0.38948673623346464,0.026972765667137442,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.44,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c3,4,3,35,Economic Building,condition,A_structural,binary,binary,-0.371,0.027,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.30; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.624; SE type not stated",pct_premium,-31.020753362377285,1.8631186422087302,100*(exp(b - se^2/2) - 1),reported,-0.37331142051781113,0.027168216587549598,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.74074074074074,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c4,4,4,35,Economic Building,condition,A_structural,binary,binary,-0.369,0.025,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.40; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.635; SE type not stated",pct_premium,-30.87906262329674,1.7285635261257715,100*(exp(b - se^2/2) - 1),reported,-0.39677167043906936,0.026881549487741827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.76,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c5,4,5,35,Economic Building,condition,A_structural,binary,binary,-0.392,0.025,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.50; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.643; SE type not stated",pct_premium,-32.45070105850583,1.689260284901565,100*(exp(b - se^2/2) - 1),reported,-0.41730142919947294,0.026613611556088837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.68,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c6,4,6,35,Economic Building,condition,A_structural,binary,binary,-0.402,0.026,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.60; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.65; SE type not stated",pct_premium,-33.12453315924835,1.7393499387949014,100*(exp(b - se^2/2) - 1),reported,-0.4124823766672258,0.02667796466006933,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.461538461538463,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c7,4,7,35,Economic Building,condition,A_structural,binary,binary,-0.415,0.026,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.70; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.654; SE type not stated",pct_premium,-33.988287659418724,1.7168847298329553,100*(exp(b - se^2/2) - 1),reported,-0.42346034897489854,0.02653004595987316,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.961538461538462,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c8,4,8,35,Economic Building,condition,A_structural,binary,binary,-0.422,0.029,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.80; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.658; SE type not stated",pct_premium,-34.45416388047199,1.9016287142409811,100*(exp(b - se^2/2) - 1),reported,-0.39203859270595465,0.026941040730977923,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.551724137931034,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c9,4,9,35,Economic Building,condition,A_structural,binary,binary,-0.376,0.038,,,***,,,high,Realtor/cadastral building class 'economic' (lower-quality building) vs base 'residential' building,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.90; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.661; SE type not stated",pct_premium,-31.389321492781153,2.609088865560744,100*(exp(b - se^2/2) - 1),reported,-0.27832158690198466,0.028128245484775043,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.894736842105264,1166.0,binary,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c1,4,1,35,Age+,age,A_structural,log,years,-0.006,0.033,,,,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.10; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.612; SE type not stated",elasticity,-0.006,0.033,b (log-log),reported,-0.005324537363559542,0.02928495549957748,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.18181818181818182,1166.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c2,4,2,35,Age+,age,A_structural,log,years,-0.012,0.025,,,,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.20; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.616; SE type not stated",elasticity,-0.012,0.025,b (log-log),reported,-0.014055589289793608,0.02928247768707002,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.48,1166.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c3,4,3,35,Age+,age,A_structural,log,years,0.017,0.022,,,,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.30; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.624; SE type not stated",elasticity,0.017,0.022,b (log-log),reported,0.02262381250546078,0.029277875007066887,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7727272727272728,1166.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c4,4,4,35,Age+,age,A_structural,log,years,0.034,0.022,,,,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.40; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.635; SE type not stated",elasticity,0.034,0.022,b (log-log),reported,0.045212925860845604,0.029255422615841267,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5454545454545456,1166.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c5,4,5,35,Age+,age,A_structural,log,years,0.048,0.024,,,**,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.50; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.643; SE type not stated",elasticity,0.048,0.024,b (log-log),reported,0.05847053462046861,0.029235267310234306,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,1166.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c6,4,6,35,Age+,age,A_structural,log,years,0.034,0.023,,,,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.60; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.65; SE type not stated",elasticity,0.034,0.023,b (log-log),reported,0.04325090715379687,0.029257966604039058,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4782608695652175,1166.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c7,4,7,35,Age+,age,A_structural,log,years,0.031,0.021,,,,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.70; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.654; SE type not stated",elasticity,0.031,0.021,b (log-log),reported,0.04319044473109238,0.029258043204933554,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.476190476190476,1166.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c8,4,8,35,Age+,age,A_structural,log,years,-0.002,0.026,,,,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.80; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.658; SE type not stated",elasticity,-0.002,0.026,b (log-log),reported,-0.002252715101936214,0.02928529632517078,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.07692307692307693,1166.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c9,4,9,35,Age+,age,A_structural,log,years,-0.008,0.028,,,,,,high,"Log of age in years, measured from the date of the last renovation if any (years since construction or renewal)","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.90; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.661; SE type not stated",elasticity,-0.008,0.028,b (log-log),reported,-0.008366955868521896,0.029284345539826635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2857142857142857,1166.0,years,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c1,4,1,35,Total Surface+,living_area,A_structural,log,m2,1.002,0.052,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.10; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.612; SE type not stated",elasticity,1.002,0.052,b (log-log),reported,0.4914559581711084,0.025504700424049537,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.26923076923077,1166.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c2,4,2,35,Total Surface+,living_area,A_structural,log,m2,1.0,0.043,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.20; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.616; SE type not stated",elasticity,1.0,0.043,b (log-log),reported,0.5629062152403098,0.024204967255333318,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.255813953488374,1166.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c3,4,3,35,Total Surface+,living_area,A_structural,log,m2,0.95,0.041,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.30; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.624; SE type not stated",elasticity,0.95,0.041,b (log-log),reported,0.561496906764523,0.024233024397205732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.17073170731707,1166.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c4,4,4,35,Total Surface+,living_area,A_structural,log,m2,0.933,0.037,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.40; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.635; SE type not stated",elasticity,0.933,0.037,b (log-log),reported,0.5940454742107663,0.023558073468165436,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.216216216216218,1166.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c5,4,5,35,Total Surface+,living_area,A_structural,log,m2,0.904,0.033,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.50; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.643; SE type not stated",elasticity,0.904,0.033,b (log-log),reported,0.6257606452381149,0.022843032403603754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.393939393939394,1166.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c6,4,6,35,Total Surface+,living_area,A_structural,log,m2,0.911,0.03,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.60; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.65; SE type not stated",elasticity,0.911,0.03,b (log-log),reported,0.6645350522435414,0.021883700952037587,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.366666666666667,1166.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c7,4,7,35,Total Surface+,living_area,A_structural,log,m2,0.917,0.034,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.70; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.654; SE type not stated",elasticity,0.917,0.034,b (log-log),reported,0.619823137086488,0.02298144674039323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.970588235294116,1166.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c8,4,8,35,Total Surface+,living_area,A_structural,log,m2,0.917,0.033,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.80; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.658; SE type not stated",elasticity,0.917,0.033,b (log-log),reported,0.631189676590117,0.02271456851414816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.78787878787879,1166.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c9,4,9,35,Total Surface+,living_area,A_structural,log,m2,0.899,0.035,,,***,,,high,Log of total surface in square metres,"log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.90; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.661; SE type not stated",elasticity,0.899,0.035,b (log-log),reported,0.6011326110809294,0.023403383078790353,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.685714285714283,1166.0,m2,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c1,4,1,35,Floor level,floor_level,A_structural,log,count,0.033,0.019,,,*,,,high,"Log of floor level (1-9) ; printed without the '+' log marker in Table 4 (model described as log-log), transform assumed as in Table 3","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.10; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.612; SE type not stated",elasticity,0.033,0.019,b (log-log),reported,0.050798395617018564,0.02924756111282887,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.736842105263158,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c2,4,2,35,Floor level,floor_level,A_structural,log,count,0.028,0.015,,,*,,,high,"Log of floor level (1-9) ; printed without the '+' log marker in Table 4 (model described as log-log), transform assumed as in Table 3","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.20; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.616; SE type not stated",elasticity,0.028,0.015,b (log-log),reported,0.054584526524690695,0.02924171063822716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8666666666666667,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c3,4,3,35,Floor level,floor_level,A_structural,log,count,0.038,0.017,,,**,,,high,"Log of floor level (1-9) ; printed without the '+' log marker in Table 4 (model described as log-log), transform assumed as in Table 3","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.30; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.624; SE type not stated",elasticity,0.038,0.017,b (log-log),reported,0.06532160834267409,0.029222824784880516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2352941176470584,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,True
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c4,4,4,35,Floor level,floor_level,A_structural,log,count,0.034,0.016,,,**,,,high,"Log of floor level (1-9) ; printed without the '+' log marker in Table 4 (model described as log-log), transform assumed as in Table 3","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.40; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.635; SE type not stated",elasticity,0.034,0.016,b (log-log),reported,0.06211125816683293,0.029228827372627265,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.125,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c5,4,5,35,Floor level,floor_level,A_structural,log,count,0.03,0.016,,,*,,,high,"Log of floor level (1-9) ; printed without the '+' log marker in Table 4 (model described as log-log), transform assumed as in Table 3","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.50; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.643; SE type not stated",elasticity,0.03,0.016,b (log-log),reported,0.054827476552053105,0.029241320827761656,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.875,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c6,4,6,35,Floor level,floor_level,A_structural,log,count,0.02,0.015,,,,,,high,"Log of floor level (1-9) ; printed without the '+' log marker in Table 4 (model described as log-log), transform assumed as in Table 3","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.60; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.65; SE type not stated",elasticity,0.02,0.015,b (log-log),reported,0.03901742761214631,0.02926307070910973,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3333333333333335,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c7,4,7,35,Floor level,floor_level,A_structural,log,count,0.017,0.016,,,,,,high,"Log of floor level (1-9) ; printed without the '+' log marker in Table 4 (model described as log-log), transform assumed as in Table 3","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.70; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.654; SE type not stated",elasticity,0.017,0.016,b (log-log),reported,0.031100654312456486,0.029271204058782575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0625,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c8,4,8,35,Floor level,floor_level,A_structural,log,count,0.015,0.017,,,,,,high,"Log of floor level (1-9) ; printed without the '+' log marker in Table 4 (model described as log-log), transform assumed as in Table 3","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.80; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.658; SE type not stated",elasticity,0.015,0.017,b (log-log),reported,0.025831410439767433,0.0292755984984031,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8823529411764705,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442,0aed4606387835599541d79050eabb05449e0442:T4-c9,4,9,35,Floor level,floor_level,A_structural,log,count,0.029,0.022,,,,,,high,"Log of floor level (1-9) ; printed without the '+' log marker in Table 4 (model described as log-log), transform assumed as in Table 3","log(price), real transaction price (EUR, CPI-deflated)",log,quantile,1176.0,,se,"Quantile regression tau = 0.90; central subsample, dwellings on the market for more than one year (N = 1,176); urban-area and time dummies; pseudo-R2 = 0.661; SE type not stated",elasticity,0.029,0.022,b (log-log),reported,0.03857471129182722,0.029263574083455122,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3181818181818183,1166.0,count,,2023.0,Italy,Europe,High income,2017.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,,2017.5,quantile,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,EPC band A/B,energy_efficiency,A_structural,dummy,binary,0.022,,,,***,0.011,0.033,high,EPC band A/B vs reference D,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,2.2227685049915236,0.5737187840784229,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.009503243481468375,0.002424341335215437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9199279999999996,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,EPC band C,energy_efficiency,A_structural,dummy,binary,0.013,,,,***,0.011,0.015,high,EPC band C vs reference D,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,1.3084339911964449,0.10337790565130883,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.030872213492282596,0.0024232951760874257,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.739765999999998,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,EPC band E,energy_efficiency,A_structural,dummy,binary,-0.015,,,,***,-0.018,-0.013,high,EPC band E vs reference D,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,-1.488886177830162,0.12565434104951193,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),-0.028499436980117476,0.0024234660245560182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.759784000000002,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,EPC band F/G,energy_efficiency,A_structural,dummy,binary,-0.041,,,,***,-0.047,-0.035,high,EPC band F/G vs reference D,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,-4.017536753203766,0.29383064075089094,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),-0.032453777065937876,0.0024231737058240045,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.393087333333337,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Property type: Bungalow,dwelling_type,A_structural,dummy,binary,0.094,,,,***,0.09,0.097,high,Bungalow vs house,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,9.855799432401934,0.19617498641353165,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.12659398904027977,0.002404945180066592,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),52.639033142857095,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Property type: Bungalow,dwelling_type,A_structural,dummy,binary,0.094,,,,***,0.09,0.097,high,Bungalow vs house,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,9.855799432401934,0.19617498641353165,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.12659398904027977,0.002404945180066592,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),52.639033142857095,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Total floor area (log),living_area,A_structural,log,m2,0.496,,,,***,0.491,0.501,high,Natural log of total floor area in sqm (EPC record),natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",elasticity,0.496,0.0025510672645007787,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.4263848859514537,0.0021930171867513134,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),194.42842879999984,170127.0,m2,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Total floor area (log),living_area,A_structural,log,m2,0.496,,,,***,0.491,0.501,high,Natural log of total floor area in sqm (EPC record),natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,elasticity,0.496,0.0025510672645007787,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.4263848859514537,0.0021930171867513134,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),194.42842879999984,170127.0,m2,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Habitable rooms: 4,bedrooms,A_structural,dummy,count,0.014,,,,***,0.01,0.017,high,"Habitable rooms (all rooms, not bedrooms) 4 vs reference 1-3",natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,1.4096842014219346,0.1810923367105071,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.019003912725595616,0.0024240129825848352,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.839855999999999,170127.0,count,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Habitable rooms: 4,bedrooms,A_structural,dummy,count,0.013,,,,***,0.01,0.017,high,"Habitable rooms (all rooms, not bedrooms) 4 vs reference 1-3",natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,1.3083252051652172,0.18091133488979047,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.017646929361550153,0.0024240732822496717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.279866285714284,170127.0,count,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Habitable rooms: 5,bedrooms,A_structural,dummy,count,0.054,,,,***,0.051,0.058,high,Habitable rooms 5 vs 1-3,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,5.548291924287563,0.18848285517197172,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.07311780714416082,0.00241796131444972,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.239444571428546,170127.0,count,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Habitable rooms: 5,bedrooms,A_structural,dummy,count,0.054,,,,***,0.051,0.058,high,Habitable rooms 5 vs 1-3,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,5.548291924287563,0.18848285517197172,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.07311780714416082,0.00241796131444972,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.239444571428546,170127.0,count,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Habitable rooms: 6-7,bedrooms,A_structural,dummy,count,0.126,,,,***,0.121,0.13,high,Habitable rooms 6-7 vs 1-3,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,13.427917863972173,0.260426709739241,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.1318891425853828,0.0024032719585188977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),54.878991999999954,170127.0,count,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Habitable rooms: 6-7,bedrooms,A_structural,dummy,count,0.126,,,,***,0.121,0.13,high,Habitable rooms 6-7 vs 1-3,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,13.427917863972173,0.260426709739241,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.1318891425853828,0.0024032719585188977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),54.878991999999954,170127.0,count,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Habitable rooms: 8-10,bedrooms,A_structural,dummy,count,0.196,,,,***,0.189,0.203,high,Habitable rooms 8-10 vs 1-3,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,21.651914661163897,0.4344818750415937,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.1318891425853828,0.0024032719585188977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),54.878991999999954,170127.0,count,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Habitable rooms: 8-10,bedrooms,A_structural,dummy,count,0.196,,,,***,0.188,0.203,high,Habitable rooms 8-10 vs 1-3,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,21.65179986415677,0.4655162946874218,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.12323475610992542,0.0024059705522507754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),51.220392533333296,170127.0,count,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Built form: Detached,dwelling_type,A_structural,dummy,binary,0.174,,,,***,0.171,0.177,high,Detached vs semi-detached,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,19.00541717544426,0.1821547078140759,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.26570003745185977,0.002337305750758853,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),113.67791200000042,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Built form: Detached,dwelling_type,A_structural,dummy,binary,0.174,,,,***,0.171,0.177,high,Detached vs semi-detached,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,19.00541717544426,0.1821547078140759,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.26570003745185977,0.002337305750758853,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),113.67791200000042,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Built form: Terraced,dwelling_type,A_structural,dummy,binary,-0.172,,,,***,-0.175,-0.17,high,Terraced vs semi-detached,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,-15.80215117754048,0.10739727530307905,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),-0.31074165726505293,0.002304426946411607,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-134.8455232000006,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Built form: Terraced,dwelling_type,A_structural,dummy,binary,-0.172,,,,***,-0.175,-0.17,high,Terraced vs semi-detached,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,-15.80215117754048,0.10739727530307905,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),-0.31074165726505293,0.002304426946411607,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-134.8455232000006,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Building age: Before 1900,age,A_structural,dummy,years,0.001,,,,,-0.003,0.005,high,"Construction period band vs reference 1950-1966 (year built, not age)",natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,0.09984155431550512,0.2042895686179355,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.001187958241408321,0.002424449105000543,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.48999099999999995,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Building age: Before 1900,age,A_structural,dummy,years,0.002,,,,,-0.002,0.006,high,"Construction period band vs reference 1950-1966 (year built, not age)",natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,0.19999146247808852,0.20449396036539455,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.0023759114533329993,0.0024244439727801118,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9799819999999999,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Building age: 1900-1929,age,A_structural,dummy,years,-0.032,,,,***,-0.035,-0.028,high,Construction period band vs 1950-1966,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,-3.149496215133285,0.17295078058970434,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),-0.043404417033990256,0.002422165975034585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.91967085714285,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Building age: 1900-1929,age,A_structural,dummy,years,-0.031,,,,***,-0.034,-0.027,high,Construction period band vs 1950-1966,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,-3.052597269950741,0.17312381787451667,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),-0.042050466037150395,0.0024223063598407505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.359681142857138,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Building age: 1930-1949,age,A_structural,dummy,years,0.014,,,,***,0.011,0.017,high,Construction period band vs 1950-1966,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,1.4097270993877142,0.1552220028947204,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.022169785926138132,0.002423854934449759,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.146498666666664,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Building age: 1930-1949,age,A_structural,dummy,years,0.015,,,,***,0.012,0.018,high,Construction period band vs 1950-1966,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,1.5111875482564985,0.15537730253449328,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.023752478417320273,0.0024237668056474784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.799820000000002,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Building age: 1967-1982,age,A_structural,dummy,years,0.026,,,,***,0.023,0.029,high,Construction period band vs 1950-1966,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,2.6339746187616475,0.15709588775203662,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.04114770285531734,0.0024223974868524283,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.98635466666666,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Building age: 1967-1982,age,A_structural,dummy,years,0.025,,,,***,0.022,0.029,high,Construction period band vs 1950-1966,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,2.5313485715805273,0.1830953487837278,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.03392215380644527,0.0024230554912755228,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.999742857142852,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Building age: 1983-2002,age,A_structural,dummy,years,0.099,,,,***,0.095,0.103,high,Construction period band vs 1950-1966,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,10.406400029668173,0.22532379157145357,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.11680293551577783,0.0024078557187223897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),48.50910900000004,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Building age: 1983-2002,age,A_structural,dummy,years,0.098,,,,***,0.094,0.102,high,Construction period band vs 1950-1966,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,10.296048814442038,0.22509858040423333,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.11563896438411791,0.002408185930947707,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),48.01911800000004,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Building age: 2003-2011,age,A_structural,dummy,years,0.132,,,,***,0.127,0.137,high,Construction period band vs 1950-1966,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,14.110460613864916,0.2911044078532147,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.12447286747990127,0.002405595890503937,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),51.74304959999996,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Building age: 2003-2011,age,A_structural,dummy,years,0.128,,,,***,0.123,0.133,high,Construction period band vs 1950-1966,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,13.654930439132329,0.2899423159550536,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.12075681160372963,0.002406708976935644,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),50.17507839999996,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Building age: 2012-2024,age,A_structural,dummy,years,0.139,,,,***,0.115,0.162,high,Construction period band vs 1950-1966,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,14.904150365197877,1.3778016509530135,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.028095511036642273,0.002423493747334477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.592978553191491,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Building age: 2012-2024,age,A_structural,dummy,years,0.132,,,,***,0.109,0.156,high,Construction period band vs 1950-1966,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,14.102629907117304,1.3681907169101077,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.026681663143925383,0.0024235876653170684,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.009159489361704,170127.0,years,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Modern kitchen,kitchen_quality,B_interior,dummy,binary,0.043,,,,***,0.041,0.045,high,Keyword from listing text,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,4.393735133958954,0.10652623158900998,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.10163544363916299,0.002411896308659369,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.13922600000003,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Modern kitchen,kitchen_quality,B_interior,dummy,binary,0.043,,,,***,0.041,0.045,high,Keyword from listing text,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,4.393735133958954,0.10652623158900998,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.10163544363916299,0.002411896308659369,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.13922600000003,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Garage,garage,A_structural,dummy,binary,0.057,,,,***,0.055,0.06,high,Keyword from listing text,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,5.865494918673431,0.135035109113675,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.10771155533099691,0.00241034581415237,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),44.687179200000024,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Garage,garage,A_structural,dummy,binary,0.058,,,,***,0.055,0.06,high,Keyword from listing text,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,5.971413363988232,0.1351702117628547,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.10957873474954925,0.0024098510612499016,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),45.471164800000025,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Basement,basement,A_structural,dummy,binary,0.051,,,,***,0.043,0.059,high,Keyword from listing text,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,5.231412729263374,0.42952743755832407,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.030279066724253845,0.002423339166113843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.494770499999998,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Basement,basement,A_structural,dummy,binary,0.052,,,,***,0.044,0.06,high,Keyword from listing text,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,5.336696775241956,0.429957179831207,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.030872213492282596,0.0024232951760874257,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.739765999999998,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Garden,garden,C_exterior,dummy,binary,0.073,,,,***,0.07,0.076,high,Keyword from listing text,natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",pct_premium,7.5729276772468435,0.16465565748881641,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.1148627185837631,0.0024084042845802954,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.6924573333334,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Garden,garden,C_exterior,dummy,binary,0.073,,,,***,0.07,0.075,high,Keyword from listing text,natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,pct_premium,7.572966181577256,0.13721304790734695,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.13743692097416377,0.0024014440413080047,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),57.23094880000011,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M1,3,Model 1: EPC bands,10,Population density (natural log),density,F_neighbourhood,log,per_km2,-0.006,,,,,-0.023,0.01,high,Log of 100s of residents per km2 (LSOA),natural log of listing price (GBP),log,other,170137.0,0.896,none,"Full sample 2017-09 to 2024-05; two-level random-intercept model (LSOA); 95% CIs in brackets, no SE; year-quarter dummies",elasticity,-0.006,0.008418521972852562,b (log-log),(ci_hi-ci_lo)/(2*1.96),-0.0017279378998863915,0.0024244471963197167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7127141818181818,170127.0,per_km2,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T3-M2,3,Model 2: EPC score,10,Population density (natural log),density,F_neighbourhood,log,per_km2,-0.006,,,,,-0.023,0.01,high,Log of 100s of residents per km2 (LSOA),natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; continuous EPC score instead of bands,elasticity,-0.006,0.008418521972852562,b (log-log),(ci_hi-ci_lo)/(2*1.96),-0.0017279378998863915,0.0024244471963197167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7127141818181818,170127.0,per_km2,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T4-M3,4,Model 3: Interaction with EPC bands,10,EPC A/B,energy_efficiency,A_structural,dummy,binary,0.02,,,,*,0.006,0.034,high,"EPC A/B vs D, pre-2022 baseline (interaction model)",natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; EPC bands interacted with post-2022 energy-crisis dummy; only variables of interest reported,pct_premium,2.0175313858280752,0.7287286276877831,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.006788181194975373,0.0024243949564802013,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7999485714285712,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T4-M3,4,Model 3: Interaction with EPC bands,10,EPC C,energy_efficiency,A_structural,dummy,binary,0.012,,,,***,0.009,0.015,high,"EPC C vs D, pre-2022 baseline",natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; EPC bands interacted with post-2022 energy-crisis dummy; only variables of interest reported,pct_premium,1.2071103294977625,0.1549118691260775,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.019003912725595616,0.0024240129825848352,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.839855999999999,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T4-M3,4,Model 3: Interaction with EPC bands,10,EPC E,energy_efficiency,A_structural,dummy,binary,-0.013,,,,***,-0.016,-0.01,high,"EPC E vs D, pre-2022 baseline",natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; EPC bands interacted with post-2022 energy-crisis dummy; only variables of interest reported,pct_premium,-1.2917021278957885,0.15108708144949923,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),-0.020586926735257537,0.002423936994045755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.493177333333332,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T4-M3,4,Model 3: Interaction with EPC bands,10,EPC F/G,energy_efficiency,A_structural,dummy,binary,-0.036,,,,***,-0.043,-0.03,high,"EPC F/G vs D, pre-2022 baseline",natural log of listing price (GBP),log,other,170137.0,0.896,none,Full sample; EPC bands interacted with post-2022 energy-crisis dummy; only variables of interest reported,pct_premium,-3.5365011264577806,0.3199120957140182,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),-0.02630875315045954,0.002423611628098881,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.855185230769232,170127.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T5-matched-bands,5,Matched listings,11,EPC band A/B,energy_efficiency,A_structural,dummy,binary,0.018,,,,*,0.001,0.035,high,Robustness model; reference band D; only EPC variables reported,natural log of listing price (GBP),log,other,64292.0,,none,"Listings matched to Land Registry transactions, 2017-09 to 2023-10; EPC bands model; only EPC rows reported",pct_premium,1.8124677975686954,0.8831167612581912,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.008184882331912786,0.003944035016360771,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0752559999999995,64282.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T5-matched-bands,5,Matched listings,11,EPC band C,energy_efficiency,A_structural,dummy,binary,0.012,,,,***,0.009,0.015,high,Robustness model; reference band D; only EPC variables reported,natural log of listing price (GBP),log,other,64292.0,,none,"Listings matched to Land Registry transactions, 2017-09 to 2023-10; EPC bands model; only EPC rows reported",pct_premium,1.2071103294977625,0.1549118691260775,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.030906930036345353,0.0039422828730968215,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.839855999999999,64282.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T5-matched-bands,5,Matched listings,11,EPC band E,energy_efficiency,A_structural,dummy,binary,-0.014,,,,***,-0.018,-0.011,high,Robustness model; reference band D; only EPC variables reported,natural log of listing price (GBP),log,other,64292.0,,none,"Listings matched to Land Registry transactions, 2017-09 to 2023-10; EPC bands model; only EPC rows reported",pct_premium,-1.3904028015491177,0.17609208153415146,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),-0.03090693003634536,0.0039422828730968215,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.839856000000001,64282.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T5-matched-bands,5,Matched listings,11,EPC band F/G,energy_efficiency,A_structural,dummy,binary,-0.045,,,,***,-0.053,-0.037,high,Robustness model; reference band D; only EPC variables reported,natural log of listing price (GBP),log,other,64292.0,,none,"Listings matched to Land Registry transactions, 2017-09 to 2023-10; EPC bands model; only EPC rows reported",pct_premium,-4.401048175389821,0.3902102209359356,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),-0.04344259212423912,0.003940443543225091,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.024797499999998,64282.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T5-all-bands,5,All listings,11,EPC band A/B,energy_efficiency,A_structural,dummy,binary,0.019,,,,**,0.007,0.031,high,Robustness model; reference band D; only EPC variables reported,natural log of listing price (GBP),log,other,149526.0,,none,All listings 2017-09 to 2023-10; EPC bands model; only EPC rows reported,pct_premium,1.9162546397838431,0.6240002256882727,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.008025324989907988,0.00258608133078749,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.103276333333333,149516.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T5-all-bands,5,All listings,11,EPC band C,energy_efficiency,A_structural,dummy,binary,0.012,,,,***,0.01,0.014,high,Robustness model; reference band D; only EPC variables reported,natural log of listing price (GBP),log,other,149526.0,,none,All listings 2017-09 to 2023-10; EPC bands model; only EPC rows reported,pct_premium,1.207176194541737,0.10327457941738499,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),0.030398682104257495,0.0025849694266712295,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.759784,149516.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T5-all-bands,5,All listings,11,EPC band E,energy_efficiency,A_structural,dummy,binary,-0.016,,,,***,-0.018,-0.013,high,Robustness model; reference band D; only EPC variables reported,natural log of listing price (GBP),log,other,149526.0,,none,All listings 2017-09 to 2023-10; EPC bands model; only EPC rows reported,pct_premium,-1.5873480525098405,0.1255287495146958,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),-0.032423196953931345,0.0025848048862386103,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.543769600000003,149516.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89,0ce3fe88a1c7202d8a2a9d78f61d5b7af8475b89:T5-all-bands,5,All listings,11,EPC band F/G,energy_efficiency,A_structural,dummy,binary,-0.04,,,,***,-0.046,-0.035,high,Robustness model; reference band D; only EPC variables reported,natural log of listing price (GBP),log,other,149526.0,,none,All listings 2017-09 to 2023-10; EPC bands model; only EPC rows reported,pct_premium,-3.9214343762477677,0.26961423349295066,100*(exp(b - se^2/2) - 1),(ci_hi-ci_lo)/(2*1.96),-0.03683890134708433,0.0025844091703848093,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.254283636363644,149516.0,binary,,2026.0,United Kingdom,Europe,High income,2017.0,2024.0,single_family,listing,journal,True,False,unknown,,2020.5,other,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c1,4,1,8,Area,living_area,A_structural,level,100 m2,0.443,0.004,,,***,,,high,Ground floor area in units of 100 m2 (sample mean 1.041 = 104 m2),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.846,se,Baseline hedonic model without geomantic attributes; district + quarter FE,semi_elasticity,0.44299999999999995,0.004,100*b/100 (X per 100m2->m2),reported,0.8465660229731788,0.00764393700201516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),110.75,4849.0,100m2,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c1,4,1,8,Subway,transit_distance,D_location,dummy,binary,0.027,0.004,,,***,,,high,Dummy = 1 if subway station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.846,se,Baseline hedonic model without geomantic attributes; district + quarter FE,pct_premium,2.735958385394288,0.4109471211053958,100*(exp(b - se^2/2) - 1),reported,0.09648211909650203,0.014293647273555856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.75,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c1,4,1,8,Bus,transit_distance,D_location,dummy,binary,0.024,0.004,,,***,,,high,Dummy = 1 if bus station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.846,se,Baseline hedonic model without geomantic attributes; district + quarter FE,pct_premium,2.4282123600855687,0.4097161271562486,100*(exp(b - se^2/2) - 1),reported,0.08584578303380906,0.014307630505634843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c1,4,1,8,Log_Park,green_space,E_environment,log,m,-0.023,0.005,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest park in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.846,se,Baseline hedonic model without geomantic attributes; district + quarter FE,elasticity,-0.023,0.005,b (log-log),reported,-0.0659152975669559,0.01432941251455563,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.6,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c1,4,1,8,Log_CBD,cbd_distance,D_location,log,m,-0.027,0.004,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest CBD in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.846,se,Baseline hedonic model without geomantic attributes; district + quarter FE,elasticity,-0.027,0.004,b (log-log),reported,-0.09648211909650203,0.014293647273555856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.75,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c2,4,2,8,Hospital,hospital_distance,D_location,dummy,binary,-0.024,0.007,,,***,,,high,"Dummy = 1 if near a hospital (unfavorable geomantic attribute); proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.847,se,Stepwise: adds unfavorable geomantic attributes and unlucky numbers,pct_premium,-2.373820894897438,0.6833999968305365,100*(exp(b - se^2/2) - 1),reported,-0.049176920724083,0.01434326854452421,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.4285714285714284,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c2,4,2,8,Slaughterhouse,hazard_site,E_environment,dummy,binary,-0.143,0.034,,,***,,,high,Dummy = 1 if near a slaughterhouse (unfavorable geomantic attribute); printed name 'Slaughterhouse',"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.847,se,Stepwise: adds unfavorable geomantic attributes and unlucky numbers,pct_premium,-13.374677019989056,2.9469638342446625,100*(exp(b - se^2/2) - 1),reported,-0.06028930861245698,0.01433452092883593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.205882352941176,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c2,4,2,8,Highway,highway_distance,D_location,dummy,binary,-0.015,0.007,,,**,,,high,"Dummy = 1 if near a highway; proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.847,se,Stepwise: adds unfavorable geomantic attributes and unlucky numbers,pct_premium,-1.491219534380328,0.6895783577221438,100*(exp(b - se^2/2) - 1),reported,-0.030758247930394986,0.014353849034184327,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.142857142857143,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c2,4,2,8,Area,living_area,A_structural,level,100 m2,0.442,0.004,,,***,,,high,Ground floor area in units of 100 m2 (sample mean 1.041 = 104 m2),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.847,se,Stepwise: adds unfavorable geomantic attributes and unlucky numbers,semi_elasticity,0.442,0.004,100*b/100 (X per 100m2->m2),reported,0.8460232750802543,0.007656319231495512,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),110.5,4849.0,100m2,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c2,4,2,8,Subway,transit_distance,D_location,dummy,binary,0.026,0.004,,,***,,,high,Dummy = 1 if subway station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.847,se,Stepwise: adds unfavorable geomantic attributes and unlucky numbers,pct_premium,2.6332737778697046,0.4105363793893768,100*(exp(b - se^2/2) - 1),reported,0.09294016222362012,0.014298486495941556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.5,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c2,4,2,8,Bus,transit_distance,D_location,dummy,binary,0.022,0.004,,,***,,,high,Dummy = 1 if bus station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.847,se,Stepwise: adds unfavorable geomantic attributes and unlucky numbers,pct_premium,2.2235606552874154,0.4088975137881753,100*(exp(b - se^2/2) - 1),reported,0.07873832178890346,0.014316058507073357,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.5,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c2,4,2,8,Log_Park,green_space,E_environment,log,m,-0.026,0.005,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest park in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.847,se,Stepwise: adds unfavorable geomantic attributes and unlucky numbers,elasticity,-0.026,0.005,b (log-log),reported,-0.07446800406992858,0.014320770013447804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.199999999999999,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c2,4,2,8,Log_CBD,cbd_distance,D_location,log,m,-0.025,0.004,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest CBD in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.847,se,Stepwise: adds unfavorable geomantic attributes and unlucky numbers,elasticity,-0.025,0.004,b (log-log),reported,-0.08939467343475828,0.014303147749561325,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.25,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c3,4,3,8,Hospital,hospital_distance,D_location,dummy,binary,-0.021,0.007,,,***,,,high,"Dummy = 1 if near a hospital (unfavorable geomantic attribute); proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.848,se,Stepwise: adds favorable geomantic attributes,pct_premium,-2.080502600128664,0.6854532751986218,100*(exp(b - se^2/2) - 1),reported,-0.04304200558228067,0.014347335194093556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c3,4,3,8,Slaughterhouse,hazard_site,E_environment,dummy,binary,-0.139,0.031,,,***,,,high,Dummy = 1 if near a slaughterhouse (unfavorable geomantic attribute); printed name 'Slaughterhouse',"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.848,se,Stepwise: adds favorable geomantic attributes,pct_premium,-13.019001566627853,2.69770688822058,100*(exp(b - se^2/2) - 1),reported,-0.0642581964599424,0.014330964678116648,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.483870967741936,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c3,4,3,8,Highway,highway_distance,D_location,dummy,binary,-0.017,0.007,,,**,,,high,"Dummy = 1 if near a highway; proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.848,se,Stepwise: adds favorable geomantic attributes,pct_premium,-1.6880402090300284,0.6882005792444368,100*(exp(b - se^2/2) - 1),reported,-0.03485465820066124,0.014351918082625216,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.428571428571429,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c3,4,3,8,Pearl River,water_proximity,E_environment,dummy,binary,0.025,0.004,,,***,,,high,Dummy = 1 if located near the Pearl River (favorable geomantic attribute),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.848,se,Stepwise: adds favorable geomantic attributes,pct_premium,2.5306918036274606,0.41012604820977155,100*(exp(b - se^2/2) - 1),reported,0.08939467343475828,0.014303147749561325,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.25,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c3,4,3,8,Orientation,sunlight,E_environment,dummy,binary,0.001,0.003,,,,,,high,Dummy = 1 if south-facing,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.848,se,Stepwise: adds favorable geomantic attributes,pct_premium,0.09959956745926313,0.30030015005001254,100*(exp(b - se^2/2) - 1),reported,0.004786826399559017,0.014360479198677053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3333333333333333,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c3,4,3,8,Area,living_area,A_structural,level,100 m2,0.44,0.005,,,***,,,high,Ground floor area in units of 100 m2 (sample mean 1.041 = 104 m2),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.848,se,Stepwise: adds favorable geomantic attributes,semi_elasticity,0.44,0.005,100*b/100 (X per 100m2->m2),reported,0.7841841688079839,0.008911183736454362,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),88.0,4849.0,100m2,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c3,4,3,8,Subway,transit_distance,D_location,dummy,binary,0.023,0.004,,,***,,,high,Dummy = 1 if subway station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.848,se,Stepwise: adds favorable geomantic attributes,pct_premium,2.3258353447645597,0.40930661581888705,100*(exp(b - se^2/2) - 1),reported,0.08229362196487157,0.014311934254760272,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.75,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c3,4,3,8,Bus,transit_distance,D_location,dummy,binary,0.021,0.004,,,***,,,high,Dummy = 1 if bus station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.848,se,Stepwise: adds favorable geomantic attributes,pct_premium,2.1213881893794584,0.4084888206550114,100*(exp(b - se^2/2) - 1),reported,0.0751800146601043,0.014320002792400817,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.25,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c3,4,3,8,Log_Park,green_space,E_environment,log,m,-0.027,0.005,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest park in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.848,se,Stepwise: adds favorable geomantic attributes,elasticity,-0.027,0.005,b (log-log),reported,-0.0773153523516994,0.014317657842907295,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.3999999999999995,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c3,4,3,8,Log_CBD,cbd_distance,D_location,log,m,-0.024,0.004,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest CBD in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.848,se,Stepwise: adds favorable geomantic attributes,elasticity,-0.024,0.004,b (log-log),reported,-0.08584578303380906,0.014307630505634843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c4,4,4,8,Hospital,hospital_distance,D_location,dummy,binary,-0.021,0.007,,,***,,,high,"Dummy = 1 if near a hospital (unfavorable geomantic attribute); proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,Stepwise: adds lucky numbers,pct_premium,-2.080502600128664,0.6854532751986218,100*(exp(b - se^2/2) - 1),reported,-0.04304200558228067,0.014347335194093556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c4,4,4,8,Slaughterhouse,hazard_site,E_environment,dummy,binary,-0.137,0.031,,,***,,,high,Dummy = 1 if near a slaughterhouse (unfavorable geomantic attribute); printed name 'Slaughterhouse',"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,Stepwise: adds lucky numbers,pct_premium,-12.84486549173156,2.703107701009539,100*(exp(b - se^2/2) - 1),reported,-0.06333735411429134,0.014331810055058621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.419354838709678,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c4,4,4,8,Highway,highway_distance,D_location,dummy,binary,-0.018,0.007,,,**,,,high,"Dummy = 1 if near a highway; proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,Stepwise: adds lucky numbers,pct_premium,-1.7863030292223359,0.6875127226508105,100*(exp(b - se^2/2) - 1),reported,-0.036902217659278196,0.014350862423052632,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.571428571428571,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c4,4,4,8,Pearl River,water_proximity,E_environment,dummy,binary,0.026,0.004,,,***,,,high,Dummy = 1 if located near the Pearl River (favorable geomantic attribute),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,Stepwise: adds lucky numbers,pct_premium,2.6332737778697046,0.4105363793893768,100*(exp(b - se^2/2) - 1),reported,0.09294016222362012,0.014298486495941556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.5,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c4,4,4,8,Orientation,sunlight,E_environment,dummy,binary,0.001,0.003,,,,,,high,Dummy = 1 if south-facing,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,Stepwise: adds lucky numbers,pct_premium,0.09959956745926313,0.30030015005001254,100*(exp(b - se^2/2) - 1),reported,0.004786826399559017,0.014360479198677053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3333333333333333,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c4,4,4,8,Area,living_area,A_structural,level,100 m2,0.44,0.005,,,***,,,high,Ground floor area in units of 100 m2 (sample mean 1.041 = 104 m2),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,Stepwise: adds lucky numbers,semi_elasticity,0.44,0.005,100*b/100 (X per 100m2->m2),reported,0.7841841688079839,0.008911183736454362,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),88.0,4849.0,100m2,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c4,4,4,8,Subway,transit_distance,D_location,dummy,binary,0.023,0.004,,,***,,,high,Dummy = 1 if subway station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,Stepwise: adds lucky numbers,pct_premium,2.3258353447645597,0.40930661581888705,100*(exp(b - se^2/2) - 1),reported,0.08229362196487157,0.014311934254760272,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.75,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c4,4,4,8,Bus,transit_distance,D_location,dummy,binary,0.021,0.004,,,***,,,high,Dummy = 1 if bus station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,Stepwise: adds lucky numbers,pct_premium,2.1213881893794584,0.4084888206550114,100*(exp(b - se^2/2) - 1),reported,0.0751800146601043,0.014320002792400817,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.25,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c4,4,4,8,Log_Park,green_space,E_environment,log,m,-0.027,0.005,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest park in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,Stepwise: adds lucky numbers,elasticity,-0.027,0.005,b (log-log),reported,-0.0773153523516994,0.014317657842907295,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.3999999999999995,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c4,4,4,8,Log_CBD,cbd_distance,D_location,log,m,-0.025,0.004,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest CBD in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,Stepwise: adds lucky numbers,elasticity,-0.025,0.004,b (log-log),reported,-0.08939467343475828,0.014303147749561325,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.25,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c5,4,5,8,Hospital,hospital_distance,D_location,dummy,binary,-0.021,0.007,,,***,,,high,"Dummy = 1 if near a hospital (unfavorable geomantic attribute); proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Full model incl. buyer demographic characteristics,pct_premium,-2.080502600128664,0.6854532751986218,100*(exp(b - se^2/2) - 1),reported,-0.04304200558228067,0.014347335194093556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c5,4,5,8,Slaughterhouse,hazard_site,E_environment,dummy,binary,-0.134,0.033,,,***,,,high,Dummy = 1 if near a slaughterhouse (unfavorable geomantic attribute); printed name 'Slaughterhouse',"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Full model incl. buyer demographic characteristics,pct_premium,-12.588602006103011,2.8861472131910024,100*(exp(b - se^2/2) - 1),reported,-0.0582140255717507,0.014336289879610248,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0606060606060606,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c5,4,5,8,Highway,highway_distance,D_location,dummy,binary,-0.018,0.007,,,**,,,high,"Dummy = 1 if near a highway; proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Full model incl. buyer demographic characteristics,pct_premium,-1.7863030292223359,0.6875127226508105,100*(exp(b - se^2/2) - 1),reported,-0.036902217659278196,0.014350862423052632,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.571428571428571,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c5,4,5,8,Pearl River,water_proximity,E_environment,dummy,binary,0.027,0.004,,,***,,,high,Dummy = 1 if located near the Pearl River (favorable geomantic attribute),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Full model incl. buyer demographic characteristics,pct_premium,2.735958385394288,0.4109471211053958,100*(exp(b - se^2/2) - 1),reported,0.09648211909650203,0.014293647273555856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.75,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c5,4,5,8,Orientation,sunlight,E_environment,dummy,binary,-0.001,0.003,,,,,,high,Dummy = 1 if south-facing,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Full model incl. buyer demographic characteristics,pct_premium,-0.10039956587594157,0.2997001499500125,100*(exp(b - se^2/2) - 1),reported,-0.004786826399559017,0.014360479198677053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3333333333333333,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c5,4,5,8,Area,living_area,A_structural,level,100 m2,0.436,0.005,,,***,,,high,Ground floor area in units of 100 m2 (sample mean 1.041 = 104 m2),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Full model incl. buyer demographic characteristics,semi_elasticity,0.436,0.005,100*b/100 (X per 100m2->m2),reported,0.781415966596542,0.00896119227748328,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),87.2,4849.0,100m2,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c5,4,5,8,Subway,transit_distance,D_location,dummy,binary,0.024,0.004,,,***,,,high,Dummy = 1 if subway station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Full model incl. buyer demographic characteristics,pct_premium,2.4282123600855687,0.4097161271562486,100*(exp(b - se^2/2) - 1),reported,0.08584578303380906,0.014307630505634843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c5,4,5,8,Bus,transit_distance,D_location,dummy,binary,0.019,0.004,,,***,,,high,Dummy = 1 if bus station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Full model incl. buyer demographic characteristics,pct_premium,1.9173495196832757,0.40767265944696324,100*(exp(b - se^2/2) - 1),reported,0.06805491098351593,0.014327349680740195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.75,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c5,4,5,8,Log_Park,green_space,E_environment,log,m,-0.028,0.005,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest park in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Full model incl. buyer demographic characteristics,elasticity,-0.028,0.005,b (log-log),reported,-0.08016081010727731,0.014314430376299519,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.6,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T4-c5,4,5,8,Log_CBD,cbd_distance,D_location,log,m,-0.024,0.004,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest CBD in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Full model incl. buyer demographic characteristics,elasticity,-0.024,0.004,b (log-log),reported,-0.08584578303380906,0.014307630505634843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c2,5,2,10,Pearl River,water_proximity,E_environment,dummy,binary,0.028,0.004,,,***,,,high,Dummy = 1 if located near the Pearl River (favorable geomantic attribute),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_1 (count of 4 unfavorable attributes) replaces individual unfavorable dummies; incl. demographics,pct_premium,2.8387457288858275,0.41135827376857004,100*(exp(b - se^2/2) - 1),reported,0.10002041441278796,0.014288630630398279,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c2,5,2,10,Orientation,sunlight,E_environment,dummy,binary,-0.001,0.003,,,,,,high,Dummy = 1 if south-facing,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_1 (count of 4 unfavorable attributes) replaces individual unfavorable dummies; incl. demographics,pct_premium,-0.10039956587594157,0.2997001499500125,100*(exp(b - se^2/2) - 1),reported,-0.004786826399559017,0.014360479198677053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3333333333333333,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c2,5,2,10,Area,living_area,A_structural,level,100 m2,0.436,0.005,,,***,,,high,Ground floor area in units of 100 m2 (sample mean 1.041 = 104 m2),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_1 (count of 4 unfavorable attributes) replaces individual unfavorable dummies; incl. demographics,semi_elasticity,0.436,0.005,100*b/100 (X per 100m2->m2),reported,0.781415966596542,0.00896119227748328,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),87.2,4849.0,100m2,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c2,5,2,10,Bus,transit_distance,D_location,dummy,binary,0.02,0.004,,,***,,,high,Dummy = 1 if bus station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_1 (count of 4 unfavorable attributes) replaces individual unfavorable dummies; incl. demographics,pct_premium,2.019317844868196,0.4080805360107023,100*(exp(b - se^2/2) - 1),reported,0.07161883330203965,0.01432376666040793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c2,5,2,10,Subway,transit_distance,D_location,dummy,binary,0.022,0.004,,,***,,,high,Dummy = 1 if subway station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_1 (count of 4 unfavorable attributes) replaces individual unfavorable dummies; incl. demographics,pct_premium,2.2235606552874154,0.4088975137881753,100*(exp(b - se^2/2) - 1),reported,0.07873832178890346,0.014316058507073357,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.5,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c2,5,2,10,Log_Park,green_space,E_environment,log,m,-0.027,0.005,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest park in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_1 (count of 4 unfavorable attributes) replaces individual unfavorable dummies; incl. demographics,elasticity,-0.027,0.005,b (log-log),reported,-0.0773153523516994,0.014317657842907295,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.3999999999999995,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c2,5,2,10,Log_CBD,cbd_distance,D_location,log,m,-0.024,0.004,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest CBD in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_1 (count of 4 unfavorable attributes) replaces individual unfavorable dummies; incl. demographics,elasticity,-0.024,0.004,b (log-log),reported,-0.08584578303380906,0.014307630505634843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c3,5,3,10,Pearl River,water_proximity,E_environment,dummy,binary,0.028,0.004,,,***,,,high,Dummy = 1 if located near the Pearl River (favorable geomantic attribute),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_2 (count of 5 unfavorable attributes incl. slaughterhouse); incl. demographics,pct_premium,2.8387457288858275,0.41135827376857004,100*(exp(b - se^2/2) - 1),reported,0.10002041441278796,0.014288630630398279,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c3,5,3,10,Orientation,sunlight,E_environment,dummy,binary,-0.001,0.003,,,,,,high,Dummy = 1 if south-facing,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_2 (count of 5 unfavorable attributes incl. slaughterhouse); incl. demographics,pct_premium,-0.10039956587594157,0.2997001499500125,100*(exp(b - se^2/2) - 1),reported,-0.004786826399559017,0.014360479198677053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3333333333333333,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c3,5,3,10,Area,living_area,A_structural,level,100 m2,0.436,0.005,,,***,,,high,Ground floor area in units of 100 m2 (sample mean 1.041 = 104 m2),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_2 (count of 5 unfavorable attributes incl. slaughterhouse); incl. demographics,semi_elasticity,0.436,0.005,100*b/100 (X per 100m2->m2),reported,0.781415966596542,0.00896119227748328,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),87.2,4849.0,100m2,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c3,5,3,10,Bus,transit_distance,D_location,dummy,binary,0.02,0.004,,,***,,,high,Dummy = 1 if bus station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_2 (count of 5 unfavorable attributes incl. slaughterhouse); incl. demographics,pct_premium,2.019317844868196,0.4080805360107023,100*(exp(b - se^2/2) - 1),reported,0.07161883330203965,0.01432376666040793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c3,5,3,10,Subway,transit_distance,D_location,dummy,binary,0.022,0.004,,,***,,,high,Dummy = 1 if subway station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_2 (count of 5 unfavorable attributes incl. slaughterhouse); incl. demographics,pct_premium,2.2235606552874154,0.4088975137881753,100*(exp(b - se^2/2) - 1),reported,0.07873832178890346,0.014316058507073357,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.5,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c3,5,3,10,Log_Park,green_space,E_environment,log,m,-0.027,0.005,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest park in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_2 (count of 5 unfavorable attributes incl. slaughterhouse); incl. demographics,elasticity,-0.027,0.005,b (log-log),reported,-0.0773153523516994,0.014317657842907295,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.3999999999999995,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T5-c3,5,3,10,Log_CBD,cbd_distance,D_location,log,m,-0.024,0.004,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest CBD in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.85,se,Group variable BFS_2 (count of 5 unfavorable attributes incl. slaughterhouse); incl. demographics,elasticity,-0.024,0.004,b (log-log),reported,-0.08584578303380906,0.014307630505634843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c1,6,1,11,Hospital,hospital_distance,D_location,dummy,binary,-0.021,0.007,,,***,,,high,"Dummy = 1 if near a hospital (unfavorable geomantic attribute); proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,"Whole sample; demographics (Guangdong, gender, age) included, improvement-demand dummy excluded",pct_premium,-2.080502600128664,0.6854532751986218,100*(exp(b - se^2/2) - 1),reported,-0.04304200558228067,0.014347335194093556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c1,6,1,11,Slaughterhouse,hazard_site,E_environment,dummy,binary,-0.136,0.032,,,***,,,high,Dummy = 1 if near a slaughterhouse (unfavorable geomantic attribute); printed name 'Slaughterhouse',"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,"Whole sample; demographics (Guangdong, gender, age) included, improvement-demand dummy excluded",pct_premium,-12.760414855340807,2.7930964239639016,100*(exp(b - se^2/2) - 1),reported,-0.06091937912010326,0.014333971557671356,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.25,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c1,6,1,11,Highway,highway_distance,D_location,dummy,binary,-0.018,0.007,,,**,,,high,"Dummy = 1 if near a highway; proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,"Whole sample; demographics (Guangdong, gender, age) included, improvement-demand dummy excluded",pct_premium,-1.7863030292223359,0.6875127226508105,100*(exp(b - se^2/2) - 1),reported,-0.036902217659278196,0.014350862423052632,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.571428571428571,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c1,6,1,11,Pearl River,water_proximity,E_environment,dummy,binary,0.027,0.004,,,***,,,high,Dummy = 1 if located near the Pearl River (favorable geomantic attribute),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,"Whole sample; demographics (Guangdong, gender, age) included, improvement-demand dummy excluded",pct_premium,2.735958385394288,0.4109471211053958,100*(exp(b - se^2/2) - 1),reported,0.09648211909650203,0.014293647273555856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.75,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c1,6,1,11,Orientation,sunlight,E_environment,dummy,binary,-0.001,0.003,,,,,,high,Dummy = 1 if south-facing,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,"Whole sample; demographics (Guangdong, gender, age) included, improvement-demand dummy excluded",pct_premium,-0.10039956587594157,0.2997001499500125,100*(exp(b - se^2/2) - 1),reported,-0.004786826399559017,0.014360479198677053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3333333333333333,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c1,6,1,12,Area,living_area,A_structural,level,100 m2,0.441,0.005,,,***,,,high,Ground floor area in units of 100 m2 (sample mean 1.041 = 104 m2),"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,"Whole sample; demographics (Guangdong, gender, age) included, improvement-demand dummy excluded",semi_elasticity,0.441,0.005,100*b/100 (X per 100m2->m2),reported,0.7848689918986934,0.008898741404747092,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),88.2,4849.0,100m2,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c1,6,1,12,Subway,transit_distance,D_location,dummy,binary,0.023,0.004,,,***,,,high,Dummy = 1 if subway station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,"Whole sample; demographics (Guangdong, gender, age) included, improvement-demand dummy excluded",pct_premium,2.3258353447645597,0.40930661581888705,100*(exp(b - se^2/2) - 1),reported,0.08229362196487157,0.014311934254760272,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.75,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c1,6,1,12,Bus,transit_distance,D_location,dummy,binary,0.02,0.004,,,***,,,high,Dummy = 1 if bus station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,"Whole sample; demographics (Guangdong, gender, age) included, improvement-demand dummy excluded",pct_premium,2.019317844868196,0.4080805360107023,100*(exp(b - se^2/2) - 1),reported,0.07161883330203965,0.01432376666040793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,4849.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c1,6,1,12,Log_Park,green_space,E_environment,log,m,-0.028,0.005,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest park in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,"Whole sample; demographics (Guangdong, gender, age) included, improvement-demand dummy excluded",elasticity,-0.028,0.005,b (log-log),reported,-0.08016081010727731,0.014314430376299519,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.6,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c1,6,1,12,Log_CBD,cbd_distance,D_location,log,m,-0.025,0.004,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest CBD in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,4859.0,0.849,se,"Whole sample; demographics (Guangdong, gender, age) included, improvement-demand dummy excluded",elasticity,-0.025,0.004,b (log-log),reported,-0.08939467343475828,0.014303147749561325,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.25,4849.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c2,6,2,11,Hospital,hospital_distance,D_location,dummy,binary,-0.01,0.011,,,,,,high,"Dummy = 1 if near a hospital (unfavorable geomantic attribute); proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,2789.0,0.827,se,First-time demand buyers subsample,pct_premium,-1.0010062453895352,1.0890548171240848,100*(exp(b - se^2/2) - 1),reported,-0.01724243008498071,0.01896667309347878,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9090909090909092,2779.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c2,6,2,11,Slaughterhouse,hazard_site,E_environment,dummy,binary,-0.122,0.039,,,***,,,high,Dummy = 1 if near a slaughterhouse (unfavorable geomantic attribute); printed name 'Slaughterhouse',"Log_Price (log10 of transaction price, RMB)",log,OLS,2789.0,0.827,se,First-time demand buyers subsample,pct_premium,-11.552453092917869,3.4520786371602457,100*(exp(b - se^2/2) - 1),reported,-0.05923626328798121,0.0189361825264858,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.128205128205128,2779.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c2,6,2,11,Highway,highway_distance,D_location,dummy,binary,-0.008,0.009,,,,,,high,"Dummy = 1 if near a highway; proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,2789.0,0.827,se,First-time demand buyers subsample,pct_premium,-0.8008261641911041,0.8928287233533545,100*(exp(b - se^2/2) - 1),reported,-0.016859375119526475,0.018966797009467285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.888888888888889,2779.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c2,6,2,11,Pearl River,water_proximity,E_environment,dummy,binary,0.023,0.006,,,***,,,high,Dummy = 1 if located near the Pearl River (favorable geomantic attribute),"Log_Price (log10 of transaction price, RMB)",log,OLS,2789.0,0.827,se,First-time demand buyers subsample,pct_premium,2.324812091527373,0.6139599237283306,100*(exp(b - se^2/2) - 1),reported,0.07252489914843116,0.01891953890828639,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.833333333333333,2779.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c2,6,2,11,Orientation,sunlight,E_environment,dummy,binary,0.002,0.005,,,,,,high,Dummy = 1 if south-facing,"Log_Price (log10 of transaction price, RMB)",log,OLS,2789.0,0.827,se,First-time demand buyers subsample,pct_premium,0.19894763872647658,0.5010010006670002,100*(exp(b - se^2/2) - 1),reported,0.007587578829573931,0.018968947073934823,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4,2779.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c2,6,2,12,Area,living_area,A_structural,level,100 m2,0.462,0.007,,,***,,,high,Ground floor area in units of 100 m2 (sample mean 1.041 = 104 m2),"Log_Price (log10 of transaction price, RMB)",log,OLS,2789.0,0.827,se,First-time demand buyers subsample,semi_elasticity,0.462,0.007000000000000001,100*b/100 (X per 100m2->m2),reported,0.781352393430129,0.011838672627729223,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),66.0,2779.0,100m2,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c2,6,2,12,Subway,transit_distance,D_location,dummy,binary,0.03,0.005,,,***,,,high,Dummy = 1 if subway station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,2789.0,0.827,se,First-time demand buyers subsample,pct_premium,3.0441653352346387,0.5152272669767585,100*(exp(b - se^2/2) - 1),reported,0.1130868353382506,0.01884780588970843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,2779.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c2,6,2,12,Bus,transit_distance,D_location,dummy,binary,0.021,0.006,,,***,,,high,Dummy = 1 if bus station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,2789.0,0.827,se,First-time demand buyers subsample,pct_premium,2.120366980603605,0.6127332309825171,100*(exp(b - se^2/2) - 1),reported,0.0662473752954962,0.01892782151299891,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5,2779.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c2,6,2,12,Log_Park,green_space,E_environment,log,m,-0.025,0.008,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest park in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,2789.0,0.827,se,First-time demand buyers subsample,elasticity,-0.025,0.008,b (log-log),reported,-0.05917578303662831,0.018936250571721058,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.125,2779.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c2,6,2,12,Log_CBD,cbd_distance,D_location,log,m,-0.02,0.005,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest CBD in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,2789.0,0.827,se,First-time demand buyers subsample,elasticity,-0.02,0.005,b (log-log),reported,-0.07566047878575344,0.01891511969643836,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,2779.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c3,6,3,11,Hospital,hospital_distance,D_location,dummy,binary,-0.042,0.012,,,***,,,high,"Dummy = 1 if near a hospital (unfavorable geomantic attribute); proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,1854.0,0.865,se,Improvement demand buyers subsample,pct_premium,-4.119925556638582,1.1506437366869815,100*(exp(b - se^2/2) - 1),reported,-0.08123623944599233,0.023210354127426377,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5,1844.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c3,6,3,11,Slaughterhouse,hazard_site,E_environment,dummy,binary,-0.193,0.017,,,***,,,high,Dummy = 1 if near a slaughterhouse (unfavorable geomantic attribute); printed name 'Slaughterhouse',"Log_Price (log10 of transaction price, RMB)",log,OLS,1854.0,0.865,se,Improvement demand buyers subsample,pct_premium,-17.563715489887464,1.401619356036484,100*(exp(b - se^2/2) - 1),reported,-0.2555977531787489,0.02251379173077063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.352941176470587,1844.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c3,6,3,11,Highway,highway_distance,D_location,dummy,binary,-0.024,0.012,,,**,,,high,"Dummy = 1 if near a highway; proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,1854.0,0.865,se,Improvement demand buyers subsample,pct_premium,-2.3784580282721457,1.1715428517094912,100*(exp(b - se^2/2) - 1),reported,-0.046524210519923545,0.023262105259961773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,1844.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c3,6,3,11,Pearl River,water_proximity,E_environment,dummy,binary,0.024,0.007,,,***,,,high,Dummy = 1 if located near the Pearl River (favorable geomantic attribute),"Log_Price (log10 of transaction price, RMB)",log,OLS,1854.0,0.865,se,Improvement demand buyers subsample,pct_premium,2.4265223085245813,0.7170032225234351,100*(exp(b - se^2/2) - 1),reported,0.07958896739033604,0.02321344882218135,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4285714285714284,1844.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c3,6,3,11,Orientation,sunlight,E_environment,dummy,binary,-0.005,0.005,,,,,,high,Dummy = 1 if south-facing,"Log_Price (log10 of transaction price, RMB)",log,OLS,1854.0,0.865,se,Improvement demand buyers subsample,pct_premium,-0.4999958385572545,0.4975062395963412,100*(exp(b - se^2/2) - 1),reported,-0.02328100985898594,0.02328100985898594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,1844.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c3,6,3,12,Area,living_area,A_structural,level,100 m2,0.4,0.007,,,***,,,high,Ground floor area in units of 100 m2 (sample mean 1.041 = 104 m2),"Log_Price (log10 of transaction price, RMB)",log,OLS,1854.0,0.865,se,Improvement demand buyers subsample,semi_elasticity,0.4,0.007000000000000001,100*b/100 (X per 100m2->m2),reported,0.7994310076118102,0.013990042633206672,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),57.142857142857146,1844.0,100m2,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c3,6,3,12,Subway,transit_distance,D_location,dummy,binary,0.009,0.007,,,,,,high,Dummy = 1 if subway station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,1854.0,0.865,se,Improvement demand buyers subsample,pct_premium,0.9015900581470282,0.7063284352417075,100*(exp(b - se^2/2) - 1),reported,0.02992743083271046,0.023276890647663695,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2857142857142856,1844.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c3,6,3,12,Bus,transit_distance,D_location,dummy,binary,0.02,0.007,,,***,,,high,Dummy = 1 if bus station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,1854.0,0.865,se,Improvement demand buyers subsample,pct_premium,2.0176345400110485,0.714140938018729,100*(exp(b - se^2/2) - 1),reported,0.06638841840874359,0.023235946443060252,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.857142857142857,1844.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c3,6,3,12,Log_Park,green_space,E_environment,log,m,-0.032,0.008,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest park in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,1854.0,0.865,se,Improvement demand buyers subsample,elasticity,-0.032,0.008,b (log-log),reported,-0.09274777915203367,0.023186944788008413,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,1844.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c3,6,3,12,Log_CBD,cbd_distance,D_location,log,m,-0.031,0.007,,,***,,,high,"Log (base 10, inferred from descriptives) of distance to nearest CBD in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,1854.0,0.865,se,Improvement demand buyers subsample,elasticity,-0.031,0.007,b (log-log),reported,-0.10258547558030442,0.023164462227810673,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.428571428571429,1844.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c4,6,4,11,Hospital,hospital_distance,D_location,dummy,binary,-0.017,0.023,,,,,,high,"Dummy = 1 if near a hospital (unfavorable geomantic attribute); proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,216.0,0.873,se,Investment demand buyers subsample,pct_premium,-1.711632248221917,2.2612304746602923,100*(exp(b - se^2/2) - 1),reported,-0.05142950698125123,0.06958109768051637,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7391304347826088,206.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c4,6,4,11,Slaughterhouse,hazard_site,E_environment,dummy,binary,-0.08,0.06,,,,,,high,Dummy = 1 if near a slaughterhouse (unfavorable geomantic attribute); printed name 'Slaughterhouse',"Log_Price (log10 of transaction price, RMB)",log,OLS,216.0,0.873,se,Investment demand buyers subsample,pct_premium,-7.854376848524447,5.538698078319815,100*(exp(b - se^2/2) - 1),reported,-0.09249945801257607,0.06937459350943205,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3333333333333335,206.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c4,6,4,11,Highway,highway_distance,D_location,dummy,binary,-0.063,0.033,,,*,,,high,"Dummy = 1 if near a highway; proximity indicator, not distance","Log_Price (log10 of transaction price, RMB)",log,OLS,216.0,0.873,se,Investment demand buyers subsample,pct_premium,-6.156764186845198,3.0985134631741396,100*(exp(b - se^2/2) - 1),reported,-0.13185139841594756,0.0690650182178773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.909090909090909,206.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c4,6,4,11,Pearl River,water_proximity,E_environment,dummy,binary,0.107,0.02,,,***,,,high,Dummy = 1 if located near the Pearl River (favorable geomantic attribute),"Log_Price (log10 of transaction price, RMB)",log,OLS,216.0,0.873,se,Investment demand buyers subsample,pct_premium,11.271168988563108,2.2258685089586514,100*(exp(b - se^2/2) - 1),reported,0.34927616748125073,0.0652852649497665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.35,206.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c4,6,4,11,Orientation,sunlight,E_environment,dummy,binary,0.0,0.016,,,,,,high,Dummy = 1 if south-facing,"Log_Price (log10 of transaction price, RMB)",log,OLS,216.0,0.873,se,Investment demand buyers subsample,pct_premium,-0.012799180834954793,1.6,100*(exp(b - se^2/2) - 1),reported,0.0,0.06967330142916177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0,206.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c4,6,4,12,Area,living_area,A_structural,level,100 m2,0.531,0.026,,,***,,,high,Ground floor area in units of 100 m2 (sample mean 1.041 = 104 m2),"Log_Price (log10 of transaction price, RMB)",log,OLS,216.0,0.873,se,Investment demand buyers subsample,semi_elasticity,0.531,0.026000000000000002,100*b/100 (X per 100m2->m2),reported,0.8181662786458921,0.04006087240074048,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.423076923076923,206.0,100m2,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c4,6,4,12,Floor,floor_level,A_structural,level,count,0.001,0.001,,,,,,high,"Floor level of the unit (mean 13.8, max 47)","Log_Price (log10 of transaction price, RMB)",log,OLS,216.0,0.873,se,Investment demand buyers subsample,semi_elasticity,0.1,0.1,100*b/1 (per unit count),reported,0.06950480468569159,0.06950480468569159,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,206.0,count,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c4,6,4,12,Subway,transit_distance,D_location,dummy,binary,0.025,0.018,,,,,,high,Dummy = 1 if subway station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,216.0,0.873,se,Investment demand buyers subsample,pct_premium,2.5149032928362347,1.8455672169439719,100*(exp(b - se^2/2) - 1),reported,0.09631855492848873,0.06934935954851187,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.388888888888889,206.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c4,6,4,12,Bus,transit_distance,D_location,dummy,binary,-0.005,0.02,,,,,,high,Dummy = 1 if bus station within 800 m,"Log_Price (log10 of transaction price, RMB)",log,OLS,216.0,0.873,se,Investment demand buyers subsample,pct_premium,-0.5186503404233211,1.9900249583853649,100*(exp(b - se^2/2) - 1),reported,-0.01741568361535407,0.06966273446141628,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.25,206.0,binary,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c4,6,4,12,Log_Park,green_space,E_environment,log,m,-0.037,0.024,,,,,,high,"Log (base 10, inferred from descriptives) of distance to nearest park in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,216.0,0.873,se,Investment demand buyers subsample,elasticity,-0.037,0.024,b (log-log),reported,-0.10679867551740724,0.06927481655183174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5416666666666665,206.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801,0d749c58da0b3282e774a34a3cbd378d57ba0801:T6-c4,6,4,12,Log_CBD,cbd_distance,D_location,log,m,0.02,0.02,,,,,,high,"Log (base 10, inferred from descriptives) of distance to nearest CBD in metres","Log_Price (log10 of transaction price, RMB)",log,OLS,216.0,0.873,se,Investment demand buyers subsample,elasticity,0.02,0.02,b (log-log),reported,0.06950480468569159,0.06950480468569159,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,206.0,m,,2023.0,China,Asia,Upper middle income,2013.0,2016.0,condo_apartment,transaction,journal,True,True,robust,,2014.5,ols,journal,True,True,False
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,net.area,living_area,A_structural,level,m2,0.004,0.0,13.863,0.0,***,,,high,"net surface area of the dwelling in m2; SE printed as 0.000 (rounded to 3 decimals), t=13.863",ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",semi_elasticity,0.4,0.028853783452355192,100*b/1 (X per m2->m2),|b/t|,0.2545413067829516,0.018361199363986988,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.863,2774.0,m2,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,False
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,bedroom,bedrooms,A_structural,level,count,-0.013,0.015,-0.862,0.389,,,,high,number of bedrooms,ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",semi_elasticity,-1.3,1.5,100*b/1 (per unit count),reported,-0.01636424150215754,0.018984038865611993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.862,2774.0,count,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,False
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,bath: more.than.one,bathrooms,A_structural,binary,binary,0.286,0.019,14.87,0.0,***,,,high,more than one bathroom (=1) vs one,ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",pct_premium,33.08522147464765,2.529075664979354,100*(exp(b - se^2/2) - 1),reported,0.2717090347914872,0.01827229554751091,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.87,2774.0,binary,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,False
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,floor: ground.floor,floor_level,A_structural,dummy,binary,-0.212,0.02,-10.461,0.0,***,,,high,ground floor vs middle floors (reference),ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",pct_premium,-19.11970791947981,1.6179293951329996,100*(exp(b - se^2/2) - 1),reported,-0.19481316670985435,0.018622805344599404,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.461,2774.0,binary,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,False
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,floor: top.floor,floor_level,A_structural,dummy,binary,-0.073,0.019,-3.912,0.0,***,,,high,top floor vs middle floors (reference),ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",pct_premium,-7.056694778162431,1.766241577049006,100*(exp(b - se^2/2) - 1),reported,-0.07407146618235935,0.01893442387074626,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.912,2774.0,binary,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,False
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,floor: basement.floor,floor_level,A_structural,dummy,binary,-0.447,0.024,-18.323,0.0,***,,,high,basement level vs middle floors (reference),ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",pct_premium,-36.06402538501634,1.5349053798595222,100*(exp(b - se^2/2) - 1),reported,-0.32857542422356073,0.01793240322128258,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-18.323,2774.0,binary,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,True
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,total.floor,storeys,A_structural,level,count,0.024,0.002,15.813,0.0,***,,,high,total number of floors in the building,ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",semi_elasticity,2.4,0.2,100*b/1 (per unit count),reported,0.2875542015303803,0.018184670937227615,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.813,2774.0,count,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,False
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,age,age,A_structural,level,years,-0.007,0.001,-9.138,0.0,***,,,high,age of the building in years,ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",semi_elasticity,-0.7000000000000001,0.1,100*b/1 (per year),reported,-0.1709455511816297,0.01870710781151562,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.138,2774.0,years,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,False
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,carpark.indoor: yes,parking,A_structural,binary,binary,0.17,0.018,9.57,0.0,***,,,high,building has indoor parking (=1),ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",pct_premium,18.511284748718193,2.1335487323766578,100*(exp(b - se^2/2) - 1),reported,0.17877438708303808,0.018680709204079216,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.57,2774.0,binary,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,False
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,carpark.outdoor: yes,parking,A_structural,binary,binary,-0.035,0.015,-2.328,0.02,*,,,high,building has outdoor parking (=1),ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",pct_premium,-3.4503208241519867,1.4484081243863496,100*(exp(b - se^2/2) - 1),reported,-0.04415764659111069,0.018968061250477102,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.328,2774.0,binary,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,False
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,dist.transportation,transit_distance,D_location,level,km,-0.015,0.01,-1.518,0.129,,,,high,"distance to closest transportation station, km",ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",semi_elasticity,-1.5,1.0,100*b/1 (X per km->km),reported,-0.028809666890607964,0.018978700191441347,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.518,2774.0,km,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,False
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,dist.school,school_distance,D_location,level,km,0.21,0.011,18.965,0.0,***,,,high,"distance to closest primary school, km",ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",semi_elasticity,21.0,1.0999999999999999,100*b/1 (X per km->km),reported,0.3387865280803806,0.01786377685633433,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.965,2774.0,km,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,True
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,dist.mall,commercial_distance,D_location,level,km,-0.16,0.008,-19.614,0.0,***,,,high,"distance to closest shopping mall, km",ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",semi_elasticity,-16.0,0.8,100*b/1 (X per km->km),reported,-0.34898869781204694,0.01779283663771015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-19.614,2774.0,km,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,True
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,dist.hospital,hospital_distance,D_location,level,km,-0.091,0.011,-8.619,0.0,***,,,high,"distance to closest hospital, km",ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",semi_elasticity,-9.1,1.0999999999999999,100*b/1 (X per km->km),reported,-0.1614971990908349,0.018737347614669327,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.619,2774.0,km,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,False
0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211,0d7a1f874f9358489f6f5882b5a4900f21774211:T3-ols,3,Coef.,4,dist.university,university_distance,D_location,level,km,-0.049,0.008,-6.395,0.0,***,,,high,"distance to closest university, km",ln asking price (TRY),log,OLS,2784.0,0.6974,se,"Global OLS; SE, t and p in separate columns; adj R2 0.6953",semi_elasticity,-4.9,0.8,100*b/1 (X per km->km),reported,-0.12053394470955732,0.018848153981166117,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.395,2774.0,km,,2022.0,Turkey,Asia,Upper middle income,2021.0,2021.0,condo_apartment,listing,journal,False,False,OLS,,2021.0,ols,journal,True,True,True
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,TTBellecour,cbd_distance,D_location,log,"minutes (travel time by car to Bellecour, morning peak)",-0.224,,,0.001,,,,high,travel time by car to Bellecour (central Lyon public-transport junction); log; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,elasticity,-0.224,0.06807420765077343,b (log-log),|b/z(p)| (two-sided normal),-0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,4352.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,TTBellecour,cbd_distance,D_location,log,"minutes (travel time by car to Bellecour, morning peak)",-0.093,,,0.001,,,,high,travel time by car to Bellecour (central Lyon public-transport junction); log; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,elasticity,-0.093,0.02826295228358004,b (log-log),|b/z(p)| (two-sided normal),-0.111314708340827,0.03382884183115508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,863.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,TTBellecour,cbd_distance,D_location,log,"minutes (travel time by car to Bellecour, morning peak)",-0.176,,,0.001,,,,high,travel time by car to Bellecour (central Lyon public-transport junction); log; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,elasticity,-0.176,0.0534868774398934,b (log-log),|b/z(p)| (two-sided normal),-0.11137845681048097,0.033848215164015094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,862.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Area,living_area,A_structural,log,m2,0.932,,,0.001,,,,high,p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,elasticity,0.932,0.28323732826125375,b (log-log),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,m2,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Area,living_area,A_structural,log,m2,0.69,,,0.001,,,,high,p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,elasticity,0.69,0.20969287178140028,b (log-log),|b/z(p)| (two-sided normal),0.111314708340827,0.03382884183115508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,863.0,m2,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Area,living_area,A_structural,log,m2,0.383,,,0.001,,,,high,p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,elasticity,0.383,0.1163947389743135,b (log-log),|b/z(p)| (two-sided normal),0.11137845681048097,0.033848215164015094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,862.0,m2,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Bath2,bathrooms,A_structural,dummy,binary (2 bathrooms vs 1),0.094,,,0.001,,,,high,reference Bath1; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,9.81115891628872,3.138239696639544,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Bath2,bathrooms,A_structural,dummy,binary (2 bathrooms vs 1),0.046,,,0.001,,,,high,reference Bath1,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,4.697210259074258,1.4637602680158552,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.111314708340827,0.03382884183115508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Bath2,bathrooms,A_structural,dummy,binary (2 bathrooms vs 1),0.053,,,0.78,,,,high,reference Bath1,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,3.561764091167685,20.007505504190398,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0095132135593042,0.034058593887534856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.27931903444745415,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,True
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,ParkUn,parking,A_structural,dummy,binary,0.092,,,0.001,,,,high,dummy for no data about parking places; reference Park0; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,9.59363869896599,3.0653318408297396,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,ParkUn,parking,A_structural,dummy,binary,0.016,,,0.48,,,,high,dummy for no data about parking places; reference Park0,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,1.5867997188913519,2.3018547322160114,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.024035872798804793,0.03403056149499872,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7063025628400874,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,ParkUn,parking,A_structural,dummy,binary,0.043,,,0.09,,,,high,dummy for no data about parking places; reference Park0,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,4.360218154581386,2.647716769145038,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.05764943798712797,0.03400348935110595,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6953977102721358,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Park1,parking,A_structural,dummy,binary (1 parking place vs 0),0.154,,,0.001,,,,high,reference Park0; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,16.521408300128826,5.45929607088871,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Park1,parking,A_structural,dummy,binary (1 parking place vs 0),0.039,,,0.2,,,,high,reference Park0,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,3.9289130313920007,3.1642151554880136,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04358307089338646,0.03400805091667588,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2815515655446004,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Park1,parking,A_structural,dummy,binary (1 parking place vs 0),0.09,,,0.001,,,,high,reference Park0,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,9.376508951426498,2.9927027971239415,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.11137845681048097,0.033848215164015094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Park2,parking,A_structural,dummy,binary (2 parking places vs 0),0.193,,,0.001,,,,high,reference Park0; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,21.079830671894094,7.113948563580198,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Park2,parking,A_structural,dummy,binary (2 parking places vs 0),0.08,,,0.01,,,,high,reference Park0,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,8.276472603029529,3.3644684954315505,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.08734712204436584,0.03391029130852016,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Park2,parking,A_structural,dummy,binary (2 parking places vs 0),0.067,,,0.58,,,,high,reference Park0,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,6.14868914374298,12.946291161639246,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.018845011198182028,0.03405408666381895,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5533847195556729,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Floor1,floor_level,A_structural,dummy,binary (storey 1 vs ground floor),0.067,,,0.001,,,,high,reference FloorGr; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,6.907384157384722,2.1772440367082515,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Floor1,floor_level,A_structural,dummy,binary (storey 1 vs ground floor),0.027,,,0.36,,,,high,reference FloorGr,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,2.6920974809605314,3.0303679966629367,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.031144274525401014,0.03402388286273497,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.915365087842814,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Floor1,floor_level,A_structural,dummy,binary (storey 1 vs ground floor),0.078,,,0.01,,,,high,reference FloorGr,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,8.062709385367217,3.2738026258216126,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.08739738596862962,0.03392980499453753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Floor2_4,floor_level,A_structural,dummy,binary (storeys 2-4 vs ground floor),0.104,,,0.001,,,,high,reference FloorGr; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,10.90463857150079,3.506990118232529,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Floor2_4,floor_level,A_structural,dummy,binary (storeys 2-4 vs ground floor),0.038,,,0.16,,,,high,reference FloorGr,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,3.8351424894471853,2.8092367651854393,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04777457804920982,0.034001526611699286,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4050715603096329,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Floor2_4,floor_level,A_structural,dummy,binary (storeys 2-4 vs ground floor),0.103,,,0.001,,,,high,reference FloorGr; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,10.794848442449245,3.4697975263997636,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.11137845681048096,0.033848215164015094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.290526731491894,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Floor5_8,floor_level,A_structural,dummy,binary (storeys 5-8 vs ground floor),0.133,,,0.001,,,,high,reference FloorGr; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,14.131733212443386,4.616867212293704,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Floor5_8,floor_level,A_structural,dummy,binary (storeys 5-8 vs ground floor),0.073,,,0.01,,,,high,reference FloorGr,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,7.5298622337698795,3.0486620012661305,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.08734712204436584,0.03391029130852016,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Floor5_8,floor_level,A_structural,dummy,binary (storeys 5-8 vs ground floor),0.134,,,0.001,,,,high,reference FloorGr; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,14.244513428068561,4.656234406669494,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.11137845681048097,0.033848215164015094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Floor9+,floor_level,A_structural,dummy,binary (storey 9+ vs ground floor),0.132,,,0.001,,,,high,reference FloorGr; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,14.019053801062121,4.577574061371702,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Floor9+,floor_level,A_structural,dummy,binary (storey 9+ vs ground floor),0.166,,,0.002,,,,high,reference FloorGr,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,17.887100770002085,6.341760601457564,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.10461551144386591,0.03385360745697441,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.090232306167813,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Floor9+,floor_level,A_structural,dummy,binary (storey 9+ vs ground floor),0.194,,,0.01,,,,high,reference FloorGr,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,21.065772218991107,9.144032897249696,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.08739738596862962,0.03392980499453753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Constr1850_1913,age,A_structural,dummy,binary (construction period 1850-1913),-0.092,,,0.001,,,,high,"construction-period dummy, not age; reference Constr1981_1991; p printed as <0.001 (upper bound)",log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,-8.825128094685885,2.550159308996181,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Constr1850_1913,age,A_structural,dummy,binary (construction period 1850-1913),0.042,,,0.18,,,,high,"construction-period dummy, not age; reference Constr1981_1991",log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,4.238291054776244,3.266932959928941,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.045592372499090386,0.034004998193894215,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3407550336902165,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Constr1850_1913,age,A_structural,dummy,binary (construction period 1850-1913),-0.119,,,0.01,,,,high,"construction-period dummy, not age; reference Constr1981_1991",log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,-11.313912735955133,4.101557822372462,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.08739738596862962,0.03392980499453753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Constr1914_1947,age,A_structural,dummy,binary (construction period 1914-1947),-0.082,,,0.001,,,,high,"construction-period dummy, not age; reference Constr1981_1991; p printed as <0.001 (upper bound)",log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,-7.901405530365002,2.295811788736009,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Constr1914_1947,age,A_structural,dummy,binary (construction period 1914-1947),0.112,,,0.001,,,,high,"construction-period dummy, not age; reference Constr1981_1991",log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,11.786513602338001,3.8070938367805707,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.111314708340827,0.03382884183115508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Constr1914_1947,age,A_structural,dummy,binary (construction period 1914-1947),-0.11,,,0.01,,,,high,"construction-period dummy, not age; reference Constr1981_1991",log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,-10.498235463344496,3.8256321855974775,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.08739738596862962,0.03392980499453753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Constr1948_1969,age,A_structural,dummy,binary (construction period 1948-1969),-0.153,,,0.001,,,,high,"construction-period dummy, not age; reference Constr1981_1991; p printed as <0.001 (upper bound)",log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,-14.279740736994073,3.9900556400469003,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,True
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Constr1948_1969,age,A_structural,dummy,binary (construction period 1948-1969),0.008,,,0.73,,,,high,"construction-period dummy, not age; reference Constr1981_1991",log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,0.7761308474019568,2.336615506153631,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01174739905645614,0.03403804698656786,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.34512553147047237,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Constr1948_1969,age,A_structural,dummy,binary (construction period 1948-1969),-0.122,,,0.002,,,,high,"construction-period dummy, not age; reference Constr1981_1991",log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,-11.554116324846175,3.494497832469954,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.10467551120055282,0.03387302339427051,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.090232306167813,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Constr1970_1980,age,A_structural,dummy,binary (construction period 1970-1980),-0.123,,,0.001,,,,high,"construction-period dummy, not age; reference Constr1981_1991; p printed as <0.001 (upper bound)",log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,-11.635389787059381,3.305380547559575,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Constr1970_1980,age,A_structural,dummy,binary (construction period 1970-1980),-0.005,,,0.83,,,,high,"construction-period dummy, not age; reference Constr1981_1991",log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,-0.5257300481633531,2.3171989111523335,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.007308331187479285,0.03403948678856365,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.21470156800174456,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Constr1970_1980,age,A_structural,dummy,binary (construction period 1970-1980),-0.088,,,0.03,,,,high,"construction-period dummy, not age; reference Constr1981_1991",log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,-8.499175629065437,3.7135299978312752,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.07371249220491717,0.033967475717284895,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1700903775845606,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Constr1992<,age,A_structural,dummy,binary (constructed 1992 or later),0.099,,,0.001,,,,high,"construction-period dummy, not age; reference Constr1981_1991; p printed as <0.001 (upper bound)",log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,10.356671797022155,3.3217345603137693,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Constr1992<,age,A_structural,dummy,binary (constructed 1992 or later),0.099,,,0.001,,,,high,"construction-period dummy, not age; reference Constr1981_1991; p printed as <0.001 (upper bound)",log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,10.356671797022155,3.3217345603137693,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.111314708340827,0.03382884183115508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Constr1992<,age,A_structural,dummy,binary (constructed 1992 or later),-0.085,,,0.12,,,,high,"construction-period dummy, not age; reference Constr1981_1991",log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,-8.28593363372695,5.021537826822176,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.05288170217512109,0.03401247767449581,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5547735945968535,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,CondMed,condition,A_structural,dummy,binary (some maintenance needed vs good),-0.109,,,0.001,,,,high,reference CondGood; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,-10.376143504762714,2.970454990438312,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,CondMed,condition,A_structural,dummy,binary (some maintenance needed vs good),0.009,,,0.63,,,,high,reference CondGood,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,0.8864536080777974,1.8851690753366448,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.016395968374840194,0.03403582006893375,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.48172684958473033,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,CondMed,condition,A_structural,dummy,binary (some maintenance needed vs good),-0.072,,,0.001,,,,high,reference CondGood,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,-6.969183636807719,2.0360942172936074,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.11137845681048097,0.033848215164015094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,CondBad,condition,A_structural,dummy,binary (renovation needed vs good),-0.215,,,0.001,,,,high,reference CondGood; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,-19.51783652868023,5.269867829321795,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.049817439149501146,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.290526731491894,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,CondBad,condition,A_structural,dummy,binary (renovation needed vs good),-0.092,,,0.04,,,,high,reference CondGood,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,-8.880954906425576,4.085877943683622,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.06974020718060914,0.033957513900350164,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.053748910631823,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,CondBad,condition,A_structural,dummy,binary (renovation needed vs good),-0.197,,,0.001,,,,high,reference CondGood; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,-18.027973622738756,4.916372604250096,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.11137845681048097,0.033848215164015094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,ViewNo,view,E_environment,dummy,binary (no data about view vs good view),-0.04,,,0.001,,,,high,missing-data dummy; reference ViewGood; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,-3.9281546620892005,1.1679460676700961,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,ViewNo,view,E_environment,dummy,binary (no data about view vs good view),-0.027,,,0.03,,,,high,missing-data dummy; reference ViewGood,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,-2.6714093881469725,1.2110441939477714,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0736700046213568,0.03394789700111748,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1700903775845606,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,ViewNo,view,E_environment,dummy,binary (no data about view vs good view),-0.017,,,0.37,,,,high,missing-data dummy; reference ViewGood,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,-1.703307008409083,1.8643546266877977,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.030519780080790287,0.034044268693659764,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8964733640019161,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,ViewBad,view,E_environment,dummy,binary (view decreasing value vs good view),-0.098,,,0.001,,,,high,reference ViewGood,log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,-9.3753103740273,2.7002240011464598,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,ViewBad,view,E_environment,dummy,binary (view decreasing value vs good view),-0.002,,,0.96,,,,high,reference ViewGood,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,-0.27912052040550694,3.9797834161504926,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.001708235339414418,0.034060085469577506,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.05015358346473367,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Cellar1,basement,A_structural,dummy,binary (1 cellar vs 0),0.099,,,0.001,,,,high,reference Cellar0,log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,10.356671797022155,3.3217345603137693,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Cellar1,basement,A_structural,dummy,binary (1 cellar vs 0),-0.002,,,0.88,,,,high,reference Cellar0,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,-0.20855733905336127,1.3221264949722646,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.005138984001514712,0.034039946386449985,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.15096921549677725,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Cellar1,basement,A_structural,dummy,binary (1 cellar vs 0),0.092,,,0.001,,,,high,reference Cellar0; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,9.59363869896599,3.0653318408297396,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.11137845681048097,0.033848215164015094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Cellar2,basement,A_structural,dummy,binary (2 cellars vs 0),0.032,,,0.001,,,,high,reference Cellar0,log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,3.246868210186604,1.0041115865599883,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.049817439149501146,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.290526731491894,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Cellar2,basement,A_structural,dummy,binary (2 cellars vs 0),0.001,,,0.98,,,,high,reference Cellar0,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,0.020441285114136676,3.9929959846531253,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0008533552506547738,0.03404038348412105,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.02506890825871106,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Cellar2,basement,A_structural,dummy,binary (2 cellars vs 0),0.021,,,0.84,,,,high,reference Cellar0,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,1.5712578795442855,10.622266343392063,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.006876356610852283,0.034059329900501326,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.20189347914185088,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Garden,garden,C_exterior,binary,binary,0.049,,,0.02,,,,high,,log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,4.998741018300423,2.212085207053515,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.03524198409591599,0.01514906024553458,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3263478740408408,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Garden,garden,C_exterior,binary,binary,-0.011,,,0.73,,,,high,,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,-1.1441963965284963,3.1523785041848975,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.01174739905645614,0.03403804698656786,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.34512553147047237,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,True
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Garden,garden,C_exterior,binary,binary,0.101,,,0.16,,,,high,,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,10.342221622026981,7.9521886268542215,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.047802218203583914,0.034021198317507634,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4050715603096329,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,Terrace,terrace_balcony,C_exterior,binary,binary,0.043,,,0.01,,,,high,,log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,4.379244369960511,1.7427136734848523,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.03901591835390113,0.015146934736764643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,Terrace,terrace_balcony,C_exterior,binary,binary,0.049,,,0.01,,,,high,,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,5.003034393934214,1.9978341389066512,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.08734712204436584,0.03391029130852016,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,Terrace,terrace_balcony,C_exterior,binary,binary,0.037,,,0.69,,,,high,,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,3.3237708711354674,9.626213900324695,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01358380403342462,0.03405699263603073,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.39885506564233686,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,NewApartment,age,A_structural,dummy,binary (new apartment sold on primary market),0.046,,,0.01,,,,high,"new-build indicator, not age in years",log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,pct_premium,4.690745787946238,1.8698996411624882,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.03901591835390113,0.015146934736764643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,4352.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,NewApartment,age,A_structural,dummy,binary (new apartment sold on primary market),-0.067,,,0.001,,,,high,"new-build indicator, not age in years",log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,pct_premium,-6.499863983219445,1.9041960027218936,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.111314708340827,0.03382884183115508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,863.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,NewApartment,age,A_structural,dummy,binary (new apartment sold on primary market),0.256,,,0.001,,,,high,"new-build indicator, not age in years; p printed as <0.001 (upper bound)",log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,pct_premium,28.784934213789025,10.04971924973948,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.11137845681048096,0.033848215164015094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.290526731491894,862.0,binary,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,%MidIncome,income,F_neighbourhood,log,"share (% of middle-income households in IRIS zone), log",0.671,,,0.001,,,,high,log of percentage of middle-income households; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,elasticity,0.671,0.20391872023959362,b (log-log),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,share log,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,True
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-expensive,Appendix 2,Expensive,14,%MidIncome,income,F_neighbourhood,log,"share (% of middle-income households in IRIS zone), log",0.313,,,0.05,,,,high,log of percentage of middle-income households,log transaction price (Euro),log,OLS,873.0,0.839,p,20% most expensive apartments; model with TTBellecour by car,elasticity,0.313,0.15969681201741665,b (log-log),|b/z(p)| (two-sided normal),0.06656995353935329,0.03396488612262703,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9599639845400545,863.0,share log,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,%MidIncome,income,F_neighbourhood,log,"share (% of middle-income households in IRIS zone), log",0.558,,,0.01,,,,high,log of percentage of middle-income households,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,elasticity,0.558,0.2166292615862411,b (log-log),|b/z(p)| (two-sided normal),0.08739738596862962,0.03392980499453753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,862.0,share log,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-overall,Appendix 2,Overall,14,%HighIncome,income,F_neighbourhood,log,"share (% of high-income households in IRIS zone), log",0.136,,,0.001,,,,high,log of percentage of high-income households; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,0.838,p,Overall sample; model with TTBellecour by car,elasticity,0.136,0.041330768930826725,b (log-log),|b/z(p)| (two-sided normal),0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,4352.0,share log,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A2-OLS-cheap,Appendix 2,Cheap,14,%HighIncome,income,F_neighbourhood,log,"share (% of high-income households in IRIS zone), log",0.029,,,0.61,,,,high,log of percentage of high-income households,log transaction price (Euro),log,OLS,872.0,0.705,p,20% cheapest apartments; model with TTBellecour by car,elasticity,0.029,0.056854556150302736,b (log-log),|b/z(p)| (two-sided normal),0.017370549634933136,0.03405499619244575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5100734569685949,862.0,share log,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:T4-OLS-overall-2,4,Overall / TTCityHall by car,10,TTCityHall,cbd_distance,D_location,log,minutes (travel time by car to Lyon City Hall),-0.278,,,0.001,,,,high,TTCityHall by car; same specification as Appendix 2 with this accessibility measure; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,,p,Overall sample; variant with TTCityHall by car as the accessibility measure; adj. R2 range across the 8 variants 0.84-0.85; full covariate set as Appendix 2,elasticity,-0.278,0.08448495413801346,b (log-log),|b/z(p)| (two-sided normal),-0.04981743914950115,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,4352.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:T4-OLS-overall-5,4,Overall / TTBellecour by public transport,10,TTBellecour,cbd_distance,D_location,log,minutes (travel time by public transport to Bellecour),-0.223,,,0.001,,,,high,TTBellecour by public transport; same specification as Appendix 2 with this accessibility measure; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,,p,Overall sample; variant with TTBellecour by public transport as the accessibility measure; adj. R2 range across the 8 variants 0.84-0.85; full covariate set as Appendix 2,elasticity,-0.223,0.06777030493804675,b (log-log),|b/z(p)| (two-sided normal),-0.04981743914950116,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.290526731491895,4352.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:T4-OLS-overall-6,4,Overall / TTCityHall by public transport,10,TTCityHall,cbd_distance,D_location,log,minutes (travel time by public transport to Lyon City Hall),-0.228,,,0.001,,,,high,TTCityHall by public transport; same specification as Appendix 2 with this accessibility measure; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,4362.0,,p,Overall sample; variant with TTCityHall by public transport as the accessibility measure; adj. R2 range across the 8 variants 0.84-0.85; full covariate set as Appendix 2,elasticity,-0.228,0.0692898185016801,b (log-log),|b/z(p)| (two-sided normal),-0.049817439149501146,0.015139654898629068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.290526731491894,4352.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:T4-OLS-expensive-2,4,Expensive / TTCityHall by car,10,TTCityHall,cbd_distance,D_location,log,minutes (travel time by car to Lyon City Hall),-0.129,,,0.001,,,,high,TTCityHall by car; same specification as Appendix 2 with this accessibility measure; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,873.0,,p,Expensive sample; variant with TTCityHall by car as the accessibility measure; adj. R2 range across the 8 variants 0.84-0.86; full covariate set as Appendix 2,elasticity,-0.129,0.039203449941740055,b (log-log),|b/z(p)| (two-sided normal),-0.111314708340827,0.03382884183115508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,863.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:T4-OLS-expensive-5,4,Expensive / TTBellecour by public transport,10,TTBellecour,cbd_distance,D_location,log,minutes (travel time by public transport to Bellecour),-0.062,,,0.001,,,,high,TTBellecour by public transport; same specification as Appendix 2 with this accessibility measure; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,873.0,,p,Expensive sample; variant with TTBellecour by public transport as the accessibility measure; adj. R2 range across the 8 variants 0.84-0.86; full covariate set as Appendix 2,elasticity,-0.062,0.01884196818905336,b (log-log),|b/z(p)| (two-sided normal),-0.111314708340827,0.03382884183115508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,863.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:T4-OLS-expensive-6,4,Expensive / TTCityHall by public transport,10,TTCityHall,cbd_distance,D_location,log,minutes (travel time by public transport to Lyon City Hall),-0.083,,,0.001,,,,high,TTCityHall by public transport; same specification as Appendix 2 with this accessibility measure; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,873.0,,p,Expensive sample; variant with TTCityHall by public transport as the accessibility measure; adj. R2 range across the 8 variants 0.84-0.86; full covariate set as Appendix 2,elasticity,-0.083,0.02522392515631337,b (log-log),|b/z(p)| (two-sided normal),-0.111314708340827,0.03382884183115508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,863.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:T4-OLS-cheap-2,4,Cheap / TTCityHall by car,10,TTCityHall,cbd_distance,D_location,log,minutes (travel time by car to Lyon City Hall),-0.217,,,0.001,,,,high,TTCityHall by car; same specification as Appendix 2 with this accessibility measure; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,872.0,,p,Cheap sample; variant with TTCityHall by car as the accessibility measure; adj. R2 range across the 8 variants 0.70-0.72; full covariate set as Appendix 2,elasticity,-0.217,0.06594688866168676,b (log-log),|b/z(p)| (two-sided normal),-0.11137845681048097,0.033848215164015094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,862.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:T4-OLS-cheap-5,4,Cheap / TTBellecour by public transport,10,TTBellecour,cbd_distance,D_location,log,minutes (travel time by public transport to Bellecour),-0.173,,,0.001,,,,high,TTBellecour by public transport; same specification as Appendix 2 with this accessibility measure; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,872.0,,p,Cheap sample; variant with TTBellecour by public transport as the accessibility measure; adj. R2 range across the 8 variants 0.70-0.72; full covariate set as Appendix 2,elasticity,-0.173,0.0525751693017134,b (log-log),|b/z(p)| (two-sided normal),-0.11137845681048097,0.033848215164015094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,862.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:T4-OLS-cheap-6,4,Cheap / TTCityHall by public transport,10,TTCityHall,cbd_distance,D_location,log,minutes (travel time by public transport to Lyon City Hall),-0.157,,,0.001,,,,high,TTCityHall by public transport; same specification as Appendix 2 with this accessibility measure; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,872.0,,p,Cheap sample; variant with TTCityHall by public transport as the accessibility measure; adj. R2 range across the 8 variants 0.70-0.72; full covariate set as Appendix 2,elasticity,-0.157,0.047712725898086734,b (log-log),|b/z(p)| (two-sided normal),-0.11137845681048097,0.033848215164015094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,862.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-SFL-1,Appendix 3,OLS / Sainte-Foy-les-Lyon / TTBellecour by car,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by car to Bellecour),-0.525,,,0.02,,,,high,TTBellecour by car; submarket model,log transaction price (Euro),log,OLS,84.0,,p,Sainte-Foy-les-Lyon submarket; OLS model with TTBellecour by car; R2 (adj. for OLS) 0.83-0.84; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.525,0.22567562051159648,b (log-log),|b/z(p)| (two-sided normal),-0.26105491835379324,0.11221662988018372,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3263478740408408,74.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-SFL-2,Appendix 3,OLS / Sainte-Foy-les-Lyon / TTCityHall by car,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by car to Lyon City Hall),-0.381,,,0.11,,,,high,TTCityHall by car; submarket model,log transaction price (Euro),log,OLS,84.0,,p,Sainte-Foy-les-Lyon submarket; OLS model with TTCityHall by car; R2 (adj. for OLS) 0.83-0.84; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.381,0.2383942156192711,b (log-log),|b/z(p)| (two-sided normal),-0.18266052035198002,0.11429189363233119,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5981931399228173,74.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-SFL-5,Appendix 3,OLS / Sainte-Foy-les-Lyon / TTBellecour by public transport,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by public transport to Bellecour),-0.304,,,0.05,,,,high,TTBellecour by public transport; submarket model,log transaction price (Euro),log,OLS,84.0,,p,Sainte-Foy-les-Lyon submarket; OLS model with TTBellecour by public transport; R2 (adj. for OLS) 0.83-0.84; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.304,0.15510489090509477,b (log-log),|b/z(p)| (two-sided normal),-0.22214810239204405,0.11334295127069675,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9599639845400545,74.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-SFL-6,Appendix 3,OLS / Sainte-Foy-les-Lyon / TTCityHall by public transport,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by public transport to Lyon City Hall),-0.203,,,0.21,,,,high,TTCityHall by public transport; submarket model,log transaction price (Euro),log,OLS,84.0,,p,Sainte-Foy-les-Lyon submarket; OLS model with TTCityHall by public transport; R2 (adj. for OLS) 0.83-0.84; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.203,0.1619380957468741,b (log-log),|b/z(p)| (two-sided normal),-0.14420097617368294,0.11503266742072203,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2535654384704504,74.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-SFL-1,Appendix 3,spatial_error / Sainte-Foy-les-Lyon / TTBellecour by car,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by car to Bellecour),-0.599,,,0.01,,,,high,TTBellecour by car; submarket model,log transaction price (Euro),log,spatial_error,84.0,,p,Sainte-Foy-les-Lyon submarket; spatial_error model with TTBellecour by car; R2 (adj. for OLS) 0.88; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.599,0.2325464653945491,b (log-log),|b/z(p)| (two-sided normal),-0.2868504680733633,0.11136237470322635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,74.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-SFL-2,Appendix 3,spatial_error / Sainte-Foy-les-Lyon / TTCityHall by car,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by car to Lyon City Hall),-0.427,,,0.1,,,,high,TTCityHall by car; submarket model,log transaction price (Euro),log,spatial_error,84.0,,p,Sainte-Foy-les-Lyon submarket; spatial_error model with TTCityHall by car; R2 (adj. for OLS) 0.88; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.427,0.2595975672263253,b (log-log),|b/z(p)| (two-sided normal),-0.18780791063299643,0.11417910235640513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6448536269514729,74.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-SFL-5,Appendix 3,spatial_error / Sainte-Foy-les-Lyon / TTBellecour by public transport,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by public transport to Bellecour),-0.486,,,0.01,,,,high,TTBellecour by public transport; submarket model,log transaction price (Euro),log,spatial_error,84.0,,p,Sainte-Foy-les-Lyon submarket; spatial_error model with TTBellecour by public transport; R2 (adj. for OLS) 0.88; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.486,0.18867709880091965,b (log-log),|b/z(p)| (two-sided normal),-0.2868504680733633,0.11136237470322635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,74.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-SFL-6,Appendix 3,spatial_error / Sainte-Foy-les-Lyon / TTCityHall by public transport,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by public transport to Lyon City Hall),-0.268,,,0.17,,,,high,TTCityHall by public transport; submarket model,log transaction price (Euro),log,spatial_error,84.0,,p,Sainte-Foy-les-Lyon submarket; spatial_error model with TTCityHall by public transport; R2 (adj. for OLS) 0.88; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.268,0.19530626445028973,b (log-log),|b/z(p)| (two-sided normal),-0.15752392941738522,0.11479630677627095,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3722038089987258,74.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-OUL-1,Appendix 3,OLS / Oullins / TTBellecour by car,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by car to Bellecour),0.098,,,0.62,,,,high,TTBellecour by car; submarket model,log transaction price (Euro),log,OLS,100.0,,p,Oullins submarket; OLS model with TTBellecour by car; R2 (adj. for OLS) 0.88-0.89; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.098,0.19764027699940126,b (log-log),|b/z(p)| (two-sided normal),0.05219596841227129,0.1052655679107479,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4958503473474533,90.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-OUL-2,Appendix 3,OLS / Oullins / TTCityHall by car,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by car to Lyon City Hall),0.306,,,0.25,,,,high,TTCityHall by car; submarket model,log transaction price (Euro),log,OLS,100.0,,p,Oullins submarket; OLS model with TTCityHall by car; R2 (adj. for OLS) 0.88-0.89; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.306,0.2660061414558937,b (log-log),|b/z(p)| (two-sided normal),0.1203757361007471,0.10464276171592372,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1503493803760079,90.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-OUL-5,Appendix 3,OLS / Oullins / TTBellecour by public transport,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by public transport to Bellecour),0.307,,,0.18,,,,high,TTBellecour by public transport; submarket model,log transaction price (Euro),log,OLS,100.0,,p,Oullins submarket; OLS model with TTBellecour by public transport; R2 (adj. for OLS) 0.88-0.89; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.307,0.22897545956253543,b (log-log),|b/z(p)| (two-sided normal),0.13993737266852577,0.10437206585260414,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3407550336902165,90.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-OUL-6,Appendix 3,OLS / Oullins / TTCityHall by public transport,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by public transport to Lyon City Hall),0.396,,,0.03,,,,high,TTCityHall by public transport; submarket model,log transaction price (Euro),log,OLS,100.0,,p,Oullins submarket; OLS model with TTCityHall by public transport; R2 (adj. for OLS) 0.88-0.89; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.396,0.1824808791792218,b (log-log),|b/z(p)| (two-sided normal),0.2229880171227916,0.1027551752802989,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1700903775845606,90.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-OUL-1,Appendix 3,spatial_error / Oullins / TTBellecour by car,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by car to Bellecour),0.117,,,0.59,,,,high,TTBellecour by car; submarket model,log transaction price (Euro),log,spatial_error,100.0,,p,Oullins submarket; spatial_error model with TTBellecour by car; R2 (adj. for OLS) 0.91; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.117,0.21713470040141672,b (log-log),|b/z(p)| (two-sided normal),0.056706908765723284,0.10523963799603243,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5388360302784503,90.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-OUL-2,Appendix 3,spatial_error / Oullins / TTCityHall by car,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by car to Lyon City Hall),0.311,,,0.27,,,,high,TTCityHall by car; submarket model,log transaction price (Euro),log,spatial_error,100.0,,p,Oullins submarket; spatial_error model with TTCityHall by car; R2 (adj. for OLS) 0.91; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.311,0.2819423053135756,b (log-log),|b/z(p)| (two-sided normal),0.11549491204365028,0.10470386415940645,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1030625561995973,90.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-OUL-5,Appendix 3,spatial_error / Oullins / TTBellecour by public transport,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by public transport to Bellecour),0.318,,,0.18,,,,high,TTBellecour by public transport; submarket model,log transaction price (Euro),log,spatial_error,100.0,,p,Oullins submarket; spatial_error model with TTBellecour by public transport; R2 (adj. for OLS) 0.91; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.318,0.23717979198985756,b (log-log),|b/z(p)| (two-sided normal),0.13993737266852577,0.10437206585260414,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3407550336902165,90.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-OUL-6,Appendix 3,spatial_error / Oullins / TTCityHall by public transport,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by public transport to Lyon City Hall),0.422,,,0.02,,,,high,TTCityHall by public transport; submarket model,log transaction price (Euro),log,spatial_error,100.0,,p,Oullins submarket; spatial_error model with TTCityHall by public transport; R2 (adj. for OLS) 0.91; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.422,0.18140021305884516,b (log-log),|b/z(p)| (two-sided normal),0.23816250997637697,0.1023761375647965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3263478740408408,90.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-VEN-1,Appendix 3,OLS / Venissieux / TTBellecour by car,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by car to Bellecour),-0.237,,,0.17,,,,high,TTBellecour by car; submarket model,log transaction price (Euro),log,OLS,97.0,,p,Venissieux submarket; OLS model with TTBellecour by car; R2 (adj. for OLS) 0.78-0.85; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.237,0.17271486818924875,b (log-log),|b/z(p)| (two-sided normal),-0.1455490605974166,0.10606956462511302,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3722038089987258,87.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-VEN-2,Appendix 3,OLS / Venissieux / TTCityHall by car,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by car to Lyon City Hall),-0.478,,,0.02,,,,high,TTCityHall by car; submarket model,log transaction price (Euro),log,OLS,97.0,,p,Venissieux submarket; OLS model with TTCityHall by car; R2 (adj. for OLS) 0.78-0.85; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.478,0.20547227924674877,b (log-log),|b/z(p)| (two-sided normal),-0.24199741198602165,0.10402460211837311,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3263478740408408,87.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-VEN-5,Appendix 3,OLS / Venissieux / TTBellecour by public transport,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by public transport to Bellecour),-0.935,,,0.001,,,,high,TTBellecour by public transport; submarket model; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,97.0,,p,Venissieux submarket; OLS model with TTBellecour by public transport; R2 (adj. for OLS) 0.78-0.85; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.935,0.28414903639943373,b (log-log),|b/z(p)| (two-sided normal),-0.33268620942909904,0.10110424153225529,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,87.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-VEN-6,Appendix 3,OLS / Venissieux / TTCityHall by public transport,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by public transport to Lyon City Hall),-0.911,,,0.001,,,,high,TTCityHall by public transport; submarket model; p printed as <0.001 (upper bound),log transaction price (Euro),log,OLS,97.0,,p,Venissieux submarket; OLS model with TTCityHall by public transport; R2 (adj. for OLS) 0.78-0.85; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.911,0.27685537129399374,b (log-log),|b/z(p)| (two-sided normal),-0.33268620942909904,0.10110424153225529,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,87.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-VEN-1,Appendix 3,spatial_error / Venissieux / TTBellecour by car,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by car to Bellecour),0.284,,,0.39,,,,high,TTBellecour by car; submarket model,log transaction price (Euro),log,spatial_error,97.0,,p,Venissieux submarket; spatial_error model with TTBellecour by car; R2 (adj. for OLS) 0.87-0.89; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.284,0.33037955236101696,b (log-log),|b/z(p)| (two-sided normal),0.09177174358955426,0.10675882945953157,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8596173642419115,87.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-VEN-2,Appendix 3,spatial_error / Venissieux / TTCityHall by car,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by car to Lyon City Hall),-0.26,,,0.45,,,,high,TTCityHall by car; submarket model,log transaction price (Euro),log,spatial_error,97.0,,p,Venissieux submarket; spatial_error model with TTCityHall by car; R2 (adj. for OLS) 0.87-0.89; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.26,0.3441816629630201,b (log-log),|b/z(p)| (two-sided normal),-0.08072467925276114,0.10686136287450669,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7554150263604693,87.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-VEN-5,Appendix 3,spatial_error / Venissieux / TTBellecour by public transport,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by public transport to Bellecour),-0.947,,,0.001,,,,high,TTBellecour by public transport; submarket model; p printed as <0.001 (upper bound),log transaction price (Euro),log,spatial_error,97.0,,p,Venissieux submarket; spatial_error model with TTBellecour by public transport; R2 (adj. for OLS) 0.87-0.89; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.947,0.2877958689521537,b (log-log),|b/z(p)| (two-sided normal),-0.33268620942909904,0.10110424153225529,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,87.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,True
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-VEN-6,Appendix 3,spatial_error / Venissieux / TTCityHall by public transport,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by public transport to Lyon City Hall),-1.162,,,0.001,,,,high,TTCityHall by public transport; submarket model; p printed as <0.001 (upper bound),log transaction price (Euro),log,spatial_error,97.0,,p,Venissieux submarket; spatial_error model with TTCityHall by public transport; R2 (adj. for OLS) 0.87-0.89; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-1.162,0.35313495218838714,b (log-log),|b/z(p)| (two-sided normal),-0.33268620942909904,0.10110424153225529,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,87.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,True
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-VEV-1,Appendix 3,OLS / Vaulx-en-Velin / TTBellecour by car,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by car to Bellecour),1.97,,,0.19,,,,high,TTBellecour by car; submarket model,log transaction price (Euro),log,OLS,54.0,,p,Vaulx-en-Velin submarket; OLS model with TTBellecour by car; R2 (adj. for OLS) 0.66-0.68; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,1.97,1.503152294821007,b (log-log),|b/z(p)| (two-sided normal),0.19383020119324726,0.14789660493870413,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3105791121681283,44.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,True
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-VEV-2,Appendix 3,OLS / Vaulx-en-Velin / TTCityHall by car,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by car to Lyon City Hall),0.016,,,0.99,,,,high,TTCityHall by car; submarket model,log transaction price (Euro),log,OLS,54.0,,p,Vaulx-en-Velin submarket; OLS model with TTCityHall by car; R2 (adj. for OLS) 0.66-0.68; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.016,1.2765818746117272,b (log-log),|b/z(p)| (two-sided normal),0.0018894882488989502,0.1507554031772657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.012533469508069278,44.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-VEV-5,Appendix 3,OLS / Vaulx-en-Velin / TTBellecour by public transport,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by public transport to Bellecour),0.559,,,0.54,,,,high,TTBellecour by public transport; submarket model,log transaction price (Euro),log,OLS,54.0,,p,Vaulx-en-Velin submarket; OLS model with TTBellecour by public transport; R2 (adj. for OLS) 0.66-0.68; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.559,0.912186928466784,b (log-log),|b/z(p)| (two-sided normal),0.09199328745630209,0.15011641202920592,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6128129910166272,44.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-OLS-VEV-6,Appendix 3,OLS / Vaulx-en-Velin / TTCityHall by public transport,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by public transport to Lyon City Hall),-0.355,,,0.67,,,,high,TTCityHall by public transport; submarket model,log transaction price (Euro),log,OLS,54.0,,p,Vaulx-en-Velin submarket; OLS model with TTCityHall by public transport; R2 (adj. for OLS) 0.66-0.68; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.355,0.8330439036857408,b (log-log),|b/z(p)| (two-sided normal),-0.06411206012604123,0.1504455234950206,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4261480078412781,44.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,ols,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-VEV-1,Appendix 3,spatial_error / Vaulx-en-Velin / TTBellecour by car,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by car to Bellecour),0.147,,,0.94,,,,high,TTBellecour by car; submarket model,log transaction price (Euro),log,spatial_error,54.0,,p,Vaulx-en-Velin submarket; spatial_error model with TTBellecour by car; R2 (adj. for OLS) 0.84; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.147,1.9529728884720807,b (log-log),|b/z(p)| (two-sided normal),0.01134662817708404,0.15074596738379942,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0752698620998299,44.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-VEV-2,Appendix 3,spatial_error / Vaulx-en-Velin / TTCityHall by car,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by car to Lyon City Hall),-0.562,,,0.65,,,,high,TTCityHall by car; submarket model,log transaction price (Euro),log,spatial_error,54.0,,p,Vaulx-en-Velin submarket; spatial_error model with TTCityHall by car; R2 (adj. for OLS) 0.84; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,-0.562,1.2385342194103888,b (log-log),|b/z(p)| (two-sided normal),-0.06824772614960625,0.150404171233517,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.45376219016987945,44.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-VEV-5,Appendix 3,spatial_error / Vaulx-en-Velin / TTBellecour by public transport,15,TTBellecour,cbd_distance,D_location,log,minutes (travel time by public transport to Bellecour),0.685,,,0.5,,,,high,TTBellecour by public transport; submarket model,log transaction price (Euro),log,spatial_error,54.0,,p,Vaulx-en-Velin submarket; spatial_error model with TTBellecour by public transport; R2 (adj. for OLS) 0.84; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.685,1.0155825196763375,b (log-log),|b/z(p)| (two-sided normal),0.10116152265797279,0.1499822979201152,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6744897501960816,44.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,True
0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4,0f2b62072edfd32a439d1606541bbbb8547810e4:A3-SE-VEV-6,Appendix 3,spatial_error / Vaulx-en-Velin / TTCityHall by public transport,15,TTCityHall,cbd_distance,D_location,log,minutes (travel time by public transport to Lyon City Hall),0.499,,,0.57,,,,high,TTCityHall by public transport; submarket model,log transaction price (Euro),log,spatial_error,54.0,,p,Vaulx-en-Velin submarket; spatial_error model with TTCityHall by public transport; R2 (adj. for OLS) 0.84; submarket models exclude construction-period and some structural dummies; n printed for OLS rows only,elasticity,0.499,0.8784414819063171,b (log-log),|b/z(p)| (two-sided normal),0.08532468452758538,0.15020589643206633,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5680514983389829,44.0,minutes,,2014.0,France,Europe,High income,1997.0,2008.0,condo_apartment,transaction,journal,True,True,unknown,,2002.5,spatial,journal,True,True,False
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T3-c1,3,1,11,Distance,transit_distance,D_location,level,miles,0.028,0.007,,,***,,,high,"Euclidean distance (miles) to nearest Metro station in sales year; quadratic with Distance squared; stars: *** p<0.001, ** p<0.01, * p<0.05, + p<0.10 (non-standard legend)","ln(sales price), 2000 dollars",log,OLS,57912.0,,se,"full sample hedonic; ZIP code FE, year-quarter FE, ZIP linear trends; SE clustered at ZIP",semi_elasticity,1.7398393382645352,0.4349598345661338,100*b/1.60934 (X per miles->km),reported,0.016620849347518573,0.004155212336879643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,57902.0,miles,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,ols,journal,True,True,False
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T3-c1,3,1,11,Age,age,A_structural,level,years,-0.001,0.001,,,,,,high,age of home; with Age squared,"ln(sales price), 2000 dollars",log,OLS,57912.0,,se,"full sample hedonic; ZIP code FE, year-quarter FE, ZIP linear trends; SE clustered at ZIP",semi_elasticity,-0.1,0.1,100*b/1 (per year),reported,-0.004155750514081046,0.004155750514081046,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,57902.0,years,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,ols,journal,True,True,False
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T3-c1,3,1,11,Structural area (ln),living_area,A_structural,log,sqft,0.411,0.019,,,***,,,high,log structural area in sq ft,"ln(sales price), 2000 dollars",log,OLS,57912.0,,se,"full sample hedonic; ZIP code FE, year-quarter FE, ZIP linear trends; SE clustered at ZIP",elasticity,0.411,0.019,b (log-log),reported,0.08953516793185722,0.004139095354514081,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.63157894736842,57902.0,sqft,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,ols,journal,True,True,False
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T3-c1,3,1,11,Basement,basement,A_structural,binary,binary,0.161,0.01,,,***,,,high,,"ln(sales price), 2000 dollars",log,OLS,57912.0,,se,"full sample hedonic; ZIP code FE, year-quarter FE, ZIP linear trends; SE clustered at ZIP",pct_premium,17.462623603376272,1.1746849688138716,100*(exp(b - se^2/2) - 1),reported,0.06675889805818996,0.004146515407340992,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.1,57902.0,binary,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,ols,journal,True,True,True
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T3-c1,3,1,11,Below average,condition,A_structural,binary,binary,-0.109,0.017,,,***,,,high,1 = below average condition,"ln(sales price), 2000 dollars",log,OLS,57912.0,,se,"full sample hedonic; ZIP code FE, year-quarter FE, ZIP linear trends; SE clustered at ZIP",pct_premium,-10.339915068556627,1.5244417097470002,100*(exp(b - se^2/2) - 1),reported,-0.02663647022508242,0.004154311869966983,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.411764705882352,57902.0,binary,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,ols,journal,True,True,False
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T3-c1,3,1,11,Split level,dwelling_type,A_structural,binary,binary,0.06,0.012,,,***,,,high,1 = split-level house,"ln(sales price), 2000 dollars",log,OLS,57912.0,,se,"full sample hedonic; ZIP code FE, year-quarter FE, ZIP linear trends; SE clustered at ZIP",pct_premium,6.176009706622265,1.2742038558544315,100*(exp(b - se^2/2) - 1),reported,0.020774447654510805,0.004154889530902161,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,57902.0,binary,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,ols,journal,True,True,False
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T3-c2,3,2,11,Distance,transit_distance,D_location,level,miles,0.05,0.011,,,***,,,high,"Euclidean distance (miles) to nearest Metro station in sales year; quadratic with Distance squared; repeat sales with house FE; stars: *** p<0.001, ** p<0.01, * p<0.05, + p<0.10 (non-standard legend)","ln(sales price), 2000 dollars",log,FE_panel,16511.0,,se,"repeat-sales sample with house FE, time FE, ZIP linear trends",semi_elasticity,3.1068559611866697,0.6835083114610673,100*b/1.60934 (X per miles->km),reported,0.03536311095699128,0.007779884410538081,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.545454545454546,16501.0,miles,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,panel,journal,True,True,False
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T4-c2,4,2,14,Distance,transit_distance,D_location,level,miles,0.044,0.01,,,***,,,high,"Euclidean distance (miles) to nearest Metro station in sales year; quadratic with Distance squared; properties built before 1990; stars: *** p<0.001, ** p<0.01, * p<0.05, + p<0.10 (non-standard legend)","ln(sales price), 2000 dollars",log,FE_panel,11243.0,,se,repeat-sales robustness: properties built before 1990; robust SE,semi_elasticity,2.734033245844269,0.621371192237334,100*b/1.60934 (X per miles->km),reported,0.04147924734559151,0.009427101669452617,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.3999999999999995,11233.0,miles,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,panel,journal,True,True,False
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T4-c3,4,3,14,Distance,transit_distance,D_location,level,miles,0.058,0.031,,,+,,,high,"Euclidean distance (miles) to nearest Metro station in sales year; quadratic with Distance squared; properties < 5 miles from station; stars: *** p<0.001, ** p<0.01, * p<0.05, + p<0.10 (non-standard legend)","ln(sales price), 2000 dollars",log,FE_panel,8956.0,,se,repeat-sales robustness: properties < 5 miles from station; robust SE,semi_elasticity,3.6039529149765372,1.9262506959357353,100*b/1.60934 (X per miles->km),reported,0.01977729542593132,0.010570623417308118,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.870967741935484,8946.0,miles,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,panel,journal,True,True,False
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T4-c4,4,4,14,Distance,transit_distance,D_location,level,miles,0.078,0.021,,,***,,,high,"Euclidean distance (miles) to nearest Metro station in sales year; quadratic with Distance squared; properties < 7 miles; stars: *** p<0.001, ** p<0.01, * p<0.05, + p<0.10 (non-standard legend)","ln(sales price), 2000 dollars",log,FE_panel,12132.0,,se,repeat-sales robustness: properties < 7 miles; robust SE,semi_elasticity,4.846695299451205,1.3048795036984013,100*b/1.60934 (X per miles->km),reported,0.03371639830561187,0.00907749185151089,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.714285714285714,12122.0,miles,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,panel,journal,True,True,False
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T4-c5,4,5,14,Distance,transit_distance,D_location,level,miles,0.062,0.012,,,***,,,high,"Euclidean distance (miles) to nearest Metro station in sales year; quadratic with Distance squared; properties < 10 miles; stars: *** p<0.001, ** p<0.01, * p<0.05, + p<0.10 (non-standard legend)","ln(sales price), 2000 dollars",log,FE_panel,15980.0,,se,repeat-sales robustness: properties < 10 miles; robust SE,semi_elasticity,3.8525013918714706,0.7456454306848007,100*b/1.60934 (X per miles->km),reported,0.04085030644173168,0.007906510924206132,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.166666666666667,15970.0,miles,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,panel,journal,True,True,False
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T4-c6,4,6,14,Distance,transit_distance,D_location,level,miles,0.042,0.007,,,***,,,high,"Euclidean distance (miles) to nearest Metro station in sales year; quadratic with Distance squared; all repeat sales 1994-2011 (extended window); stars: *** p<0.001, ** p<0.01, * p<0.05, + p<0.10 (non-standard legend)","ln(sales price), 2000 dollars",log,FE_panel,32231.0,,se,repeat-sales robustness: all repeat sales 1994-2011 (extended window); robust SE,semi_elasticity,2.6097590073968027,0.4349598345661338,100*b/1.60934 (X per miles->km),reported,0.033407137399294844,0.005567856233215807,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,32221.0,miles,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,panel,journal,True,True,False
0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b,0f88c3ee1b9c25f3d6602c7c07d55400a39f254b:T4-c7,4,7,14,Distance,transit_distance,D_location,level,miles,0.019,0.012,,,,,,medium,"Euclidean distance (miles) to nearest Metro station in sales year; quadratic with Distance squared; placebo-type: treatment date = construction groundbreaking, 1994-2011 sample; stars: *** p<0.001, ** p<0.01, * p<0.05, + p<0.10 (non-standard legend)","ln(sales price), 2000 dollars",log,FE_panel,32231.0,,se,"repeat-sales robustness: placebo-type: treatment date = construction groundbreaking, 1994-2011 sample; robust SE",semi_elasticity,1.1806052652509345,0.7456454306848007,100*b/1.60934 (X per miles->km),reported,0.00882035272838947,0.0055707490916144025,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5833333333333333,32221.0,miles,,2023.0,United States,North America,High income,1998.0,2007.0,single_family,transaction,journal,True,True,clustered,,2002.5,panel,journal,True,True,False
1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd:T2-c1,2,1,9,Building Type,dwelling_type,A_structural,binary,binary,-0.473,0.022,-21.673,0.0,,,,high,"1 = apartment, reference = villa (text p.5/9)",ln(listing price),log,OLS,2097.0,0.8178,se,"Full sample of apartments and villas; district dummies (reference East Riyadh); N and R2 taken from Table 3 training results (70% split), Table 2 itself does not print N",pct_premium,-37.70207080545441,1.3708861565908472,100*(exp(b - se^2/2) - 1),reported,-0.4286250389482461,0.019776913161456477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.673,2087.0,binary,,2025.0,Saudi Arabia,Asia,High income,2024.0,2024.0,mixed,listing,journal,False,True,OLS,ANN;random_forest,2024.0,ols,journal,True,True,False
1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd:T2-c1,2,1,9,Bed Room,bedrooms,A_structural,level,count,0.012,0.004,2.837,0.005,,,,high,,ln(listing price),log,OLS,2097.0,0.8178,se,"Full sample of apartments and villas; district dummies (reference East Riyadh); N and R2 taken from Table 3 training results (70% split), Table 2 itself does not print N",semi_elasticity,1.2,0.4,100*b/1 (per unit count),reported,0.061981529360413457,0.021847560578221167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.837,2087.0,count,,2025.0,Saudi Arabia,Asia,High income,2024.0,2024.0,mixed,listing,journal,False,True,OLS,ANN;random_forest,2024.0,ols,journal,True,True,False
1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd:T2-c1,2,1,9,Bathroom,bathrooms,A_structural,level,count,0.03,0.006,5.007,0.0,,,,high,,ln(listing price),log,OLS,2097.0,0.8178,se,"Full sample of apartments and villas; district dummies (reference East Riyadh); N and R2 taken from Table 3 training results (70% split), Table 2 itself does not print N",semi_elasticity,3.0,0.6,100*b/1 (per unit count),reported,0.10894904617211154,0.021759346149812574,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.007,2087.0,count,,2025.0,Saudi Arabia,Asia,High income,2024.0,2024.0,mixed,listing,journal,False,True,OLS,ANN;random_forest,2024.0,ols,journal,True,True,False
1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd:T2-c1,2,1,9,Size,living_area,A_structural,level,m2,0.002,,27.336,0.0,,,,high,"Size in square metres (Table 1: Size (m2), 56-930). Std. Error printed as '0' (rounded to 3 decimals) -> not recorded; t = 27.336 printed",ln(listing price),log,OLS,2097.0,0.8178,se,"Full sample of apartments and villas; district dummies (reference East Riyadh); N and R2 taken from Table 3 training results (70% split), Table 2 itself does not print N",semi_elasticity,0.2,0.0073163593795727245,100*b/1 (X per m2->m2),|b/t|,0.5134703372103845,0.01878366758890783,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.336,2087.0,m2,,2025.0,Saudi Arabia,Asia,High income,2024.0,2024.0,mixed,listing,journal,False,True,OLS,ANN;random_forest,2024.0,ols,journal,True,True,False
1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd:T2-c1,2,1,9,Floor,floor_level,A_structural,level,count,-0.022,0.006,-3.599,0.0,,,,high,floor number 0-10,ln(listing price),log,OLS,2097.0,0.8178,se,"Full sample of apartments and villas; district dummies (reference East Riyadh); N and R2 taken from Table 3 training results (70% split), Table 2 itself does not print N",semi_elasticity,-2.1999999999999997,0.6,100*b/1 (per unit count),reported,-0.07853750129411285,0.021822034257880756,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.599,2087.0,count,,2025.0,Saudi Arabia,Asia,High income,2024.0,2024.0,mixed,listing,journal,False,True,OLS,ANN;random_forest,2024.0,ols,journal,True,True,False
1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd:T2-c1,2,1,9,Age,age,A_structural,level,years,-0.007,0.001,-5.051,0.0,,,,high,"age in years (Table 1: Age (years), 0-20)",ln(listing price),log,OLS,2097.0,0.8178,se,"Full sample of apartments and villas; district dummies (reference East Riyadh); N and R2 taken from Table 3 training results (70% split), Table 2 itself does not print N",semi_elasticity,-0.7000000000000001,0.1,100*b/1 (per year),reported,-0.10989494460269605,0.021757066838783617,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.051,2087.0,years,,2025.0,Saudi Arabia,Asia,High income,2024.0,2024.0,mixed,listing,journal,False,True,OLS,ANN;random_forest,2024.0,ols,journal,True,True,False
1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd,1076844f99e9f35c7768a4e64f2c167ab26b5afd:T2-c1,2,1,9,Elevator,accessibility,B_interior,binary,binary,0.065,0.011,5.861,0.0,,,,high,presence of elevator (dummy),ln(listing price),log,OLS,2097.0,0.8178,se,"Full sample of apartments and villas; district dummies (reference East Riyadh); N and R2 taken from Table 3 training results (70% split), Table 2 itself does not print N",pct_premium,6.7094463216212485,1.1738749268226119,100*(exp(b - se^2/2) - 1),reported,0.12725223592446358,0.0217116935547626,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.861,2087.0,binary,,2025.0,Saudi Arabia,Asia,High income,2024.0,2024.0,mixed,listing,journal,False,True,OLS,ANN;random_forest,2024.0,ols,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c2,2,2,10,Living Area (m2),living_area,A_structural,level,m2,0.005,0.0001,,,***,,,high,,Log(selling price),log,OLS,98269.0,0.335,se,"DiD + basic characteristics, no FE; treatment < 20 km",semi_elasticity,0.5,0.01,100*b/1 (X per m2->m2),reported,0.15751723510049742,0.0031503447020099482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),50.0,98259.0,m2,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,ols,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c2,2,2,10,Age,age,A_structural,level,years,-0.004,0.0001,,,***,,,high,Quadratic in age (Age2 also included),Log(selling price),log,OLS,98269.0,0.335,se,"DiD + basic characteristics, no FE; treatment < 20 km",semi_elasticity,-0.4,0.01,100*b/1 (per year),reported,-0.12658037705155908,0.003164509426288977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-40.0,98259.0,years,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,ols,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c2,2,2,10,Number of rooms,bedrooms,A_structural,level,count,0.076,0.002,,,***,,,high,"Total number of rooms, not bedrooms",Log(selling price),log,OLS,98269.0,0.335,se,"DiD + basic characteristics, no FE; treatment < 20 km",semi_elasticity,7.6,0.2,100*b/1 (per unit count),reported,0.12034539689254041,0.003166984128751063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),38.0,98259.0,count,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,ols,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c3,2,3,10,Living Area (m2),living_area,A_structural,level,m2,0.005,0.0001,,,***,,,high,,Log(selling price),log,spatial_lag,98269.0,0.682,se,+ spatial price lag W(Price); no FE; treatment < 20 km,semi_elasticity,0.5,0.01,100*b/1 (X per m2->m2),reported,0.15751723510049742,0.0031503447020099482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),50.0,98259.0,m2,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,spatial,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c3,2,3,10,Age,age,A_structural,level,years,-0.0003,0.0001,,,***,,,high,Quadratic in age (Age2 also included),Log(selling price),log,spatial_lag,98269.0,0.682,se,+ spatial price lag W(Price); no FE; treatment < 20 km,semi_elasticity,-0.03,0.01,100*b/1 (per year),reported,-0.009570071800690036,0.003190023933563346,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.9999999999999996,98259.0,years,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,spatial,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c3,2,3,10,Number of rooms,bedrooms,A_structural,level,count,0.05,0.002,,,***,,,high,"Total number of rooms, not bedrooms",Log(selling price),log,spatial_lag,98269.0,0.682,se,+ spatial price lag W(Price); no FE; treatment < 20 km,semi_elasticity,5.0,0.2,100*b/1 (per unit count),reported,0.07950180623795465,0.003180072249518186,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.0,98259.0,count,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,spatial,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c4,2,4,10,Living Area (m2),living_area,A_structural,level,m2,0.005,0.0001,,,***,,,high,,Log(selling price),log,spatial_lag,98269.0,0.694,se,+ distances; no FE; treatment < 20 km,semi_elasticity,0.5,0.01,100*b/1 (X per m2->m2),reported,0.15751723510049742,0.0031503447020099482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),50.0,98259.0,m2,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,spatial,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c4,2,4,10,Age,age,A_structural,level,years,-0.0004,0.0001,,,***,,,high,Quadratic in age (Age2 also included),Log(selling price),log,spatial_lag,98269.0,0.694,se,+ distances; no FE; treatment < 20 km,semi_elasticity,-0.04,0.01,100*b/1 (per year),reported,-0.012759641283677221,0.003189910320919305,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,98259.0,years,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,spatial,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c4,2,4,10,Number of rooms,bedrooms,A_structural,level,count,0.052,0.002,,,***,,,high,"Total number of rooms, not bedrooms",Log(selling price),log,spatial_lag,98269.0,0.694,se,+ distances; no FE; treatment < 20 km,semi_elasticity,5.2,0.2,100*b/1 (per unit count),reported,0.08266056490092927,0.0031792524961895873,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.0,98259.0,count,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,spatial,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c5,2,5,10,Living Area (m2),living_area,A_structural,level,m2,0.005,5e-05,,,***,,,high,,Log(selling price),log,spatial_lag,98269.0,0.829,se,full model with month FE and postal code FE; treatment < 20 km,semi_elasticity,0.5,0.005,100*b/1 (X per m2->m2),reported,0.30392609804812076,0.0030392609804812077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),100.0,98259.0,m2,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,spatial,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c5,2,5,10,Age,age,A_structural,level,years,-0.002,5e-05,,,***,,,high,Quadratic in age (Age2 also included),Log(selling price),log,spatial_lag,98269.0,0.829,se,full model with month FE and postal code FE; treatment < 20 km,semi_elasticity,-0.2,0.005,100*b/1 (per year),reported,-0.12658037705155908,0.003164509426288977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-40.0,98259.0,years,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,spatial,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c5,2,5,10,Number of rooms,bedrooms,A_structural,level,count,0.06,0.001,,,***,,,high,"Total number of rooms, not bedrooms",Log(selling price),log,spatial_lag,98269.0,0.829,se,full model with month FE and postal code FE; treatment < 20 km,semi_elasticity,6.0,0.1,100*b/1 (per unit count),reported,0.18799727155273147,0.003133287859212191,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),60.0,98259.0,count,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,spatial,journal,True,True,False
11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5,11135c13b52c3fe849cfd9899af8e92968906ec5:T2-c5,2,5,10,Distance forest,green_space,E_environment,level,m,2e-05,1e-05,,,***,,,medium,Distance to closest forest in meters,Log(selling price),log,spatial_lag,98269.0,0.829,se,full model with month FE and postal code FE; treatment < 20 km,semi_elasticity,2.0,1.0,100*b/0.001 (X per m->km),reported,0.006380210185769235,0.003190105092884617,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,98259.0,m,,2026.0,Sweden,Europe,High income,2012.0,2016.0,mixed,transaction,journal,True,True,OLS,,2014.0,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c1,3,1,8,LN_ACRE,lot_size,A_structural,log,acres,0.0982,,13.83,,*,,,high,Natural log of parcel size in acres,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,1676.0,0.7549,t,"Calvert County, OLS; adjusted R2",elasticity,0.0982,0.007100506146059291,b (log-log),|b/t|,0.32091113522581693,0.023203986639610766,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.83,1666.0,acre,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c1,3,1,8,LN_AGE,age,A_structural,log,years,-0.0226,,-5.31,,*,,,high,Natural log of age of structure in years,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,1676.0,0.7549,t,"Calvert County, OLS; adjusted R2",elasticity,-0.0226,0.0042561205273069684,b (log-log),|b/t|,-0.12900682361774457,0.02429507036115717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.31,1666.0,years,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c1,3,1,8,LN_SQFT,living_area,A_structural,log,sqft,0.3894,,20.46,,*,,,high,Natural log of structure size in square feet,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,1676.0,0.7549,t,"Calvert County, OLS; adjusted R2",elasticity,0.3894,0.01903225806451613,b (log-log),|b/t|,0.4481186865003056,0.021902184090924027,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.46,1666.0,sqft,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c1,3,1,8,AVERAGE,condition,A_structural,dummy,binary,0.2106,,13.88,,*,,,high,Assessor quality grade average (omitted category: fair),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,1676.0,0.7549,t,"Calvert County, OLS; adjusted R2",pct_premium,23.427640488172095,1.872972145260582,100*(exp(b - se^2/2) - 1),|b/t|,0.32195127107974847,0.023195336533123084,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.88,1666.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c1,3,1,8,GOOD_VGOOD,condition,A_structural,dummy,binary,0.4859,,12.29,,*,,,high,Assessor quality grade good or very good (omitted: fair),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,1676.0,0.7549,t,"Calvert County, OLS; adjusted R2",pct_premium,62.436739421167275,6.427153982807359,100*(exp(b - se^2/2) - 1),|b/t|,0.2883162687888979,0.023459419754995756,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.29,1666.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c1,3,1,8,NUSTORY,storeys,A_structural,level,count,0.079,,5.99,,*,,,high,Number of stories,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,1676.0,0.7549,t,"Calvert County, OLS; adjusted R2",semi_elasticity,7.9,1.318864774624374,100*b/1 (per unit count),|b/t|,0.14519857104440848,0.02424016211091961,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.99,1666.0,count,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c1,3,1,8,BASEMENT,basement,A_structural,binary,binary,-0.0126,,-1.12,,,,,high,,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,1676.0,0.7549,t,"Calvert County, OLS; adjusted R2",pct_premium,-1.2583439279781339,1.110913928608001,100*(exp(b - se^2/2) - 1),|b/t|,-0.027429449184989674,0.024490579629455066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.12,1666.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c1,3,1,8,FRAME,roof_materials,A_structural,binary,binary,-0.0052,,-0.22,,,,,high,Framed structure (omitted: all other construction types),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,1676.0,0.7549,t,"Calvert County, OLS; adjusted R2",pct_premium,-0.5464354646219527,2.351377355589994,100*(exp(b - se^2/2) - 1),|b/t|,-0.0053898772412844225,0.02449944200583828,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.22,1666.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c1,3,1,8,ALUM,roof_materials,A_structural,binary,binary,-0.0422,,-1.82,,,,,high,Aluminum-sided structure (omitted: all other construction types),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,1676.0,0.7549,t,"Calvert County, OLS; adjusted R2",pct_premium,-4.15796457944646,2.2228688290353276,100*(exp(b - se^2/2) - 1),|b/t|,-0.04454537078742743,0.024475478454630457,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.82,1666.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c1,3,1,8,LN_POPDEN,density,F_neighbourhood,log,households per sq mile,-0.0396,,-3.67,,*,,,high,Natural log of census tract/block-group population density (households per square mile),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,1676.0,0.7549,t,"Calvert County, OLS; adjusted R2",elasticity,-0.0396,0.010790190735694824,b (log-log),|b/t|,-0.08955298804763184,0.0244013591410441,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.67,1666.0,households per sq mile,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c1,3,1,8,LN_CITYDIST,cbd_distance,D_location,log,km,-0.1669,,-4.27,,*,,,high,"Natural log of Euclidean distance to nearest of Washington DC or Baltimore; printed in units of 100 km (log, so scale does not affect the elasticity)","LN_PRICE (natural log of full transaction price, USD)",log,OLS,1676.0,0.7549,t,"Calvert County, OLS; adjusted R2",elasticity,-0.1669,0.03908665105386417,b (log-log),|b/t|,-0.1040463385378416,0.024366824013546045,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.27,1666.0,km,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c2,3,2,8,LN_ACRE,lot_size,A_structural,log,acres,0.1002,,12.87,,*,,,high,Natural log of parcel size in acres,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,1676.0,0.7785,t,"Calvert County, spatial error model (lambda 0.4067); adjusted R2",elasticity,0.1002,0.007785547785547786,b (log-log),|b/t|,0.3007176056420591,0.02336578132416932,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.87,1666.0,acre,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c2,3,2,8,LN_AGE,age,A_structural,log,years,-0.0287,,-6.28,,*,,,high,Natural log of age of structure in years,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,1676.0,0.7785,t,"Calvert County, spatial error model (lambda 0.4067); adjusted R2",elasticity,-0.0287,0.004570063694267516,b (log-log),|b/t|,-0.15206932738475204,0.024214861048527395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.28,1666.0,years,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c2,3,2,8,LN_SQFT,living_area,A_structural,log,sqft,0.3765,,19.49,,*,,,high,Natural log of structure size in square feet,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,1676.0,0.7785,t,"Calvert County, spatial error model (lambda 0.4067); adjusted R2",elasticity,0.3765,0.019317598768599283,b (log-log),|b/t|,0.43089739929096815,0.022108640291994268,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.49,1666.0,sqft,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c2,3,2,8,AVERAGE,condition,A_structural,dummy,binary,0.202,,12.94,,*,,,high,Assessor quality grade average (omitted category: fair),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,1676.0,0.7785,t,"Calvert County, spatial error model (lambda 0.4067); adjusted R2",pct_premium,22.36988986442603,1.910489162584964,100*(exp(b - se^2/2) - 1),|b/t|,0.302204202155599,0.023354266008933467,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.94,1666.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c2,3,2,8,GOOD_VGOOD,condition,A_structural,dummy,binary,0.4699,,11.56,,*,,,high,Assessor quality grade good or very good (omitted: fair),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,1676.0,0.7785,t,"Calvert County, spatial error model (lambda 0.4067); adjusted R2",pct_premium,59.85130253689541,6.503132278760893,100*(exp(b - se^2/2) - 1),|b/t|,0.2724995488272578,0.023572625331077665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.56,1666.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c2,3,2,8,NUSTORY,storeys,A_structural,level,count,0.0655,,5.14,,*,,,high,Number of stories,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,1676.0,0.7785,t,"Calvert County, spatial error model (lambda 0.4067); adjusted R2",semi_elasticity,6.550000000000001,1.27431906614786,100*b/1 (per unit count),|b/t|,0.12494218477005789,0.024307818048649395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.14,1666.0,count,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c2,3,2,8,BASEMENT,basement,A_structural,binary,binary,-0.0008,,-0.07,,,,,high,,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,1676.0,0.7785,t,"Calvert County, spatial error model (lambda 0.4067); adjusted R2",pct_premium,-0.0864931853066464,1.1419432227596387,100*(exp(b - se^2/2) - 1),|b/t|,-0.0017149833293926351,0.024499761848466212,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.07,1666.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c2,3,2,8,FRAME,roof_materials,A_structural,binary,binary,-0.0311,,-1.36,,,,,high,Framed structure (omitted: all other construction types),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,1676.0,0.7785,t,"Calvert County, spatial error model (lambda 0.4067); adjusted R2",pct_premium,-3.0874794737354883,2.216740838557395,100*(exp(b - se^2/2) - 1),|b/t|,-0.03330124465238143,0.024486209303221637,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.36,1666.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c2,3,2,8,ALUM,roof_materials,A_structural,binary,binary,-0.0464,,-2.07,,,,,high,Aluminum-sided structure (omitted: all other construction types); no star printed despite |t| > 1.96 (as printed),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,1676.0,0.7785,t,"Calvert County, spatial error model (lambda 0.4067); adjusted R2",pct_premium,-4.557978387716865,2.1399142517620304,100*(exp(b - se^2/2) - 1),|b/t|,-0.05064948898121878,0.02446835216483999,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.07,1666.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c2,3,2,8,LN_POPDEN,density,F_neighbourhood,log,households per sq mile,-0.0393,,-2.85,,*,,,high,Natural log of census tract/block-group population density (households per square mile),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,1676.0,0.7785,t,"Calvert County, spatial error model (lambda 0.4067); adjusted R2",elasticity,-0.0393,0.013789473684210527,b (log-log),|b/t|,-0.06965483108056955,0.02444029160721739,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.85,1666.0,households per sq mile,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T3-c2,3,2,8,LN_CITYDIST,cbd_distance,D_location,log,km,-0.1432,,-2.59,,*,,,high,"Natural log of Euclidean distance to nearest of Washington DC or Baltimore; printed in units of 100 km (log, so scale does not affect the elasticity)","LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,1676.0,0.7785,t,"Calvert County, spatial error model (lambda 0.4067); adjusted R2",elasticity,-0.1432,0.05528957528957529,b (log-log),|b/t|,-0.06332711220371977,0.024450622472478672,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.59,1666.0,km,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c1,4,1,8,LN_ACRE,lot_size,A_structural,log,acres,0.1334,,31.68,,*,,,high,Natural log of parcel size in acres,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,3133.0,0.7394,t,"Carroll County, OLS; adjusted R2",elasticity,0.1334,0.004210858585858585,b (log-log),|b/t|,0.4931599584073992,0.01556691787902144,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),31.68,3123.0,acre,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c1,4,1,8,LN_AGE,age,A_structural,log,years,-0.0641,,-21.8,,*,,,high,Natural log of age of structure in years,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,3133.0,0.7394,t,"Carroll County, OLS; adjusted R2",elasticity,-0.0641,0.0029403669724770644,b (log-log),|b/t|,-0.36342218072685334,0.01667074223517676,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.8,3123.0,years,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c1,4,1,8,LN_SQFT,living_area,A_structural,log,sqft,0.2692,,24.29,,*,,,high,Natural log of structure size in square feet,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,3133.0,0.7394,t,"Carroll County, OLS; adjusted R2",elasticity,0.2692,0.011082750102923014,b (log-log),|b/t|,0.3986252461364907,0.016411084649505588,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.29,3123.0,sqft,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c1,4,1,8,AVERAGE,condition,A_structural,dummy,binary,0.1546,,17.51,,*,,,high,Assessor quality grade average (omitted category: fair),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,3133.0,0.7394,t,"Carroll County, OLS; adjusted R2",pct_premium,16.714549773662423,1.0305409894814728,100*(exp(b - se^2/2) - 1),|b/t|,0.2989953295573191,0.017075689866208967,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.51,3123.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c1,4,1,8,GOOD_VGOOD,condition,A_structural,dummy,binary,0.4036,,17.17,,*,,,high,Assessor quality grade good or very good (omitted: fair),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,3133.0,0.7394,t,"Carroll County, OLS; adjusted R2",pct_premium,49.67913714123302,3.5193472095384637,100*(exp(b - se^2/2) - 1),|b/t|,0.29369490128746456,0.017105119469275745,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.17,3123.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c1,4,1,8,NUSTORY,storeys,A_structural,level,count,-0.0212,,-2.52,,,,,high,Number of stories; no star printed despite |t| > 1.96 (as printed),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,3133.0,0.7394,t,"Carroll County, OLS; adjusted R2",semi_elasticity,-2.12,0.8412698412698414,100*b/1 (per unit count),|b/t|,-0.04504778519019629,0.017876105234204874,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.52,3123.0,count,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c1,4,1,8,BASEMENT,basement,A_structural,binary,binary,0.1324,,8.74,,*,,,high,,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,3133.0,0.7394,t,"Carroll County, OLS; adjusted R2",pct_premium,14.143387576658363,1.7293270784416628,100*(exp(b - se^2/2) - 1),|b/t|,0.1545176178012709,0.017679361304493237,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.74,3123.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c1,4,1,8,FRAME,roof_materials,A_structural,binary,binary,-0.0528,,-4.05,,*,,,high,Framed structure (omitted: all other construction types),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,3133.0,0.7394,t,"Carroll County, OLS; adjusted R2",pct_premium,-5.151090063079156,1.2366538408284746,100*(exp(b - se^2/2) - 1),|b/t|,-0.07228222678528726,0.017847463403774633,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.05,3123.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c1,4,1,8,ALUM,roof_materials,A_structural,binary,binary,-0.0015,,-0.16,,,,,high,Aluminum-sided structure (omitted: all other construction types),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,3133.0,0.7394,t,"Carroll County, OLS; adjusted R2",pct_premium,-0.15427540421003583,0.9360948041603538,100*(exp(b - se^2/2) - 1),|b/t|,-0.0028630716098793246,0.01789419756174578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.16,3123.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c1,4,1,8,LN_POPDEN,density,F_neighbourhood,log,households per sq mile,0.0286,,4.75,,*,,,high,Natural log of census tract/block-group population density (households per square mile),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,3133.0,0.7394,t,"Carroll County, OLS; adjusted R2",elasticity,0.0286,0.006021052631578948,b (log-log),|b/t|,0.08469240200009637,0.017829979368441343,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.75,3123.0,households per sq mile,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c1,4,1,8,LN_CITYDIST,cbd_distance,D_location,log,km,-0.1581,,-6.45,,*,,,high,"Natural log of Euclidean distance to nearest of Washington DC or Baltimore; printed in units of 100 km (log, so scale does not affect the elasticity)","LN_PRICE (natural log of full transaction price, USD)",log,OLS,3133.0,0.7394,t,"Carroll County, OLS; adjusted R2",elasticity,-0.1581,0.02451162790697674,b (log-log),|b/t|,-0.11465688303006547,0.01777626093489387,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.45,3123.0,km,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c2,4,2,8,LN_ACRE,lot_size,A_structural,log,acres,0.1338,,31.06,,*,,,high,Natural log of parcel size in acres,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,3133.0,0.7458,t,"Carroll County, spatial error model (lambda 0.2149); adjusted R2",elasticity,0.1338,0.004307791371538957,b (log-log),|b/t|,0.4858035568453203,0.01564080994350677,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),31.06,3123.0,acre,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c2,4,2,8,LN_AGE,age,A_structural,log,years,-0.061,,-20.15,,*,,,high,Natural log of age of structure in years,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,3133.0,0.7458,t,"Carroll County, spatial error model (lambda 0.2149); adjusted R2",elasticity,-0.061,0.0030272952853598015,b (log-log),|b/t|,-0.33919374648425427,0.016833436550087063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-20.15,3123.0,years,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c2,4,2,8,LN_SQFT,living_area,A_structural,log,sqft,0.2629,,24.0,,*,,,high,Natural log of structure size in square feet,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,3133.0,0.7458,t,"Carroll County, spatial error model (lambda 0.2149); adjusted R2",elasticity,0.2629,0.010954166666666668,b (log-log),|b/t|,0.3946108989335921,0.01644212078889967,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.0,3123.0,sqft,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c2,4,2,8,AVERAGE,condition,A_structural,dummy,binary,0.1551,,16.76,,*,,,high,Assessor quality grade average (omitted category: fair),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,3133.0,0.7458,t,"Carroll County, spatial error model (lambda 0.2149); adjusted R2",pct_premium,16.772472982191488,1.0806793618611608,100*(exp(b - se^2/2) - 1),|b/t|,0.2872670211626098,0.01714003706220822,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.76,3123.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c2,4,2,8,GOOD_VGOOD,condition,A_structural,dummy,binary,0.3973,,16.69,,*,,,high,Assessor quality grade good or very good (omitted: fair),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,3133.0,0.7458,t,"Carroll County, spatial error model (lambda 0.2149); adjusted R2",pct_premium,48.73807226381579,3.5416645629540997,100*(exp(b - se^2/2) - 1),|b/t|,0.28616566044920383,0.01714593531750772,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.69,3123.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c2,4,2,8,NUSTORY,storeys,A_structural,level,count,-0.0155,,-1.83,,,,,high,Number of stories,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,3133.0,0.7458,t,"Carroll County, spatial error model (lambda 0.2149); adjusted R2",semi_elasticity,-1.55,0.8469945355191256,100*b/1 (per unit count),|b/t|,-0.032728972254982246,0.01788468429234002,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.83,3123.0,count,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c2,4,2,8,BASEMENT,basement,A_structural,binary,binary,0.133,,8.87,,*,,,high,,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,3133.0,0.7458,t,"Carroll County, spatial error model (lambda 0.2149); adjusted R2",pct_premium,14.212159898768672,1.712731113619041,100*(exp(b - se^2/2) - 1),|b/t|,0.15675986057481772,0.017673039523654763,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.87,3123.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c2,4,2,8,FRAME,roof_materials,A_structural,binary,binary,-0.0488,,-3.79,,*,,,high,Framed structure (omitted: all other construction types),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,3133.0,0.7458,t,"Carroll County, spatial error model (lambda 0.2149); adjusted R2",pct_premium,-4.770735912690649,1.2262726476650037,100*(exp(b - se^2/2) - 1),|b/t|,-0.06766385678698773,0.01785326036595982,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.79,3123.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c2,4,2,8,ALUM,roof_materials,A_structural,binary,binary,-0.0007,,-0.08,,,,,high,Aluminum-sided structure (omitted: all other construction types),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,3133.0,0.7458,t,"Carroll County, spatial error model (lambda 0.2149); adjusted R2",pct_premium,-0.0738008787453448,0.8743877143249877,100*(exp(b - se^2/2) - 1),|b/t|,-0.00143154020541819,0.017894252567727375,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.08,3123.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c2,4,2,8,LN_POPDEN,density,F_neighbourhood,log,households per sq mile,0.0274,,4.02,,*,,,high,Natural log of census tract/block-group population density (households per square mile),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,3133.0,0.7458,t,"Carroll County, spatial error model (lambda 0.2149); adjusted R2",elasticity,0.0274,0.006815920398009951,b (log-log),|b/t|,0.07174956947740223,0.017848151611294088,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.02,3123.0,households per sq mile,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T4-c2,4,2,8,LN_CITYDIST,cbd_distance,D_location,log,km,-0.1687,,-5.8,,*,,,high,"Natural log of Euclidean distance to nearest of Washington DC or Baltimore; printed in units of 100 km (log, so scale does not affect the elasticity)","LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,3133.0,0.7458,t,"Carroll County, spatial error model (lambda 0.2149); adjusted R2",elasticity,-0.1687,0.02908620689655172,b (log-log),|b/t|,-0.10323226728434982,0.017798666773163763,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.8,3123.0,km,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c1,5,1,9,LN_ACRE,lot_size,A_structural,log,acres,0.1045,,26.82,,*,,,high,Natural log of parcel size in acres,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,5326.0,0.739,t,"Howard County, OLS; adjusted R2",elasticity,0.1045,0.00389634601043997,b (log-log),|b/t|,0.3452302923451221,0.012872121265664508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.82,5316.0,acre,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c1,5,1,9,LN_AGE,age,A_structural,log,years,-0.0559,,-20.79,,*,,,high,Natural log of age of structure in years,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,5326.0,0.739,t,"Howard County, OLS; adjusted R2",elasticity,-0.0559,0.002688792688792689,b (log-log),|b/t|,-0.27421274971003734,0.013189646450699248,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-20.79,5316.0,years,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c1,5,1,9,LN_SQFT,living_area,A_structural,log,sqft,0.2518,,34.22,,,,,high,Natural log of structure size in square feet; no star printed although t = 34.22 (likely typographic omission); no star printed despite |t| > 1.96 (as printed),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,5326.0,0.739,t,"Howard County, OLS; adjusted R2",elasticity,0.2518,0.007358270017533607,b (log-log),|b/t|,0.42487167127676495,0.012415887530004822,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.22,5316.0,sqft,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c1,5,1,9,AVERAGE,condition,A_structural,dummy,binary,0.2258,,14.67,,*,,,high,Assessor quality grade average (omitted category: fair),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,5326.0,0.739,t,"Howard County, OLS; adjusted R2",pct_premium,25.317651994344146,1.929112334039134,100*(exp(b - se^2/2) - 1),|b/t|,0.1972513950162982,0.013445902864096675,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.67,5316.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c1,5,1,9,GOOD_VGOOD,condition,A_structural,dummy,binary,0.4152,,24.96,,*,,,high,Assessor quality grade good or very good (omitted: fair),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,5326.0,0.739,t,"Howard County, OLS; adjusted R2",pct_premium,51.4464096628954,2.519601351994465,100*(exp(b - se^2/2) - 1),|b/t|,0.3238827811548376,0.0129760729629342,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.96,5316.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c1,5,1,9,NUSTORY,storeys,A_structural,level,count,0.0675,,8.04,,*,,,high,Number of stories,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,5326.0,0.739,t,"Howard County, OLS; adjusted R2",semi_elasticity,6.75,0.8395522388059703,100*b/1 (per unit count),|b/t|,0.109607183023019,0.01363273420684316,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.04,5316.0,count,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c1,5,1,9,BASEMENT,basement,A_structural,binary,binary,0.0847,,8.13,,*,,,high,,"LN_PRICE (natural log of full transaction price, USD)",log,OLS,5326.0,0.739,t,"Howard County, OLS; adjusted R2",pct_premium,8.833143577197667,1.1339074464688774,100*(exp(b - se^2/2) - 1),|b/t|,0.1108191435099518,0.013630890960633676,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.13,5316.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c1,5,1,9,FRAME,roof_materials,A_structural,binary,binary,-0.0736,,-7.85,,*,,,high,Framed structure (omitted: all other construction types),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,5326.0,0.739,t,"Howard County, OLS; adjusted R2",pct_premium,-7.099759631036373,0.871052002931637,100*(exp(b - se^2/2) - 1),|b/t|,-0.10704699999237993,0.013636560508583431,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.85,5316.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c1,5,1,9,ALUM,roof_materials,A_structural,binary,binary,-0.0919,,-8.58,,*,,,high,Aluminum-sided structure (omitted: all other construction types),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,5326.0,0.739,t,"Howard County, OLS; adjusted R2",pct_premium,-8.785595954741199,0.9770494861147367,100*(exp(b - se^2/2) - 1),|b/t|,-0.11687143052879623,0.01362137884951005,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.58,5316.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c1,5,1,9,LN_POPDEN,density,F_neighbourhood,log,households per sq mile,0.0089,,2.62,,*,,,high,Natural log of census tract/block-group population density (households per square mile),"LN_PRICE (natural log of full transaction price, USD)",log,OLS,5326.0,0.739,t,"Howard County, OLS; adjusted R2",elasticity,0.0089,0.003396946564885496,b (log-log),|b/t|,0.03591109021798119,0.013706522983962285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.62,5316.0,households per sq mile,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c1,5,1,9,LN_CITYDIST,cbd_distance,D_location,log,km,-0.0033,,-0.24,,,,,high,"Natural log of Euclidean distance to nearest of Washington DC or Baltimore; printed in units of 100 km (log, so scale does not affect the elasticity)","LN_PRICE (natural log of full transaction price, USD)",log,OLS,5326.0,0.739,t,"Howard County, OLS; adjusted R2",elasticity,-0.0033,0.01375,b (log-log),|b/t|,-0.0032916708593588974,0.013715295247328741,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.24,5316.0,km,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,ols,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c2,5,2,9,LN_ACRE,lot_size,A_structural,log,acres,0.1114,,23.79,,*,,,high,Natural log of parcel size in acres,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,5326.0,0.7741,t,"Howard County, spatial error model (lambda 0.6339); adjusted R2",elasticity,0.1114,0.004682639764606978,b (log-log),|b/t|,0.31019390298276023,0.013038835770607828,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.79,5316.0,acre,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c2,5,2,9,LN_AGE,age,A_structural,log,years,-0.0566,,-18.56,,*,,,high,Natural log of age of structure in years,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,5326.0,0.7741,t,"Howard County, spatial error model (lambda 0.6339); adjusted R2",elasticity,-0.0566,0.0030495689655172416,b (log-log),|b/t|,-0.24669002402393345,0.013291488363358486,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-18.56,5316.0,years,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c2,5,2,9,LN_SQFT,living_area,A_structural,log,sqft,0.2031,,29.46,,*,,,high,Natural log of structure size in square feet,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,5326.0,0.7741,t,"Howard County, spatial error model (lambda 0.6339); adjusted R2",elasticity,0.2031,0.006894093686354378,b (log-log),|b/t|,0.37462935836639993,0.012716543053849285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.46,5316.0,sqft,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c2,5,2,9,AVERAGE,condition,A_structural,dummy,binary,0.23,,14.07,,*,,,high,Assessor quality grade average (omitted category: fair),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,5326.0,0.7741,t,"Howard County, spatial error model (lambda 0.6339); adjusted R2",pct_premium,25.843186018963603,2.057412951554939,100*(exp(b - se^2/2) - 1),|b/t|,0.18947944275502163,0.013466911354301465,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.07,5316.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c2,5,2,9,GOOD_VGOOD,condition,A_structural,dummy,binary,0.412,,23.06,,*,,,high,Assessor quality grade good or very good (omitted: fair),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,5326.0,0.7741,t,"Howard County, spatial error model (lambda 0.6339); adjusted R2",pct_premium,50.95934788003724,2.6975359400149297,100*(exp(b - se^2/2) - 1),|b/t|,0.3015535177997151,0.013076908837802046,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.06,5316.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c2,5,2,9,NUSTORY,storeys,A_structural,level,count,0.0734,,8.97,,*,,,high,Number of stories,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,5326.0,0.7741,t,"Howard County, spatial error model (lambda 0.6339); adjusted R2",semi_elasticity,7.340000000000001,0.8182831661092531,100*b/1 (per unit count),|b/t|,0.12210625894964183,0.013612737898510795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.97,5316.0,count,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c2,5,2,9,BASEMENT,basement,A_structural,binary,binary,0.0731,,7.15,,*,,,high,,"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,5326.0,0.7741,t,"Howard County, spatial error model (lambda 0.6339); adjusted R2",pct_premium,7.578189050407147,1.0999128144319201,100*(exp(b - se^2/2) - 1),|b/t|,0.09759673474669803,0.013649892971566158,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.15,5316.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c2,5,2,9,FRAME,roof_materials,A_structural,binary,binary,-0.0538,,-6.0,,*,,,high,Framed structure (omitted: all other construction types),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,5326.0,0.7741,t,"Howard County, spatial error model (lambda 0.6339); adjusted R2",pct_premium,-5.241648227654149,0.8497007119794603,100*(exp(b - se^2/2) - 1),|b/t|,-0.08201498277207121,0.013669163795345203,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,5316.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c2,5,2,9,ALUM,roof_materials,A_structural,binary,binary,-0.0601,,-5.65,,*,,,high,Aluminum-sided structure (omitted: all other construction types),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,5326.0,0.7741,t,"Howard County, spatial error model (lambda 0.6339); adjusted R2",pct_premium,-5.838291134630225,1.0016705972842004,100*(exp(b - se^2/2) - 1),|b/t|,-0.0772602119664432,0.013674373799370476,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.65,5316.0,binary,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c2,5,2,9,LN_POPDEN,density,F_neighbourhood,log,households per sq mile,0.0041,,0.74,,,,,high,Natural log of census tract/block-group population density (households per square mile),"LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,5326.0,0.7741,t,"Howard County, spatial error model (lambda 0.6339); adjusted R2",elasticity,0.0041,0.005540540540540541,b (log-log),|b/t|,0.010148850765904547,0.01371466319716831,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.74,5316.0,households per sq mile,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e,1196e55c7401009f4e60d7c8db96469c1e13b00e:T5-c2,5,2,9,LN_CITYDIST,cbd_distance,D_location,log,km,0.0154,,1.68,,,,,high,"Natural log of Euclidean distance to nearest of Washington DC or Baltimore; printed in units of 100 km (log, so scale does not affect the elasticity)","LN_PRICE (natural log of full transaction price, USD)",log,spatial_error,5326.0,0.7741,t,"Howard County, spatial error model (lambda 0.6339); adjusted R2",elasticity,0.0154,0.009166666666666667,b (log-log),|b/t|,0.023035706535390024,0.0137117300805893,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.68,5316.0,km,,2003.0,United States,North America,High income,1993.0,1996.0,single_family,transaction,journal,True,False,unknown,,1994.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c1,2,1,9,House size (sq. ft.),living_area,A_structural,log,sqft,0.516,0.113,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,247.0,0.557,se,Combined; All variables; adj. R2 0.522,elasticity,0.516,0.113,b (log-log),reported,0.2843715965401644,0.06227517521131507,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.566371681415929,237.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c2,2,2,9,House size (sq. ft.),living_area,A_structural,log,sqft,0.498,0.125,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.623,se,San Diego; All variables; adj. R2 0.566,elasticity,0.498,0.125,b (log-log),reported,0.34178573798174144,0.08578959286690298,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.984,120.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c3,2,3,9,House size (sq. ft.),living_area,A_structural,log,sqft,0.523,0.163,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,117.0,0.55,se,Santa Cruz; All variables; adj. R2 0.473,elasticity,0.523,0.163,b (log-log),reported,0.29626084341757886,0.09233368542459913,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.208588957055215,107.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c4,2,4,9,House size (sq. ft.),living_area,A_structural,log,sqft,0.496,0.089,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,281.0,0.516,se,"Combined; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.496",elasticity,0.496,0.089,b (log-log),reported,0.3206608887890714,0.05753794173836161,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.573033707865169,271.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c5,2,5,9,House size (sq. ft.),living_area,A_structural,log,sqft,0.455,0.105,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.574,se,"San Diego; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.538",elasticity,0.455,0.105,b (log-log),reported,0.36784269273329034,0.08488677524614391,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.333333333333334,120.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c6,2,6,9,House size (sq. ft.),living_area,A_structural,log,sqft,0.48,0.131,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,151.0,0.497,se,"Santa Cruz; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.461",elasticity,0.48,0.131,b (log-log),reported,0.29485603717916387,0.08047112681348013,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.66412213740458,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c7,2,7,9,House size (sq. ft.),living_area,A_structural,log,sqft,0.494,0.088,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,281.0,0.513,se,Combined; Reduced model 2 (also drops nourishment dummies); adj. R2 0.497,elasticity,0.494,0.088,b (log-log),reported,0.3227545086923724,0.057494730293378066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.613636363636364,271.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c8,2,8,9,House size (sq. ft.),living_area,A_structural,log,sqft,0.46,0.104,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.572,se,San Diego; Reduced model 2 (also drops nourishment dummies); adj. R2 0.544,elasticity,0.46,0.104,b (log-log),reported,0.37440220339954616,0.08464745468163651,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.423076923076923,120.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c9,2,9,9,House size (sq. ft.),living_area,A_structural,log,sqft,0.504,0.129,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,151.0,0.486,se,Santa Cruz; Reduced model 2 (also drops nourishment dummies); adj. R2 0.457,elasticity,0.504,0.129,b (log-log),reported,0.31254367056844606,0.07999629663359036,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9069767441860463,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c1,2,1,9,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.15,0.061,,,**,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,247.0,0.557,se,Combined; All variables; adj. R2 0.522,elasticity,0.15,0.061,b (log-log),reported,0.15773079948181284,0.06414385845593722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.459016393442623,237.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c2,2,2,9,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.37,0.097,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.623,se,San Diego; All variables; adj. R2 0.566,elasticity,0.37,0.097,b (log-log),reported,0.32884277293851416,0.08621013236496183,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8144329896907214,120.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c3,2,3,9,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.057,0.073,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,117.0,0.55,se,Santa Cruz; All variables; adj. R2 0.473,elasticity,0.057,0.073,b (log-log),reported,0.07527076324511374,0.09639939854198776,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7808219178082193,107.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c4,2,4,9,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.133,0.053,,,**,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,281.0,0.516,se,"Combined; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.496",elasticity,0.133,0.053,b (log-log),reported,0.15069643664636465,0.060051963475618995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.509433962264151,271.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c5,2,5,9,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.373,0.089,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.574,se,"San Diego; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.538",elasticity,0.373,0.089,b (log-log),reported,0.3573267419035699,0.08526026817538263,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.191011235955056,120.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c6,2,6,9,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.079,0.065,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,151.0,0.497,se,"Santa Cruz; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.461",elasticity,0.079,0.065,b (log-log),reported,0.10182187969902326,0.08377749595489256,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2153846153846153,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c7,2,7,9,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.137,0.053,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,281.0,0.513,se,Combined; Reduced model 2 (also drops nourishment dummies); adj. R2 0.497,elasticity,0.137,0.053,b (log-log),reported,0.15512115818673045,0.06001037506493951,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5849056603773586,271.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c8,2,8,9,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.375,0.089,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.572,se,San Diego; Reduced model 2 (also drops nourishment dummies); adj. R2 0.544,elasticity,0.375,0.089,b (log-log),reported,0.3589963510264612,0.08520180064361345,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.213483146067416,120.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c9,2,9,9,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.076,0.063,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,151.0,0.486,se,Santa Cruz; Reduced model 2 (also drops nourishment dummies); adj. R2 0.457,elasticity,0.076,0.063,b (log-log),reported,0.10107267732237708,0.0837839298856547,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2063492063492063,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c1,2,1,9,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.387,0.04,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,247.0,0.557,se,Combined; All variables; adj. R2 0.522,elasticity,-0.387,0.04,b (log-log),reported,-0.5321031800599463,0.05499774470903838,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.675,237.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c2,2,2,9,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.392,0.058,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.623,se,San Diego; All variables; adj. R2 0.566,elasticity,-0.392,0.058,b (log-log),reported,-0.5250787007287627,0.07769021592415368,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.758620689655173,120.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,True
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c3,2,3,9,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.375,0.057,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,117.0,0.55,se,Santa Cruz; All variables; adj. R2 0.473,elasticity,-0.375,0.057,b (log-log),reported,-0.5366635961010194,0.08157286660735497,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.578947368421052,107.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c4,2,4,9,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.374,0.036,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,281.0,0.516,se,"Combined; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.496",elasticity,-0.374,0.036,b (log-log),reported,-0.5336913605824131,0.05137136091167612,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.38888888888889,271.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c5,2,5,9,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.379,0.055,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.574,se,"San Diego; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.538",elasticity,-0.379,0.055,b (log-log),reported,-0.5324625207701638,0.07727028665530081,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.890909090909091,120.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c6,2,6,9,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.355,0.048,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,151.0,0.497,se,"Santa Cruz; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.461",elasticity,-0.355,0.048,b (log-log),reported,-0.5286807931996682,0.07148360020727909,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.395833333333333,141.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c7,2,7,9,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.372,0.036,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,281.0,0.513,se,Combined; Reduced model 2 (also drops nourishment dummies); adj. R2 0.497,elasticity,-0.372,0.036,b (log-log),reported,-0.5316456139417775,0.05144957554275265,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.333333333333334,271.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c8,2,8,9,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.38,0.055,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.572,se,San Diego; Reduced model 2 (also drops nourishment dummies); adj. R2 0.544,elasticity,-0.38,0.055,b (log-log),reported,-0.5334679898331169,0.07721247221268797,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.909090909090909,120.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c9,2,9,9,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.359,0.047,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,151.0,0.486,se,Santa Cruz; Reduced model 2 (also drops nourishment dummies); adj. R2 0.457,elasticity,-0.359,0.047,b (log-log),reported,-0.5409977367350923,0.0708270017452628,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.638297872340425,141.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c1,2,1,9,Fireplace (0−1),fireplace,B_interior,binary,binary,0.232,0.075,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,247.0,0.557,se,Combined; All variables; adj. R2 0.522,pct_premium,25.757781274525037,9.45839796621247,100*(exp(b - se^2/2) - 1),reported,0.1969961501855258,0.06368410027549325,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0933333333333337,237.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c2,2,2,9,Fireplace (0−1),fireplace,B_interior,binary,binary,0.267,0.096,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.623,se,San Diego; All variables; adj. R2 0.566,pct_premium,30.003605669228506,12.537988284774281,100*(exp(b - se^2/2) - 1),reported,0.24608462161750064,0.08847986395235978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.78125,120.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,True
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c3,2,3,9,Fireplace (0−1),fireplace,B_interior,binary,binary,0.181,0.115,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,117.0,0.55,se,Santa Cruz; All variables; adj. R2 0.473,pct_premium,19.051680171080033,13.781774561871796,100*(exp(b - se^2/2) - 1),reported,0.15042460832676538,0.09557364617446419,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5739130434782607,107.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c4,2,4,9,Fireplace (0−1),fireplace,B_interior,binary,binary,0.213,0.074,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,281.0,0.516,se,"Combined; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.496",pct_premium,23.400132595444845,9.156646419202644,100*(exp(b - se^2/2) - 1),reported,0.17223603927753361,0.05983787280064548,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8783783783783785,271.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c5,2,5,9,Fireplace (0−1),fireplace,B_interior,binary,binary,0.255,0.105,,,**,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.574,se,"San Diego; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.538",pct_premium,28.33675222615357,13.549847019165343,100*(exp(b - se^2/2) - 1),reported,0.21644199897526475,0.08912317604863841,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.428571428571429,120.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,True
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c6,2,6,9,Fireplace (0−1),fireplace,B_interior,binary,binary,0.187,0.104,,,*,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,151.0,0.497,se,"Santa Cruz; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.461",pct_premium,19.91248511214763,12.538523764519217,100*(exp(b - se^2/2) - 1),reported,0.1497186241441001,0.08326597278602359,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7980769230769231,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c7,2,7,9,Fireplace (0−1),fireplace,B_interior,binary,binary,0.211,0.074,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,281.0,0.513,se,Combined; Reduced model 2 (also drops nourishment dummies); adj. R2 0.497,pct_premium,23.15357896606787,9.138351427454317,100*(exp(b - se^2/2) - 1),reported,0.17066612137963472,0.05985446910944536,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8513513513513513,271.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c8,2,8,9,Fireplace (0−1),fireplace,B_interior,binary,binary,0.241,0.103,,,**,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.572,se,San Diego; Reduced model 2 (also drops nourishment dummies); adj. R2 0.544,pct_premium,26.57888187834758,13.10696666367476,100*(exp(b - se^2/2) - 1),reported,0.2088823524635587,0.08927337055496493,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3398058252427183,120.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c9,2,9,9,Fireplace (0−1),fireplace,B_interior,binary,binary,0.191,0.104,,,*,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,151.0,0.486,se,Santa Cruz; Reduced model 2 (also drops nourishment dummies); adj. R2 0.457,pct_premium,20.393095632823698,12.588778301645513,100*(exp(b - se^2/2) - 1),reported,0.15284710862460937,0.08322565076942082,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8365384615384617,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c1,2,1,9,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.29,0.106,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,247.0,0.557,se,Combined; All variables; adj. R2 0.522,pct_premium,32.89404890698086,14.166131373070003,100*(exp(b - se^2/2) - 1),reported,0.17497102607354148,0.06395492677170826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7358490566037736,237.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c2,2,2,9,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.165,0.119,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.623,se,San Diego; All variables; adj. R2 0.566,pct_premium,17.107191962361856,14.034778112665549,100*(exp(b - se^2/2) - 1),reported,0.1255726308445825,0.09056450345760797,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3865546218487397,120.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c3,2,3,9,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.333,0.159,,,**,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,117.0,0.55,se,Santa Cruz; All variables; adj. R2 0.473,pct_premium,37.76229307680692,22.18284204566988,100*(exp(b - se^2/2) - 1),reported,0.19844095171273018,0.0947510850520243,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0943396226415096,107.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c4,2,4,9,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.375,0.088,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,281.0,0.516,se,"Combined; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.496",pct_premium,44.936858069225224,12.80392444864017,100*(exp(b - se^2/2) - 1),reported,0.25059942678096137,0.05880733215126559,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.261363636363637,271.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c5,2,5,9,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.196,0.134,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.574,se,"San Diego; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.538",pct_premium,20.565380914195973,16.30146053147984,100*(exp(b - se^2/2) - 1),reported,0.13234980002579078,0.09048404695640798,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.462686567164179,120.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c6,2,6,9,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.463,0.117,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,151.0,0.497,se,"Santa Cruz; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); adj. R2 0.461",pct_premium,57.799570402127685,18.589350106268135,100*(exp(b - se^2/2) - 1),reported,0.31616671223483006,0.07989525989519464,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9572649572649574,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c7,2,7,9,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.365,0.086,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,281.0,0.513,se,Combined; Reduced model 2 (also drops nourishment dummies); adj. R2 0.497,pct_premium,43.51968248784115,12.388420470083267,100*(exp(b - se^2/2) - 1),reported,0.2496523380256856,0.05882219471290125,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.244186046511628,271.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c8,2,8,9,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.207,0.133,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.572,se,San Diego; Reduced model 2 (also drops nourishment dummies); adj. R2 0.544,pct_premium,21.91519572120537,16.35876820468401,100*(exp(b - se^2/2) - 1),reported,0.1406657426574951,0.09037943851906691,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5563909774436089,120.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c9,2,9,9,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.428,0.112,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,151.0,0.486,se,Santa Cruz; Reduced model 2 (also drops nourishment dummies); adj. R2 0.457,pct_premium,52.45937787725665,17.18288410683689,100*(exp(b - se^2/2) - 1),reported,0.30634889768187484,0.08016606668310743,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.821428571428571,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c1,2,1,9,Bedrooms,bedrooms,A_structural,log,count,-0.036,0.088,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,247.0,0.557,se,Combined; All variables; adj. R2 0.522,elasticity,-0.036,0.088,b (log-log),reported,-0.02656393281731724,0.0649340579978866,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.40909090909090906,237.0,count,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c2,2,2,9,Bedrooms,bedrooms,A_structural,log,count,-0.066,0.116,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.623,se,San Diego; All variables; adj. R2 0.566,elasticity,-0.066,0.116,b (log-log),reported,-0.05186929175046857,0.09116420974324778,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5689655172413793,120.0,count,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,True
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c3,2,3,9,Bedrooms,bedrooms,A_structural,log,count,0.032,0.137,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,117.0,0.55,se,Santa Cruz; All variables; adj. R2 0.473,elasticity,0.032,0.137,b (log-log),reported,0.02257495169509073,0.0966490119446072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.23357664233576642,107.0,count,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c1,2,1,10,Elevation (ft.),flood_risk,E_environment,log,"ft (first-floor height above base flood elevation), log",0.013,0.016,,,,,,high,flood protection measure; entered in logs per Eq. 4,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,247.0,0.557,se,Combined; All variables; adj. R2 0.522,elasticity,0.013,0.016,b (log-log),reported,0.05270419453355939,0.06486670096438078,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8125,237.0,ft log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c2,2,2,10,Elevation (ft.),flood_risk,E_environment,log,"ft (first-floor height above base flood elevation), log",-0.004,0.027,,,,,,high,flood protection measure; entered in logs per Eq. 4,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.623,se,San Diego; All variables; adj. R2 0.566,elasticity,-0.004,0.027,b (log-log),reported,-0.013522777171238454,0.09127874590585956,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.14814814814814814,120.0,ft log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c3,2,3,10,Elevation (ft.),flood_risk,E_environment,log,"ft (first-floor height above base flood elevation), log",0.02,0.023,,,,,,high,flood protection measure; entered in logs per Eq. 4,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,117.0,0.55,se,Santa Cruz; All variables; adj. R2 0.473,elasticity,0.02,0.023,b (log-log),reported,0.08376857725110064,0.09633386383876572,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8695652173913044,107.0,ft log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c1,2,1,10,Distance to water (ft.),water_proximity,E_environment,log,ft,-0.009,0.043,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,247.0,0.557,se,Combined; All variables; adj. R2 0.522,elasticity,-0.009,0.043,b (log-log),reported,-0.013594390681734828,0.06495097770162195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.20930232558139536,237.0,ft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c2,2,2,10,Distance to water (ft.),water_proximity,E_environment,log,ft,0.027,0.109,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.623,se,San Diego; All variables; adj. R2 0.566,elasticity,0.027,0.109,b (log-log),reported,0.022606620286399405,0.09126376337842723,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2477064220183486,120.0,ft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c3,2,3,10,Distance to water (ft.),water_proximity,E_environment,log,ft,-0.023,0.049,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,117.0,0.55,se,Santa Cruz; All variables; adj. R2 0.473,elasticity,-0.023,0.049,b (log-log),reported,-0.04533078048534455,0.09657427146877752,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4693877551020408,107.0,ft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c1,2,1,10,Built Post-FIRM,flood_risk,E_environment,binary,binary (built after Flood Insurance Rate Map publication),-0.54,0.239,,,**,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,247.0,0.557,se,Combined; All variables; adj. R2 0.522,pct_premium,-43.36599012205379,13.927683231738351,100*(exp(b - se^2/2) - 1),reported,-0.14520916296684647,0.06426849990569684,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.259414225941423,237.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c2,2,2,10,Built Post-FIRM,flood_risk,E_environment,binary,binary (built after Flood Insurance Rate Map publication),-0.58,0.356,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,130.0,0.623,se,San Diego; All variables; adj. R2 0.566,pct_premium,-47.44805095450383,19.932381849728312,100*(exp(b - se^2/2) - 1),reported,-0.1471080848926163,0.09029392796857137,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6292134831460674,120.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,True
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T2-c3,2,3,10,Built Post-FIRM,flood_risk,E_environment,binary,binary (built after Flood Insurance Rate Map publication),-0.476,0.401,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,OLS,117.0,0.55,se,Santa Cruz; All variables; adj. R2 0.473,pct_premium,-42.67311642753631,24.91266563812322,100*(exp(b - se^2/2) - 1),reported,-0.11400655402856086,0.09604333648204393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1870324189526182,107.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,ols,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c1,4,Spatial lag model (1),17,House size (sq. ft.),living_area,A_structural,log,sqft,0.496,0.155,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,117.0,,se,"Santa Cruz only; Spatial lag model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.103",elasticity,0.496,0.155,b (log-log),reported,0.2955371449174024,0.09235535778668826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2,107.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c2,4,Spatial lag model (2),17,House size (sq. ft.),living_area,A_structural,log,sqft,0.48,0.117,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,151.0,,se,"Santa Cruz only; Spatial lag model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -106.39",elasticity,0.48,0.117,b (log-log),reported,0.32655713503848804,0.07959830166563148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.102564102564102,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c3,4,Spatial lag model (3),17,House size (sq. ft.),living_area,A_structural,log,sqft,0.502,0.118,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,151.0,,se,"Santa Cruz only; Spatial lag model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.966",elasticity,0.502,0.118,b (log-log),reported,0.337278470428434,0.07928059663457213,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.254237288135593,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c4,4,Spatial error model (1),17,House size (sq. ft.),living_area,A_structural,log,sqft,0.519,0.155,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,117.0,,se,"Santa Cruz only; Spatial error model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.586",elasticity,0.519,0.155,b (log-log),reported,0.3079678883983387,0.09197499557175819,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3483870967741938,107.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c5,4,Spatial error model (2),17,House size (sq. ft.),living_area,A_structural,log,sqft,0.484,0.114,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,151.0,,se,"Santa Cruz only; Spatial error model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -106.167",elasticity,0.484,0.114,b (log-log),reported,0.3366723748523598,0.07929886515117567,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.245614035087719,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c6,4,Spatial error model (3),17,House size (sq. ft.),living_area,A_structural,log,sqft,0.508,0.115,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,151.0,,se,"Santa Cruz only; Spatial error model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.833",elasticity,0.508,0.115,b (log-log),reported,0.34866656086737075,0.07893042224359771,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.417391304347826,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c7,4,"Spatial ARAR(1,1) model (1)",17,House size (sq. ft.),living_area,A_structural,log,sqft,0.472,0.149,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,117.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; All variables; ML estimation, inverse-distance weights; log-likelihood -70.669",elasticity,0.472,0.149,b (log-log),reported,0.2928182252858344,0.0924362617957401,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1677852348993287,107.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c8,4,"Spatial ARAR(1,1) model (2)",17,House size (sq. ft.),living_area,A_structural,log,sqft,0.468,0.112,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,151.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -105.846",elasticity,0.468,0.112,b (log-log),reported,0.3319459508250636,0.07944005660770753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.178571428571429,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c9,4,"Spatial ARAR(1,1) model (3)",17,House size (sq. ft.),living_area,A_structural,log,sqft,0.489,0.113,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,151.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.458",elasticity,0.489,0.113,b (log-log),reported,0.3424062480227311,0.07912455220157182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.327433628318584,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c1,4,Spatial lag model (1),17,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.056,0.075,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,117.0,,se,"Santa Cruz only; Spatial lag model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.103",elasticity,0.056,0.075,b (log-log),reported,0.07199567230858431,0.09642277541328255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7466666666666667,107.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c2,4,Spatial lag model (2),17,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.079,0.06,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,151.0,,se,"Santa Cruz only; Spatial lag model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -106.39",elasticity,0.079,0.06,b (log-log),reported,0.11020789674104979,0.08370220005649352,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3166666666666667,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c3,4,Spatial lag model (3),17,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.076,0.059,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,151.0,,se,"Santa Cruz only; Spatial lag model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.966",elasticity,0.076,0.059,b (log-log),reported,0.10784786361554825,0.08372399938575456,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.288135593220339,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c4,4,Spatial error model (1),17,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.056,0.077,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,117.0,,se,"Santa Cruz only; Spatial error model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.586",elasticity,0.056,0.077,b (log-log),reported,0.07013497532921857,0.09643559107767553,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7272727272727273,107.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c5,4,Spatial error model (2),17,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.073,0.058,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,151.0,,se,"Santa Cruz only; Spatial error model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -106.167",elasticity,0.073,0.058,b (log-log),reported,0.10540453036112986,0.08374606521843193,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2586206896551724,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c6,4,Spatial error model (3),17,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.071,0.058,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,151.0,,se,"Santa Cruz only; Spatial error model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.833",elasticity,0.071,0.058,b (log-log),reported,0.10254752614540359,0.08377121854131563,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2241379310344827,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c7,4,"Spatial ARAR(1,1) model (1)",17,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.064,0.07,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,117.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; All variables; ML estimation, inverse-distance weights; log-likelihood -70.669",elasticity,0.064,0.07,b (log-log),reported,0.08804409086431449,0.09629822438284395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9142857142857143,107.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c8,4,"Spatial ARAR(1,1) model (2)",17,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.064,0.055,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,151.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -105.846",elasticity,0.064,0.055,b (log-log),reported,0.09752868563767927,0.08381371421988063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1636363636363636,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c9,4,"Spatial ARAR(1,1) model (3)",17,Lot size (sq. ft.),lot_size,A_structural,log,sqft,0.062,0.055,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,151.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.458",elasticity,0.062,0.055,b (log-log),reported,0.0945085715312309,0.08383824893899516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1272727272727272,141.0,sqft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c1,4,Spatial lag model (1),17,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.379,0.057,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,117.0,,se,"Santa Cruz only; Spatial lag model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.103",elasticity,-0.379,0.057,b (log-log),reported,-0.5407205806196017,0.08132209259978179,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.649122807017544,107.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c2,4,Spatial lag model (2),17,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.355,0.053,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,151.0,,se,"Santa Cruz only; Spatial lag model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -106.39",elasticity,-0.355,0.053,b (log-log),reported,-0.49130818789829556,0.0733502365031258,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.69811320754717,141.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c3,4,Spatial lag model (3),17,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.36,0.053,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,151.0,,se,"Santa Cruz only; Spatial lag model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.966",elasticity,-0.36,0.053,b (log-log),reported,-0.49653094230271533,0.07310038872789976,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.7924528301886795,141.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c4,4,Spatial error model (1),17,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.374,0.058,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,117.0,,se,"Santa Cruz only; Spatial error model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.586",elasticity,-0.374,0.058,b (log-log),reported,-0.5290089861038253,0.08203882672198361,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.448275862068965,107.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c5,4,Spatial error model (2),17,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.358,0.053,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,151.0,,se,"Santa Cruz only; Spatial error model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -106.167",elasticity,-0.358,0.053,b (log-log),reported,-0.494448255181082,0.07320044001284175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.754716981132075,141.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c6,4,Spatial error model (3),17,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.363,0.053,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,151.0,,se,"Santa Cruz only; Spatial error model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.833",elasticity,-0.363,0.053,b (log-log),reported,-0.49963896346549513,0.07295004149771692,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.849056603773585,141.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c7,4,"Spatial ARAR(1,1) model (1)",17,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.382,0.057,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,117.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; All variables; ML estimation, inverse-distance weights; log-likelihood -70.669",elasticity,-0.382,0.057,b (log-log),reported,-0.5437387762422808,0.081133796455,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.701754385964912,107.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c8,4,"Spatial ARAR(1,1) model (2)",17,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.363,0.053,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,151.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -105.846",elasticity,-0.363,0.053,b (log-log),reported,-0.49963896346549513,0.07295004149771692,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.849056603773585,141.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c9,4,"Spatial ARAR(1,1) model (3)",17,Years since last transaction,transaction_timing,G_market,log,"years (since purchase), log",-0.367,0.052,,,***,,,high,captures price appreciation since purchase year (survey-reported purchase price),"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,151.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.458",elasticity,-0.367,0.052,b (log-log),reported,-0.5109295171692934,0.07239328308665738,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0576923076923075,141.0,years log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c1,4,Spatial lag model (1),17,Fireplace (0−1),fireplace,B_interior,binary,binary,0.176,0.116,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,117.0,,se,"Santa Cruz only; Spatial lag model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.103",pct_premium,18.444226340870063,13.832281480347769,100*(exp(b - se^2/2) - 1),reported,0.1451244482865132,0.09565020455247461,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5172413793103448,107.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c2,4,Spatial lag model (2),17,Fireplace (0−1),fireplace,B_interior,binary,binary,0.187,0.108,,,*,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,151.0,,se,"Santa Cruz only; Spatial lag model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -106.39",pct_premium,19.861652995630298,13.020774678539187,100*(exp(b - se^2/2) - 1),reported,0.14429111139299797,0.08333390390611647,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7314814814814814,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c3,4,Spatial lag model (3),17,Fireplace (0−1),fireplace,B_interior,binary,binary,0.191,0.108,,,*,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,151.0,,se,"Santa Cruz only; Spatial lag model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.966",pct_premium,20.342059780640632,13.072962082478034,100*(exp(b - se^2/2) - 1),reported,0.14731126106326328,0.08329641986823264,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7685185185185186,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c4,4,Spatial error model (1),17,Fireplace (0−1),fireplace,B_interior,binary,binary,0.183,0.117,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,117.0,,se,"Santa Cruz only; Spatial error model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.586",pct_premium,19.262349718626215,14.04952857454572,100*(exp(b - se^2/2) - 1),reported,0.14950800765199054,0.09558708685946937,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5641025641025639,107.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c5,4,Spatial error model (2),17,Fireplace (0−1),fireplace,B_interior,binary,binary,0.177,0.108,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,151.0,,se,"Santa Cruz only; Spatial error model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -106.167",pct_premium,18.66900962122424,12.891215805773099,100*(exp(b - se^2/2) - 1),reported,0.13672324227297133,0.08342435121740625,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6388888888888888,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c6,4,Spatial error model (3),17,Fireplace (0−1),fireplace,B_interior,binary,binary,0.184,0.108,,,*,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,151.0,,se,"Santa Cruz only; Spatial error model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.833",pct_premium,19.50260687510874,12.981770889440055,100*(exp(b - se^2/2) - 1),reported,0.14202334516028056,0.08336152868103423,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7037037037037037,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c7,4,"Spatial ARAR(1,1) model (1)",17,Fireplace (0−1),fireplace,B_interior,binary,binary,0.142,0.119,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,117.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; All variables; ML estimation, inverse-distance weights; log-likelihood -70.669",pct_premium,14.444465284851704,13.715662117590359,100*(exp(b - se^2/2) - 1),reported,0.11459847783053664,0.09603675254812578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1932773109243697,107.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c8,4,"Spatial ARAR(1,1) model (2)",17,Fireplace (0−1),fireplace,B_interior,binary,binary,0.165,0.108,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,151.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -105.846",pct_premium,17.253491600071968,12.737445682083019,100*(exp(b - se^2/2) - 1),reported,0.12761020881670534,0.08352668213457076,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.527777777777778,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c9,4,"Spatial ARAR(1,1) model (3)",17,Fireplace (0−1),fireplace,B_interior,binary,binary,0.171,0.108,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,151.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.458",pct_premium,17.959127339986193,12.814100089434488,100*(exp(b - se^2/2) - 1),reported,0.13217091487147517,0.08347636728724749,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5833333333333335,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c1,4,Spatial lag model (1),17,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.333,0.131,,,**,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,117.0,,se,"Santa Cruz only; Spatial lag model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.103",pct_premium,38.32274493411394,18.27642960995443,100*(exp(b - se^2/2) - 1),reported,0.23864279163818658,0.09388049761141874,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5419847328244276,107.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c2,4,Spatial lag model (2),17,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.463,0.101,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,151.0,,se,"Santa Cruz only; Spatial lag model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -106.39",pct_premium,58.07501296901327,16.04721675840241,100*(exp(b - se^2/2) - 1),reported,0.36014937345667997,0.07856390220113323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.584158415841584,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c3,4,Spatial lag model (3),17,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.426,0.099,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,151.0,,se,"Santa Cruz only; Spatial lag model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.966",pct_premium,52.36358726361434,15.158095673819151,100*(exp(b - se^2/2) - 1),reported,0.34070003964439893,0.07917676977651524,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.303030303030303,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c4,4,Spatial error model (1),17,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.326,0.136,,,**,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,117.0,,se,"Santa Cruz only; Spatial error model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.586",pct_premium,37.26621095067062,18.84164901666987,100*(exp(b - se^2/2) - 1),reported,0.22575029689993298,0.09417803797052418,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3970588235294117,107.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c5,4,Spatial error model (2),17,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.48,0.1,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,151.0,,se,"Santa Cruz only; Spatial error model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -106.167",pct_premium,60.80141974857829,16.160744021928934,100*(exp(b - se^2/2) - 1),reported,0.3747713274987064,0.07807735989556383,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.8,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c6,4,Spatial error model (3),17,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.441,0.098,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,151.0,,se,"Santa Cruz only; Spatial error model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.833",pct_premium,54.6815033807404,15.231754882954599,100*(exp(b - se^2/2) - 1),reported,0.354374653931171,0.07874992309581577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c7,4,"Spatial ARAR(1,1) model (1)",17,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.371,0.133,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,117.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; All variables; ML estimation, inverse-distance weights; log-likelihood -70.669",pct_premium,43.64222882605515,19.274134876042375,100*(exp(b - se^2/2) - 1),reported,0.2603676104967943,0.09333933206488854,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.789473684210526,107.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c8,4,"Spatial ARAR(1,1) model (2)",17,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.47,0.096,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,151.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; Reduced model (drops bedrooms, Geotime, elevation, distance to water, beach width, post-FIRM); ML estimation, inverse-distance weights; log-likelihood -105.846",pct_premium,59.26383807827635,15.359944254886658,100*(exp(b - se^2/2) - 1),reported,0.3811757045894443,0.07785716519273755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.895833333333333,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c9,4,"Spatial ARAR(1,1) model (3)",17,Waterfront (0−1),waterfront,C_exterior,binary,binary,0.434,0.094,,,***,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,151.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; Reduced model 2 (also drops nourishment dummies); ML estimation, inverse-distance weights; log-likelihood -107.458",pct_premium,53.66150841826198,14.50813736029498,100*(exp(b - se^2/2) - 1),reported,0.3623931879506572,0.07849069047779211,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.617021276595745,141.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c1,4,Spatial lag model (1),17,Bedrooms,bedrooms,A_structural,log,count,0.033,0.134,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,117.0,,se,"Santa Cruz only; Spatial lag model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.103",elasticity,0.033,0.134,b (log-log),reported,0.02380094535079756,0.09664626293960224,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2462686567164179,107.0,count,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c4,4,Spatial error model (1),17,Bedrooms,bedrooms,A_structural,log,count,0.028,0.136,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,117.0,,se,"Santa Cruz only; Spatial error model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.586",elasticity,0.028,0.136,b (log-log),reported,0.01989945715630465,0.09665450618776544,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.20588235294117646,107.0,count,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c7,4,"Spatial ARAR(1,1) model (1)",17,Bedrooms,bedrooms,A_structural,log,count,0.054,0.132,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,117.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; All variables; ML estimation, inverse-distance weights; log-likelihood -70.669",elasticity,0.054,0.132,b (log-log),reported,0.039517419007088266,0.09659813535066021,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.40909090909090906,107.0,count,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c1,4,Spatial lag model (1),18,Elevation (ft.),flood_risk,E_environment,log,"ft (first-floor height above base flood elevation), log",0.027,0.021,,,,,,high,flood protection measure; entered in logs per Eq. 4,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,117.0,,se,"Santa Cruz only; Spatial lag model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.103",elasticity,0.027,0.021,b (log-log),reported,0.12334555005453965,0.09593542782019752,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2857142857142856,107.0,ft log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c4,4,Spatial error model (1),18,Elevation (ft.),flood_risk,E_environment,log,"ft (first-floor height above base flood elevation), log",0.02,0.02,,,,,,high,flood protection measure; entered in logs per Eq. 4,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,117.0,,se,"Santa Cruz only; Spatial error model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.586",elasticity,0.02,0.02,b (log-log),reported,0.09622504486493763,0.09622504486493763,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,107.0,ft log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c7,4,"Spatial ARAR(1,1) model (1)",18,Elevation (ft.),flood_risk,E_environment,log,"ft (first-floor height above base flood elevation), log",0.036,0.02,,,*,,,high,flood protection measure; entered in logs per Eq. 4,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,117.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; All variables; ML estimation, inverse-distance weights; log-likelihood -70.669",elasticity,0.036,0.02,b (log-log),reported,0.17143634649587836,0.09524241471993242,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7999999999999998,107.0,ft log,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c1,4,Spatial lag model (1),18,Distance to water (ft.),water_proximity,E_environment,log,ft,-0.033,0.049,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,117.0,,se,"Santa Cruz only; Spatial lag model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.103",elasticity,-0.033,0.049,b (log-log),reported,-0.0649691901931334,0.09646940362010717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.673469387755102,107.0,ft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c4,4,Spatial error model (1),18,Distance to water (ft.),water_proximity,E_environment,log,ft,-0.03,0.059,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,117.0,,se,"Santa Cruz only; Spatial error model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.586",elasticity,-0.03,0.059,b (log-log),reported,-0.04909681161283754,0.0965570628385805,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5084745762711864,107.0,ft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c7,4,"Spatial ARAR(1,1) model (1)",18,Distance to water (ft.),water_proximity,E_environment,log,ft,-0.009,0.049,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,117.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; All variables; ML estimation, inverse-distance weights; log-likelihood -70.669",elasticity,-0.009,0.049,b (log-log),reported,-0.017753585956375002,0.0966584124291528,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.18367346938775508,107.0,ft,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c1,4,Spatial lag model (1),18,Built Post-FIRM,flood_risk,E_environment,binary,binary (built after Flood Insurance Rate Map publication),-0.426,0.29,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_lag,117.0,,se,"Santa Cruz only; Spatial lag model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.103",pct_premium,-37.37777882358231,18.940373921499592,100*(exp(b - se^2/2) - 1),reported,-0.1405996033133861,0.09571334497859617,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4689655172413794,107.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c4,4,Spatial error model (1),18,Built Post-FIRM,flood_risk,E_environment,binary,binary (built after Flood Insurance Rate Map publication),-0.449,0.312,,,,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,spatial_error,117.0,,se,"Santa Cruz only; Spatial error model; All variables; ML estimation, inverse-distance weights; log-likelihood -71.586",pct_premium,-39.20556920634717,19.913902279245587,100*(exp(b - se^2/2) - 1),reported,-0.1377961448173108,0.09575144138753001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.439102564102564,107.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d,11ddac3108d5fcc806866635ea2276160f2ca53d:T4-c7,4,"Spatial ARAR(1,1) model (1)",18,Built Post-FIRM,flood_risk,E_environment,binary,binary (built after Flood Insurance Rate Map publication),-0.512,0.302,,,*,,,high,,"ln(property price), owner-reported purchase price in 2014 US$",log,SAC,117.0,,se,"Santa Cruz only; Spatial ARAR(1,1) model; All variables; ML estimation, inverse-distance weights; log-likelihood -70.669",pct_premium,-42.74195331610673,18.09873279293526,100*(exp(b - se^2/2) - 1),reported,-0.16173910540265907,0.09540080045234968,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.695364238410596,107.0,binary,,2020.0,United States,North America,High income,1944.0,1999.0,single_family,transaction,journal,False,False,robust,,1971.5,spatial,journal,True,True,False
122e07c191e40cdc3321c3817fb731f2d55466e1,122e07c191e40cdc3321c3817fb731f2d55466e1,122e07c191e40cdc3321c3817fb731f2d55466e1:T9-SDM,9,1,11,Ar,living_area,A_structural,level,m2,0.0029,0.0002,13.05,0.0,,,,high,Building area in m2 (range 40-200),Ln unit listing price (yuan/m2),log,spatial_lag,429.0,0.9037,none,"Spatial Durbin model (coefficient, SE, t, p in separate columns); R2 from Table 7",semi_elasticity,0.29,0.02,100*b/1 (X per m2->m2),reported,0.5375778548110431,0.041193705349505214,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.05,419.0,m2,,2023.0,China,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,unknown,,2022.0,spatial,journal,True,True,False
122e07c191e40cdc3321c3817fb731f2d55466e1,122e07c191e40cdc3321c3817fb731f2d55466e1,122e07c191e40cdc3321c3817fb731f2d55466e1:T9-SDM,9,1,11,Ag,age,A_structural,level,years,-0.0157,0.001,-15.74,0.0,,,,high,"Age = 2022.4.1 minus year built, years",Ln unit listing price (yuan/m2),log,spatial_lag,429.0,0.9037,none,"Spatial Durbin model (coefficient, SE, t, p in separate columns); R2 from Table 7",semi_elasticity,-1.5699999999999998,0.1,100*b/1 (per year),reported,-0.6095705788818194,0.038727482775210896,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.74,419.0,years,,2023.0,China,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,unknown,,2022.0,spatial,journal,True,True,False
13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500:T2-c2,2,2,6,Rooms,bedrooms,A_structural,level,count,0.0112,,,0.0021,***,,,high,Number of main rooms,"log P (sale price, EUR)",log,spatial_error,24871.0,,p,"SEM, ML, W = 1 nearest neighbour; lambda 0.1609; year dummies included",semi_elasticity,1.1199999999999999,0.36414322947520283,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.01950311017235363,0.00634100493122458,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.075712822161009,24861.0,count,,2025.0,France,Europe,High income,2011.0,2016.0,single_family,transaction,journal,True,False,unknown,,2013.5,spatial,journal,True,True,False
13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500:T2-c2,2,2,6,Terrace,terrace_balcony,C_exterior,binary,binary,0.0688,,,0.0046,***,,,high,,"log P (sale price, EUR)",log,spatial_error,24871.0,,p,"SEM, ML, W = 1 nearest neighbour; lambda 0.1609; year dummies included",pct_premium,7.090627721014298,2.600762621934009,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01796957300869945,0.006341187193242696,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.833786870043548,24861.0,binary,,2025.0,France,Europe,High income,2011.0,2016.0,single_family,transaction,journal,True,False,unknown,,2013.5,spatial,journal,True,True,False
13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500:T2-c2,2,2,6,Swim,pool,C_exterior,binary,binary,0.1777,,,0.0068,***,,,high,,"log P (sale price, EUR)",log,spatial_error,24871.0,,p,"SEM, ML, W = 1 nearest neighbour; lambda 0.1609; year dummies included",pct_premium,19.189510887461147,7.842530270385172,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.017162560686599285,0.006341277114516502,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7064833119042557,24861.0,binary,,2025.0,France,Europe,High income,2011.0,2016.0,single_family,transaction,journal,True,False,unknown,,2013.5,spatial,journal,True,True,False
13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500:T2-c2,2,2,6,Bathroom,bathrooms,A_structural,binary,binary,0.0709,,,0.005,***,,,high,More than one bathroom/shower room,"log P (sale price, EUR)",log,spatial_error,24871.0,,p,"SEM, ML, W = 1 nearest neighbour; lambda 0.1609; year dummies included",pct_premium,7.313150807061541,2.711378055442943,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01779998058953763,0.0063412064330241056,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8070337683438042,24861.0,binary,,2025.0,France,Europe,High income,2011.0,2016.0,single_family,transaction,journal,True,False,unknown,,2013.5,spatial,journal,True,True,False
13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500:T2-c2,2,2,6,Garage,garage,A_structural,binary,binary,0.0331,,,0.0041,***,,,high,,"log P (sale price, EUR)",log,spatial_error,24871.0,,p,"SEM, ML, W = 1 nearest neighbour; lambda 0.1609; year dummies included",pct_premium,3.358517476147793,1.1919724621349144,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.018201436760968054,0.006341160593634446,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8703636333133575,24861.0,binary,,2025.0,France,Europe,High income,2011.0,2016.0,single_family,transaction,journal,True,False,unknown,,2013.5,spatial,journal,True,True,False
13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500:T2-c2,2,2,6,Condition,condition,A_structural,binary,binary,0.0579,,,0.005,***,,,high,House in good condition,"log P (sale price, EUR)",log,spatial_error,24871.0,,p,"SEM, ML, W = 1 nearest neighbour; lambda 0.1609; year dummies included",pct_premium,5.9383641236731455,2.1856296671762543,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01779998058953763,0.0063412064330241056,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8070337683438042,24861.0,binary,,2025.0,France,Europe,High income,2011.0,2016.0,single_family,transaction,journal,True,False,unknown,,2013.5,spatial,journal,True,True,False
13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500:T2-c1,2,1,6,social_compo_G2,demographics,F_neighbourhood,dummy,binary,0.0279,,,0.0006,***,,,high,IRIS social composition group 2 (least favourable socioeconomic conditions; ref. G1 mixed),"log P (sale price, EUR)",log,OLS,24871.0,,p,MCO (OLS) benchmark; year dummies included,pct_premium,2.82588646965074,0.8360313001531575,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.021758870772517914,0.006340709710725022,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.431614403623269,24861.0,binary,,2025.0,France,Europe,High income,2011.0,2016.0,single_family,transaction,journal,True,False,unknown,,2013.5,ols,journal,True,True,False
13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500:T2-c2,2,2,6,social_compo_G2,demographics,F_neighbourhood,dummy,binary,0.0318,,,0.0094,***,,,high,IRIS social composition group 2 (least favourable socioeconomic conditions; ref. G1 mixed),"log P (sale price, EUR)",log,spatial_error,24871.0,,p,"SEM, ML, W = 1 nearest neighbour; lambda 0.1609; year dummies included",pct_premium,3.2233643400298773,1.2639797700185942,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.016469459891849735,0.00634135104465227,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.597153158038555,24861.0,binary,,2025.0,France,Europe,High income,2011.0,2016.0,single_family,transaction,journal,True,False,unknown,,2013.5,spatial,journal,True,True,False
13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500:T2-c2,2,2,6,social_compo_G3,demographics,F_neighbourhood,dummy,binary,0.1615,,,0.0071,***,,,high,IRIS social composition group 3 (majority favourable socioeconomic conditions; ref. G1 mixed),"log P (sale price, EUR)",log,spatial_error,24871.0,,p,"SEM, ML, W = 1 nearest neighbour; lambda 0.1609; year dummies included",pct_premium,17.315957719369045,7.050454761239859,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01707148751253235,0.006341287002849209,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6921171530104133,24861.0,binary,,2025.0,France,Europe,High income,2011.0,2016.0,single_family,transaction,journal,True,False,unknown,,2013.5,spatial,journal,True,True,False
13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500:T2-c2,2,2,6,CatNat,flood_risk,E_environment,binary,binary,0.075,,,0.0066,***,,,high,Municipality with >= 9 natural-disaster (CatNat) declarations,"log P (sale price, EUR)",log,spatial_error,24871.0,,p,"SEM, ML, W = 1 nearest neighbour; lambda 0.1609; year dummies included",pct_premium,7.747337908915419,2.976067190605143,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01722530344014705,0.0063412702715614205,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7163805834608654,24861.0,binary,,2025.0,France,Europe,High income,2011.0,2016.0,single_family,transaction,journal,True,False,unknown,,2013.5,spatial,journal,True,True,False
13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500,13561959c7aabb108ebf10b83cf499e51f169500:T2-c2,2,2,6,PPRI,flood_risk,E_environment,binary,binary,-0.1153,,,0.0158,**,,,high,Located within a PPRI flood-risk prevention zone,"log P (sale price, EUR)",log,spatial_error,24871.0,,p,"SEM, ML, W = 1 nearest neighbour; lambda 0.1609; year dummies included",pct_premium,-10.991750032969916,4.2570359683815315,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.015305152629811861,0.006341468375839984,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4135029495884783,24861.0,binary,,2025.0,France,Europe,High income,2011.0,2016.0,single_family,transaction,journal,True,False,unknown,,2013.5,spatial,journal,True,True,False
13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526:T4-c1,4,1,19,Bedrooms,bedrooms,A_structural,level,count,0.142,0.00158,90.152,,***,,,high,Number of bedrooms; printed p-value '<2.00e-6',"log(house sale price), AUD",log,OLS,32050.0,0.8103,se,"Greater Sydney detached houses sold in two quarters of 2016 (APM); SE, t and p in separate columns; adj. R2 0.8102",semi_elasticity,14.2,0.158,100*b/1 (per unit count),reported,0.4498198295359178,0.004989571274468872,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),90.152,32040.0,count,,2022.0,Australia,Oceania,High income,2016.0,2016.0,single_family,transaction,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526:T4-c1,4,1,19,Bathrooms,bathrooms,A_structural,level,count,0.0489,0.00148,33.016,,***,,,high,Number of bathrooms; printed p-value '<2.00e-6',"log(house sale price), AUD",log,OLS,32050.0,0.8103,se,"Greater Sydney detached houses sold in two quarters of 2016 (APM); SE, t and p in separate columns; adj. R2 0.8102",semi_elasticity,4.89,0.148,100*b/1 (per unit count),reported,0.18139001186241188,0.005494003266973948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.016,32040.0,count,,2022.0,Australia,Oceania,High income,2016.0,2016.0,single_family,transaction,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526:T4-c1,4,1,19,Distance to Sydney,cbd_distance,D_location,level,m,-1.45e-05,1.69e-07,-85.66,,***,,,medium,"Network/Euclidean distance to Sydney CBD; distance unit not stated in the paper, coefficient magnitudes (1e-5 per unit) are consistent with metres; printed p-value '<2.00e-6'","log(house sale price), AUD",log,OLS,32050.0,0.8103,se,"Greater Sydney detached houses sold in two quarters of 2016 (APM); SE, t and p in separate columns; adj. R2 0.8102",semi_elasticity,-1.45,0.0169,100*b/0.001 (X per m->km),reported,-0.43167137653113336,0.005039357652709939,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-85.66,32040.0,m,,2022.0,Australia,Oceania,High income,2016.0,2016.0,single_family,transaction,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526:T4-c1,4,1,19,Distance to Beach,water_proximity,E_environment,level,m,-2.44e-06,2.24e-07,-10.916,,***,,,medium,"Distance to nearest beach; unit not stated, assumed metres; printed p-value '<2.00e-6'","log(house sale price), AUD",log,OLS,32050.0,0.8103,se,"Greater Sydney detached houses sold in two quarters of 2016 (APM); SE, t and p in separate columns; adj. R2 0.8102",semi_elasticity,-0.244,0.0224,100*b/0.001 (X per m->km),reported,-0.06087110493596404,0.005576319616706122,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.916,32040.0,m,,2022.0,Australia,Oceania,High income,2016.0,2016.0,single_family,transaction,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526:T4-c1,4,1,19,Distance to Bus Interchanges,transit_distance,D_location,level,m,2.91e-06,4.83e-07,6.031,1.65e-09,***,,,medium,"Distance to nearest bus interchange; unit not stated, assumed metres","log(house sale price), AUD",log,OLS,32050.0,0.8103,se,"Greater Sydney detached houses sold in two quarters of 2016 (APM); SE, t and p in separate columns; adj. R2 0.8102",semi_elasticity,0.29100000000000004,0.048299999999999996,100*b/0.001 (X per m->km),reported,0.03367415458346659,0.005583510957298391,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.031,32040.0,m,,2022.0,Australia,Oceania,High income,2016.0,2016.0,single_family,transaction,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526:T4-c1,4,1,19,Distance to Highway,highway_distance,D_location,level,m,7.5e-06,4.44e-07,16.883,,***,,,medium,"Distance to nearest highway/motorway; unit not stated, assumed metres; printed p-value '<2.00e-6'","log(house sale price), AUD",log,OLS,32050.0,0.8103,se,"Greater Sydney detached houses sold in two quarters of 2016 (APM); SE, t and p in separate columns; adj. R2 0.8102",semi_elasticity,0.75,0.0444,100*b/0.001 (X per m->km),reported,0.09390313982521951,0.005561993711142541,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.883,32040.0,m,,2022.0,Australia,Oceania,High income,2016.0,2016.0,single_family,transaction,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526:T4-c1,4,1,19,Distance to Primary School,school_distance,D_location,level,m,1.02e-05,3.26e-06,3.118,0.00182,**,,,medium,"Distance to nearest primary school; unit not stated, assumed metres","log(house sale price), AUD",log,OLS,32050.0,0.8103,se,"Greater Sydney detached houses sold in two quarters of 2016 (APM); SE, t and p in separate columns; adj. R2 0.8102",semi_elasticity,1.02,0.326,100*b/0.001 (X per m->km),reported,0.017416624073292905,0.005585831967059945,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.118,32040.0,m,,2022.0,Australia,Oceania,High income,2016.0,2016.0,single_family,transaction,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526:T4-c1,4,1,19,Distance to University,university_distance,D_location,level,m,1.12e-06,4.27e-07,2.617,0.00889,**,,,medium,"Distance to nearest university; unit not stated, assumed metres","log(house sale price), AUD",log,OLS,32050.0,0.8103,se,"Greater Sydney detached houses sold in two quarters of 2016 (APM); SE, t and p in separate columns; adj. R2 0.8102",semi_elasticity,0.11200000000000002,0.0427,100*b/0.001 (X per m->km),reported,0.014618777554039257,0.005586082366847252,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.617,32040.0,m,,2022.0,Australia,Oceania,High income,2016.0,2016.0,single_family,transaction,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526,13a61953f01e5f8f119d4fa1872eb72503252526:T4-c1,4,1,19,Distance to Shopping Centre,commercial_distance,D_location,level,m,1.11e-05,7.5e-07,14.774,,***,,,medium,"Distance to nearest shopping centre; unit not stated, assumed metres; printed p-value '<2.00e-6'","log(house sale price), AUD",log,OLS,32050.0,0.8103,se,"Greater Sydney detached houses sold in two quarters of 2016 (APM); SE, t and p in separate columns; adj. R2 0.8102",semi_elasticity,1.11,0.07500000000000001,100*b/0.001 (X per m->km),reported,0.08225788733360413,0.0055677465367269625,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.774,32040.0,m,,2022.0,Australia,Oceania,High income,2016.0,2016.0,single_family,transaction,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
14eecd7db66f7a02fa146490275ce97a19765a1a,14eecd7db66f7a02fa146490275ce97a19765a1a,14eecd7db66f7a02fa146490275ce97a19765a1a:T3-T1,3,T1,6,ln (network distance),transit_distance,D_location,log,ft,0.123,0.028,,,*,,,high,log of network distance (feet) to nearest light rail station; SE printed in table; * = p<0.05,"ln(sales price, 2005 constant USD)",log,OLS,1592.0,0.779,none,1997-1998 (pre-planning),elasticity,0.123,0.028,b (log-log),reported,0.10977693697165758,0.024989871830946444,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.392857142857142,1582.0,ft,,2012.0,United States,North America,High income,1997.0,2008.0,single_family,transaction,journal,False,True,unknown,,2002.5,ols,journal,True,True,False
14eecd7db66f7a02fa146490275ce97a19765a1a,14eecd7db66f7a02fa146490275ce97a19765a1a,14eecd7db66f7a02fa146490275ce97a19765a1a:T3-T2,3,T2,6,ln (network distance),transit_distance,D_location,log,ft,0.169,0.022,,,*,,,high,log of network distance (feet) to nearest light rail station; SE printed in table; * = p<0.05,"ln(sales price, 2005 constant USD)",log,OLS,2568.0,0.786,none,1999-2005 (planning),elasticity,0.169,0.022,b (log-log),reported,0.15016243610493318,0.01954777274738775,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.6818181818181825,2558.0,ft,,2012.0,United States,North America,High income,1997.0,2008.0,single_family,transaction,journal,False,True,unknown,,2002.5,ols,journal,True,True,False
14eecd7db66f7a02fa146490275ce97a19765a1a,14eecd7db66f7a02fa146490275ce97a19765a1a,14eecd7db66f7a02fa146490275ce97a19765a1a:T3-T3,3,T3,6,ln (network distance),transit_distance,D_location,log,ft,0.148,0.027,,,*,,,high,log of network distance (feet) to nearest light rail station; SE printed in table; * = p<0.05,"ln(sales price, 2005 constant USD)",log,OLS,1308.0,0.811,none,2005-2007 (construction),elasticity,0.148,0.027,b (log-log),reported,0.15041504835770125,0.027440583146337395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.481481481481481,1298.0,ft,,2012.0,United States,North America,High income,1997.0,2008.0,single_family,transaction,journal,False,True,unknown,,2002.5,ols,journal,True,True,False
14eecd7db66f7a02fa146490275ce97a19765a1a,14eecd7db66f7a02fa146490275ce97a19765a1a,14eecd7db66f7a02fa146490275ce97a19765a1a:T3-T4,3,T4,6,ln (network distance),transit_distance,D_location,log,ft,0.052,0.033,,,,,,high,log of network distance (feet) to nearest light rail station; SE printed in table; * = p<0.05,"ln(sales price, 2005 constant USD)",log,OLS,913.0,0.837,none,2007-2008 (operation),elasticity,0.052,0.033,b (log-log),reported,0.05236598178935655,0.03323225767401474,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5757575757575757,903.0,ft,,2012.0,United States,North America,High income,1997.0,2008.0,single_family,transaction,journal,False,True,unknown,,2002.5,ols,journal,True,True,False
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T6-c1,6,1,18,log(LIVAREA),living_area,A_structural,log,sqft,0.803,0.004,,,***,0.796,0.81,high,air-conditioned living area in sq ft,"log(JMV, just market value USD)",log,OLS,30555.0,0.911,se,Full cleaned sample; log-log model; HC2 robust SEs; adjusted R2 0.911,elasticity,0.803,0.004,b (log-log),reported,0.7542220543122693,0.003757021441157008,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),200.75,30545.0,sqft,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,ols,journal,True,True,False
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T6-c1,6,1,18,log(ACREAGE),lot_size,A_structural,log,acres,0.078,0.001,,,***,0.075,0.08,high,,"log(JMV, just market value USD)",log,OLS,30555.0,0.911,se,Full cleaned sample; log-log model; HC2 robust SEs; adjusted R2 0.911,elasticity,0.078,0.001,b (log-log),reported,0.40755110179042103,0.005225014125518219,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),78.0,30545.0,acre,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,ols,journal,True,True,False
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T6-c1,6,1,18,log(MHHI),income,F_neighbourhood,log,currency,0.222,0.004,,,***,0.214,0.23,high,"median household income by zip code, USD","log(JMV, just market value USD)",log,OLS,30555.0,0.911,se,Full cleaned sample; log-log model; HC2 robust SEs; adjusted R2 0.911,elasticity,0.222,0.004,b (log-log),reported,0.3026636200063351,0.005453398558672705,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),55.5,30545.0,currency,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,ols,journal,True,True,False
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T6-c1,6,1,18,log(NBEDS),bedrooms,A_structural,log,count,0.042,0.003,,,***,0.034,0.049,high,,"log(JMV, just market value USD)",log,OLS,30555.0,0.911,se,Full cleaned sample; log-log model; HC2 robust SEs; adjusted R2 0.911,elasticity,0.042,0.003,b (log-log),reported,0.07984891885448572,0.005703494203891837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.0,30545.0,count,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,ols,journal,True,True,False
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T6-c1,6,1,18,log(NBATHS),bathrooms,A_structural,log,count,-0.06,0.004,,,***,-0.067,-0.052,high,,"log(JMV, just market value USD)",log,OLS,30555.0,0.911,se,Full cleaned sample; log-log model; HC2 robust SEs; adjusted R2 0.911,elasticity,-0.06,0.004,b (log-log),reported,-0.08551208798801606,0.005700805865867737,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.0,30545.0,count,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,ols,journal,True,True,False
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T6-c1,6,1,18,log(AGE),age,A_structural,log,years,-0.173,0.002,,,***,-0.177,-0.168,high,see study note on years vs decades,"log(JMV, just market value USD)",log,OLS,30555.0,0.911,se,Full cleaned sample; log-log model; HC2 robust SEs; adjusted R2 0.911,elasticity,-0.173,0.002,b (log-log),reported,-0.443576620215228,0.00512805341289281,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-86.49999999999999,30545.0,years,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,ols,journal,True,True,False
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T6-c1,6,1,18,Pool,pool,C_exterior,binary,binary,0.024,0.002,,,***,0.02,0.028,high,,"log(JMV, just market value USD)",log,OLS,30555.0,0.911,se,Full cleaned sample; log-log model; HC2 robust SEs; adjusted R2 0.911,pct_premium,2.4288269312034316,0.2048580635781243,100*(exp(b - se^2/2) - 1),reported,0.06849989053107838,0.005708324210923199,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,30545.0,binary,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,ols,journal,True,True,False
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T4-c1,4,Production frontier,17,log(LIVAREA),living_area,A_structural,log,sqft,0.8086,0.0032,,,***,,,high,,"log(JMV, just market value USD)",log,other,30555.0,,se,"Stochastic frontier analysis (SFA) production-frontier equation; Wald chi2(6)=253,536; log-likelihood 20,211",elasticity,0.8086,0.0032,b (log-log),reported,0.8224453050765427,0.0032547922041119668,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),252.68749999999997,30545.0,sqft,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,other,journal,True,True,False
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T4-c1,4,Production frontier,17,log(NBEDS),bedrooms,A_structural,log,count,0.048,0.0032,,,***,,,high,,"log(JMV, just market value USD)",log,other,30555.0,,se,"Stochastic frontier analysis (SFA) production-frontier equation; Wald chi2(6)=253,536; log-likelihood 20,211",elasticity,0.048,0.0032,b (log-log),reported,0.08551208798801606,0.005700805865867737,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.0,30545.0,count,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,other,journal,True,True,False
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T4-c1,4,Production frontier,17,log(NBATHS),bathrooms,A_structural,log,count,-0.0615,0.0038,,,***,,,high,,"log(JMV, just market value USD)",log,other,30555.0,,se,"Stochastic frontier analysis (SFA) production-frontier equation; Wald chi2(6)=253,536; log-likelihood 20,211",elasticity,-0.0615,0.0038,b (log-log),reported,-0.09220772726035974,0.005697388025843367,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.184210526315788,30545.0,count,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,other,journal,True,True,True
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T4-c1,4,Production frontier,17,log(MHHI),income,F_neighbourhood,log,currency,0.2214,0.0037,,,***,,,high,"median household income by zip code, USD","log(JMV, just market value USD)",log,other,30555.0,,se,"Stochastic frontier analysis (SFA) production-frontier equation; Wald chi2(6)=253,536; log-likelihood 20,211",elasticity,0.2214,0.0037,b (log-log),reported,0.3239186513302515,0.005413274660893995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),59.83783783783784,30545.0,currency,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,other,journal,True,True,False
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T4-c1,4,Production frontier,17,log(ACREAGE),lot_size,A_structural,log,acres,0.075,0.0013,,,***,,,high,,"log(JMV, just market value USD)",log,other,30555.0,,se,"Stochastic frontier analysis (SFA) production-frontier equation; Wald chi2(6)=253,536; log-likelihood 20,211",elasticity,0.075,0.0013,b (log-log),reported,0.31346459867719695,0.005433386377071414,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),57.69230769230769,30545.0,acre,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,other,journal,True,True,False
154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3,154f55871a6811fb1dd94f5c020e97dabe79c8c3:T4-c1,4,Production frontier,17,log(AGE),age,A_structural,log,years,-0.196,0.0024,,,***,,,medium,Table cell is typeset as '-8***' (typo); value -0.196 taken from the text on p. 19 ('a 1% increase in the age of the property reduces the JMV by 0.196%'); SE as printed in table,"log(JMV, just market value USD)",log,other,30555.0,,se,"Stochastic frontier analysis (SFA) production-frontier equation; Wald chi2(6)=253,536; log-likelihood 20,211",elasticity,-0.196,0.0024,b (log-log),reported,-0.4233397603728087,0.00518375216783031,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-81.66666666666667,30545.0,years,,2024.0,United States,North America,High income,,,single_family,appraisal,journal,False,True,robust,,2021.0,other,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c1,A.2,1 (S.Main),52,Type of Dwelling: House (ref. Flat),dwelling_type,A_structural,dummy,binary,0.493,0.014,,,***,,,high,house vs flat; in models with interaction the house effect also depends on surface,log advertised sales price (EUR),log,OLS,14759.0,0.824,se,"Sales adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,63.70600816397503,2.292108729944838,100*(exp(b - se^2/2) - 1),reported,0.2784887197851878,0.007908401778889714,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.214285714285715,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c2,A.2,2 (S.Alt.1),52,Type of Dwelling: House (ref. Flat),dwelling_type,A_structural,dummy,binary,0.543,0.018,,,***,,,high,house vs flat; in models with interaction the house effect also depends on surface,log advertised sales price (EUR),log,OLS,14759.0,0.703,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,72.08838067707653,3.0980927025542138,100*(exp(b - se^2/2) - 1),reported,0.24107097658648488,0.007991303091264692,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.16666666666667,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c3,A.2,3 (S.Alt.2),52,Type of Dwelling: House (ref. Flat),dwelling_type,A_structural,dummy,binary,0.488,0.014,,,***,,,high,house vs flat; in models with interaction the house effect also depends on surface,log advertised sales price (EUR),log,other,14759.0,0.819,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + linked-neighbour Markov random field spline (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,62.88952104197427,2.2806767899616043,100*(exp(b - se^2/2) - 1),reported,0.27588027432962026,0.007914598034046485,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.857142857142854,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c4,A.2,4 (S.Alt.3),52,Type of Dwelling: House (ref. Flat),dwelling_type,A_structural,dummy,binary,0.031,0.006,,,***,,,high,house vs flat; in models with interaction the house effect also depends on surface,log advertised sales price (EUR),log,OLS,14759.0,0.809,se,"Sales adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,3.1466937314552412,0.6188913023319136,100*(exp(b - se^2/2) - 1),reported,0.04250465473018455,0.00822670736713249,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.166666666666667,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c5,A.2,5 (S.Alt.4),52,Type of Dwelling: House (ref. Flat),dwelling_type,A_structural,dummy,binary,-0.103,0.009,,,***,,,high,house vs flat; in models with interaction the house effect also depends on surface,log advertised sales price (EUR),log,OLS,14759.0,0.507,se,"Sales adverts 2018, Luxembourg; physical characteristics only; n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-9.79095619210626,0.8119142761333648,100*(exp(b - se^2/2) - 1),reported,-0.09381960712629994,0.008197829748899994,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.444444444444445,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c6,A.2,6 (R.Main),52,Type of Dwelling: House (ref. Flat),dwelling_type,A_structural,dummy,binary,0.265,0.025,,,***,,,high,house vs flat; in models with interaction the house effect also depends on surface,log advertised monthly rent (EUR),log,OLS,7860.0,0.744,se,"Rent adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,30.30237172358996,3.258577439445922,100*(exp(b - se^2/2) - 1),reported,0.11879138903676556,0.011206734814789203,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.6,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c7,A.2,7 (R.Alt.1),52,Type of Dwelling: House (ref. Flat),dwelling_type,A_structural,dummy,binary,0.31,0.027,,,***,,,high,house vs flat; in models with interaction the house effect also depends on surface,log advertised monthly rent (EUR),log,OLS,7860.0,0.679,se,"Rent adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,36.29282362395738,3.68124780815688,100*(exp(b - se^2/2) - 1),reported,0.12851293573377348,0.011193062144554466,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.481481481481481,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c9,A.2,9 (R.Alt.3),52,Type of Dwelling: House (ref. Flat),dwelling_type,A_structural,dummy,binary,0.239,0.012,,,***,,,high,house vs flat; in models with interaction the house effect also depends on surface,log advertised monthly rent (EUR),log,OLS,7860.0,0.742,se,"Rent adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,26.98871014209079,1.5239742439006039,100*(exp(b - se^2/2) - 1),reported,0.21931950234270448,0.011011857858211105,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.916666666666664,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c10,A.2,10 (R.Alt.4),52,Type of Dwelling: House (ref. Flat),dwelling_type,A_structural,dummy,binary,0.082,0.016,,,***,,,high,house vs flat; in models with interaction the house effect also depends on surface,log advertised monthly rent (EUR),log,OLS,7860.0,0.526,se,"Rent adverts 2018, Luxembourg; physical characteristics only; n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,8.531688037756545,1.7367292957272784,100*(exp(b - se^2/2) - 1),reported,0.057747567163375285,0.011267817983097615,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.125,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c1,A.2,1 (S.Main),52,Number of bedrooms: 2 (ref. 1),bedrooms,A_structural,dummy,binary,0.143,0.006,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,OLS,14759.0,0.824,se,"Sales adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,15.370903471648356,0.6922378809996064,100*(exp(b - se^2/2) - 1),reported,0.19257394934842662,0.008080025846787131,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.833333333333332,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c2,A.2,2 (S.Alt.1),52,Number of bedrooms: 2 (ref. 1),bedrooms,A_structural,dummy,binary,0.1,0.008,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,OLS,14759.0,0.703,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,10.513555317211075,0.8841367344605182,100*(exp(b - se^2/2) - 1),reported,0.10238595385961516,0.008190876308769213,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.5,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c3,A.2,3 (S.Alt.2),52,Number of bedrooms: 2 (ref. 1),bedrooms,A_structural,dummy,binary,0.143,0.006,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,other,14759.0,0.819,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + linked-neighbour Markov random field spline (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,15.370903471648356,0.6922378809996064,100*(exp(b - se^2/2) - 1),reported,0.19257394934842662,0.008080025846787131,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.833333333333332,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c4,A.2,4 (S.Alt.3),52,Number of bedrooms: 2 (ref. 1),bedrooms,A_structural,dummy,binary,0.242,0.005,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,OLS,14759.0,0.809,se,"Sales adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,27.37782704882994,0.6368970964080974,100*(exp(b - se^2/2) - 1),reported,0.3702154250256378,0.007649079029455326,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),48.4,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c5,A.2,5 (S.Alt.4),52,Number of bedrooms: 2 (ref. 1),bedrooms,A_structural,dummy,binary,0.181,0.009,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,OLS,14759.0,0.507,se,"Sales adverts 2018, Luxembourg; physical characteristics only; n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,19.83666444612753,1.0785736613638797,100*(exp(b - se^2/2) - 1),reported,0.16337297139003842,0.0081235179144218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.11111111111111,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c6,A.2,6 (R.Main),52,Number of bedrooms: 2 (ref. 1),bedrooms,A_structural,dummy,binary,0.119,0.006,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised monthly rent (EUR),log,OLS,7860.0,0.744,se,"Rent adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,12.634964381229462,0.6758219509730118,100*(exp(b - se^2/2) - 1),reported,0.21844572425099582,0.011014070130302311,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.833333333333332,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c7,A.2,7 (R.Alt.1),52,Number of bedrooms: 2 (ref. 1),bedrooms,A_structural,dummy,binary,0.112,0.007,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised monthly rent (EUR),log,OLS,7860.0,0.679,se,"Rent adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,11.848545741565042,0.7829590024515317,100*(exp(b - se^2/2) - 1),reported,0.17771197071360278,0.011106998169600174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.0,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c9,A.2,9 (R.Alt.3),52,Number of bedrooms: 2 (ref. 1),bedrooms,A_structural,dummy,binary,0.12,0.006,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised monthly rent (EUR),log,OLS,7860.0,0.742,se,"Rent adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,12.747655681870063,0.6764981109476255,100*(exp(b - se^2/2) - 1),reported,0.22019275302527214,0.011009637651263606,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.0,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c10,A.2,10 (R.Alt.4),52,Number of bedrooms: 2 (ref. 1),bedrooms,A_structural,dummy,binary,0.092,0.008,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised monthly rent (EUR),log,OLS,7860.0,0.526,se,"Rent adverts 2018, Luxembourg; physical characteristics only; n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,9.632973896784325,0.8770918576646535,100*(exp(b - se^2/2) - 1),reported,0.12871678318227486,0.011192763754980423,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.5,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c1,A.2,1 (S.Main),52,Number of bedrooms: 3 (ref. 1),bedrooms,A_structural,dummy,binary,0.182,0.008,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,OLS,14759.0,0.824,se,"Sales adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,19.95758068398601,0.9596913551038947,100*(exp(b - se^2/2) - 1),reported,0.18412415679466407,0.008093369529435783,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.75,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c2,A.2,2 (S.Alt.1),52,Number of bedrooms: 3 (ref. 1),bedrooms,A_structural,dummy,binary,0.122,0.011,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,OLS,14759.0,0.703,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,12.968575372471047,1.2427295119583506,100*(exp(b - se^2/2) - 1),reported,0.09094573485417047,0.00820002527373668,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.090909090909092,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c3,A.2,3 (S.Alt.2),52,Number of bedrooms: 3 (ref. 1),bedrooms,A_structural,dummy,binary,0.183,0.008,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,other,14759.0,0.819,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + linked-neighbour Markov random field spline (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,20.077598263458274,0.9606515264646646,100*(exp(b - se^2/2) - 1),reported,0.185101257104707,0.008091858234085552,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.875,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c4,A.2,4 (S.Alt.3),52,Number of bedrooms: 3 (ref. 1),bedrooms,A_structural,dummy,binary,0.375,0.006,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,OLS,14759.0,0.809,se,"Sales adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,45.49652250084453,0.8729948487709208,100*(exp(b - se^2/2) - 1),reported,0.45759311420585436,0.00732148982729367,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),62.5,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c5,A.2,5 (S.Alt.4),52,Number of bedrooms: 3 (ref. 1),bedrooms,A_structural,dummy,binary,0.32,0.01,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,OLS,14759.0,0.507,se,"Sales adverts 2018, Luxembourg; physical characteristics only; n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,37.70589096691212,1.3771277643359572,100*(exp(b - se^2/2) - 1),reported,0.2547961295766584,0.007962379049270574,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.0,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c6,A.2,6 (R.Main),52,Number of bedrooms: 3 (ref. 1),bedrooms,A_structural,dummy,binary,0.165,0.01,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised monthly rent (EUR),log,OLS,7860.0,0.744,se,"Rent adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,17.933415052967195,1.1793931187113906,100*(exp(b - se^2/2) - 1),reported,0.18308205049265489,0.01109588184803969,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.5,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c7,A.2,7 (R.Alt.1),52,Number of bedrooms: 3 (ref. 1),bedrooms,A_structural,dummy,binary,0.146,0.011,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised monthly rent (EUR),log,OLS,7860.0,0.679,se,"Rent adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,15.712617979919008,1.2729158068558757,100*(exp(b - se^2/2) - 1),reported,0.14815152320497843,0.011162101063388786,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.272727272727273,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c9,A.2,9 (R.Alt.3),52,Number of bedrooms: 3 (ref. 1),bedrooms,A_structural,dummy,binary,0.166,0.009,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised monthly rent (EUR),log,OLS,7860.0,0.742,se,"Rent adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,18.052528948086067,1.0625157915509484,100*(exp(b - se^2/2) - 1),reported,0.20380666878430775,0.011049759150956443,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.444444444444446,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c10,A.2,10 (R.Alt.4),52,Number of bedrooms: 3 (ref. 1),bedrooms,A_structural,dummy,binary,0.154,0.013,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised monthly rent (EUR),log,OLS,7860.0,0.526,se,"Rent adverts 2018, Luxembourg; physical characteristics only; n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,16.63923224629078,1.5164381528119715,100*(exp(b - se^2/2) - 1),reported,0.1325241335717461,0.011187102184627918,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.846153846153847,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c1,A.2,1 (S.Main),52,Number of bedrooms: 4+ (ref. 1),bedrooms,A_structural,dummy,binary,0.226,0.01,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,OLS,14759.0,0.824,se,"Sales adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,25.35129880618665,1.2535756652781869,100*(exp(b - se^2/2) - 1),reported,0.18295091569150435,0.008095173260686034,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.6,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c2,A.2,2 (S.Alt.1),52,Number of bedrooms: 4+ (ref. 1),bedrooms,A_structural,dummy,binary,0.15,0.013,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,OLS,14759.0,0.703,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,16.173607188254913,1.510384515546768,100*(exp(b - se^2/2) - 1),reported,0.09458347606654768,0.008197234592434132,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.538461538461538,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c3,A.2,3 (S.Alt.2),52,Number of bedrooms: 4+ (ref. 1),bedrooms,A_structural,dummy,binary,0.224,0.01,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,other,14759.0,0.819,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + linked-neighbour Markov random field spline (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,25.100846744120364,1.2510710194283623,100*(exp(b - se^2/2) - 1),reported,0.18138537824958534,0.008097561528999346,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.4,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c4,A.2,4 (S.Alt.3),52,Number of bedrooms: 4+ (ref. 1),bedrooms,A_structural,dummy,binary,0.419,0.008,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,OLS,14759.0,0.809,se,"Sales adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,52.039170147730005,1.216352283832157,100*(exp(b - se^2/2) - 1),reported,0.39600672018691796,0.007560987497602252,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),52.375,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c5,A.2,5 (S.Alt.4),52,Number of bedrooms: 4+ (ref. 1),bedrooms,A_structural,dummy,binary,0.372,0.013,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised sales price (EUR),log,OLS,14759.0,0.507,se,"Sales adverts 2018, Luxembourg; physical characteristics only; n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,45.051040798503486,1.8858228756811064,100*(exp(b - se^2/2) - 1),reported,0.22934295532672716,0.008014673170020034,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.615384615384617,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c6,A.2,6 (R.Main),52,Number of bedrooms: 4+ (ref. 1),bedrooms,A_structural,dummy,binary,-0.137,0.009,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised monthly rent (EUR),log,OLS,7860.0,0.744,se,"Rent adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-12.806508794693395,0.7847732035188983,100*(exp(b - se^2/2) - 1),reported,-0.169327019503196,0.011123672814078568,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.222222222222225,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c7,A.2,7 (R.Alt.1),52,Number of bedrooms: 4+ (ref. 1),bedrooms,A_structural,dummy,binary,-0.135,0.01,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised monthly rent (EUR),log,OLS,7860.0,0.679,se,"Rent adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-12.63277730154233,0.8737159116880345,100*(exp(b - se^2/2) - 1),reported,-0.1506312776851143,0.01115787242111958,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.5,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c9,A.2,9 (R.Alt.3),52,Number of bedrooms: 4+ (ref. 1),bedrooms,A_structural,dummy,binary,-0.145,0.009,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised monthly rent (EUR),log,OLS,7860.0,0.742,se,"Rent adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-13.501273958271288,0.7785200637996671,100*(exp(b - se^2/2) - 1),reported,-0.17890671255793433,0.011104554572561442,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.11111111111111,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c10,A.2,10 (R.Alt.4),52,Number of bedrooms: 4+ (ref. 1),bedrooms,A_structural,dummy,binary,-0.109,0.012,,,***,,,high,bedroom-count category dummy; reference = 1 bedroom,log advertised monthly rent (EUR),log,OLS,7860.0,0.526,se,"Rent adverts 2018, Luxembourg; physical characteristics only; n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-10.333414476755499,1.0760765009978825,100*(exp(b - se^2/2) - 1),reported,-0.10198587384459472,0.011227802625092995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.083333333333334,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c1,A.2,1 (S.Main),52,Energy Efficiency Class: medium (E-G) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.063,0.019,,,***,,,high,energy passport class E-G vs H-I,log advertised sales price (EUR),log,OLS,14759.0,0.824,se,"Sales adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,6.483461923520073,2.0235509945394803,100*(exp(b - se^2/2) - 1),reported,0.02729253345060239,0.00823108151684834,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3157894736842106,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c2,A.2,2 (S.Alt.1),52,Energy Efficiency Class: medium (E-G) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.083,0.024,,,***,,,high,energy passport class E-G vs H-I,log advertised sales price (EUR),log,OLS,14759.0,0.703,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,8.622892956411254,2.6077003405157715,100*(exp(b - se^2/2) - 1),reported,0.028464892497306646,0.008230812288377826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4583333333333335,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c3,A.2,3 (S.Alt.2),52,Energy Efficiency Class: medium (E-G) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.068,0.018,,,***,,,high,energy passport class E-G vs H-I,log advertised sales price (EUR),log,other,14759.0,0.819,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + linked-neighbour Markov random field spline (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,7.019192334337587,1.9266575552617935,100*(exp(b - se^2/2) - 1),reported,0.031091745400222855,0.008230167900058991,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.777777777777778,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c4,A.2,4 (S.Alt.3),52,Energy Efficiency Class: medium (E-G) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.032,0.006,,,***,,,high,energy passport class E-G vs H-I,log advertised sales price (EUR),log,OLS,14759.0,0.809,se,"Sales adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,3.2498920157289835,0.619510503183071,100*(exp(b - se^2/2) - 1),reported,0.043873174581596494,0.008226220234049344,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.333333333333333,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c5,A.2,5 (S.Alt.4),52,Energy Efficiency Class: medium (E-G) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.155,0.01,,,***,,,high,energy passport class E-G vs H-I,log advertised sales price (EUR),log,OLS,14759.0,0.507,se,"Sales adverts 2018, Luxembourg; physical characteristics only; n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,16.759957966661787,1.167657961105125,100*(exp(b - se^2/2) - 1),reported,0.1266023440146963,0.008167893162238472,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.5,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c6,A.2,6 (R.Main),52,Energy Efficiency Class: medium (E-G) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.317,0.045,,,***,,,high,energy passport class E-G vs H-I,log advertised monthly rent (EUR),log,OLS,7860.0,0.744,se,"Rent adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,37.16131103550055,6.178511573664564,100*(exp(b - se^2/2) - 1),reported,0.07925807730502528,0.011251146620587182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.044444444444445,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c7,A.2,7 (R.Alt.1),52,Energy Efficiency Class: medium (E-G) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.25,0.048,,,***,,,high,energy passport class E-G vs H-I,log advertised monthly rent (EUR),log,OLS,7860.0,0.679,se,"Rent adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,28.254707109827002,6.163322000101159,100*(exp(b - se^2/2) - 1),reported,0.05868334416172844,0.011267202079051861,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.208333333333333,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c9,A.2,9 (R.Alt.3),52,Energy Efficiency Class: medium (E-G) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.032,0.01,,,**,,,high,energy passport class E-G vs H-I,log advertised monthly rent (EUR),log,OLS,7860.0,0.742,se,"Rent adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,3.2465880720478513,1.0325175053051183,100*(exp(b - se^2/2) - 1),reported,0.03609375573809582,0.011279298668154943,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c10,A.2,10 (R.Alt.4),52,Energy Efficiency Class: medium (E-G) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.243,0.012,,,***,,,high,energy passport class E-G vs H-I,log advertised monthly rent (EUR),log,OLS,7860.0,0.526,se,"Rent adverts 2018, Luxembourg; physical characteristics only; n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,27.49768224824216,1.5300823489421518,100*(exp(b - se^2/2) - 1),reported,0.22280932391732255,0.011002929576164076,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.25,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c1,A.2,1 (S.Main),52,Energy Efficiency Class: high (A-D) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.157,0.061,,,*,,,high,energy passport class A-D vs H-I,log advertised sales price (EUR),log,OLS,14759.0,0.824,se,"Sales adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,16.782086075268545,7.1369732447955725,100*(exp(b - se^2/2) - 1),reported,0.02118805165382723,0.008232300324098479,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5737704918032787,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c2,A.2,2 (S.Alt.1),52,Energy Efficiency Class: high (A-D) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.268,0.077,,,***,,,high,energy passport class A-D vs H-I,log advertised sales price (EUR),log,OLS,14759.0,0.703,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,30.34772483993431,10.066572978115008,100*(exp(b - se^2/2) - 1),reported,0.02864735312473659,0.00823076936792805,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.480519480519481,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c3,A.2,3 (S.Alt.2),52,Energy Efficiency Class: high (A-D) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.141,0.06,,,*,,,high,energy passport class A-D vs H-I,log advertised sales price (EUR),log,other,14759.0,0.819,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + linked-neighbour Markov random field spline (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,14.935394780762001,6.9085478879084645,100*(exp(b - se^2/2) - 1),reported,0.019346628076281472,0.008232607692034669,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3499999999999996,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c4,A.2,4 (S.Alt.3),52,Energy Efficiency Class: high (A-D) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.132,0.007,,,***,,,high,energy passport class A-D vs H-I,log advertised sales price (EUR),log,OLS,14759.0,0.809,se,"Sales adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,14.10803624558854,0.7987758234870646,100*(exp(b - se^2/2) - 1),reported,0.15343392474270154,0.008136647524234172,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.857142857142858,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c5,A.2,5 (S.Alt.4),52,Energy Efficiency Class: high (A-D) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.217,0.011,,,***,,,high,energy passport class A-D vs H-I,log advertised sales price (EUR),log,OLS,14759.0,0.507,se,"Sales adverts 2018, Luxembourg; physical characteristics only; n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,24.22689425931839,1.3665785123515402,100*(exp(b - se^2/2) - 1),reported,0.16033577201651952,0.00812761977963924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.727272727272727,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c6,A.2,6 (R.Main),52,Energy Efficiency Class: high (A-D) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.358,0.106,,,***,,,high,energy passport class A-D vs H-I,log advertised monthly rent (EUR),log,OLS,7860.0,0.744,se,"Rent adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,42.24517965331391,15.162935577086918,100*(exp(b - se^2/2) - 1),reported,0.0380914086269604,0.011278461772228498,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3773584905660377,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,True
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c7,A.2,7 (R.Alt.1),52,Energy Efficiency Class: high (A-D) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.285,0.116,,,*,,,high,energy passport class A-D vs H-I,log advertised monthly rent (EUR),log,OLS,7860.0,0.679,se,"Rent adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,32.08454183065908,15.425239526209095,100*(exp(b - se^2/2) - 1),reported,0.027719483189996105,0.011282315965051049,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4568965517241375,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c9,A.2,9 (R.Alt.3),52,Energy Efficiency Class: high (A-D) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.123,0.013,,,***,,,high,energy passport class A-D vs H-I,log advertised monthly rent (EUR),log,OLS,7860.0,0.742,se,"Rent adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,13.078886525120437,1.470149747231736,100*(exp(b - se^2/2) - 1),reported,0.10618535325422836,0.011222842213861535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.461538461538462,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c10,A.2,10 (R.Alt.4),52,Energy Efficiency Class: high (A-D) (ref. low H-I),energy_efficiency,A_structural,dummy,binary,0.29,0.016,,,***,,,high,energy passport class A-D vs H-I,log advertised monthly rent (EUR),log,OLS,7860.0,0.526,se,"Rent adverts 2018, Luxembourg; physical characteristics only; n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,33.62564362545517,2.138283980840755,100*(exp(b - se^2/2) - 1),reported,0.20041986782221133,0.011057647879846142,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.125,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c1,A.2,1 (S.Main),52,Dwelling State: new-build (ref. planned),condition,A_structural,dummy,binary,0.009,0.014,,,,,,high,state of dwelling: new-build vs planned (off-plan),log advertised sales price (EUR),log,OLS,14759.0,0.824,se,"Sales adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,0.8941740638188866,1.412656870483415,100*(exp(b - se^2/2) - 1),reported,0.00529330722866528,0.008234033466812658,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6428571428571428,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c2,A.2,2 (S.Alt.1),52,Dwelling State: new-build (ref. planned),condition,A_structural,dummy,binary,-0.043,0.018,,,*,,,high,state of dwelling: new-build vs planned (off-plan),log advertised sales price (EUR),log,OLS,14759.0,0.703,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-4.224377900912568,1.724240502120655,100*(exp(b - se^2/2) - 1),reported,-0.019666662220070415,0.00823255627816901,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.388888888888889,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c3,A.2,3 (S.Alt.2),52,Dwelling State: new-build (ref. planned),condition,A_structural,dummy,binary,0.003,0.014,,,,,,high,state of dwelling: new-build vs planned (off-plan),log advertised sales price (EUR),log,other,14759.0,0.819,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + linked-neighbour Markov random field spline (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,0.29062148782059705,1.4042063063047279,100*(exp(b - se^2/2) - 1),reported,0.001764457715700655,0.008234136006603056,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.21428571428571427,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c4,A.2,4 (S.Alt.3),52,Dwelling State: new-build (ref. planned),condition,A_structural,dummy,binary,0.016,0.015,,,,,,high,state of dwelling: new-build vs planned (off-plan),log advertised sales price (EUR),log,OLS,14759.0,0.809,se,"Sales adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,1.601437735893474,1.5241930281091425,100*(exp(b - se^2/2) - 1),reported,0.008782753323154825,0.008233831240457649,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0666666666666667,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c5,A.2,5 (S.Alt.4),52,Dwelling State: new-build (ref. planned),condition,A_structural,dummy,binary,-0.021,0.024,,,,,,high,state of dwelling: new-build vs planned (off-plan),log advertised sales price (EUR),log,OLS,14759.0,0.507,se,"Sales adverts 2018, Luxembourg; physical characteristics only; n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-2.1063009886065798,2.350125514966703,100*(exp(b - se^2/2) - 1),reported,-0.007204693224839902,0.008233935114102746,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.875,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c6,A.2,6 (R.Main),52,Dwelling State: new-build (ref. planned),condition,A_structural,dummy,binary,-0.006,0.019,,,,,,high,state of dwelling: new-build vs planned (off-plan),log advertised monthly rent (EUR),log,OLS,7860.0,0.744,se,"Rent adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-0.6161439996873797,1.8886341317024768,100*(exp(b - se^2/2) - 1),reported,-0.0035641835589396826,0.01128658126997566,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.31578947368421056,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c7,A.2,7 (R.Alt.1),52,Dwelling State: new-build (ref. planned),condition,A_structural,dummy,binary,-0.029,0.022,,,,,,high,state of dwelling: new-build vs planned (off-plan),log advertised monthly rent (EUR),log,OLS,7860.0,0.679,se,"Rent adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-2.8818589875073575,2.1371162218265303,100*(exp(b - se^2/2) - 1),reported,-0.014876214380126363,0.011285404012509654,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3181818181818183,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c9,A.2,9 (R.Alt.3),52,Dwelling State: new-build (ref. planned),condition,A_structural,dummy,binary,0.004,0.02,,,,,,high,state of dwelling: new-build vs planned (off-plan),log advertised monthly rent (EUR),log,OLS,7860.0,0.742,se,"Rent adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,0.3807229154028091,2.008016021354684,100*(exp(b - se^2/2) - 1),reported,0.0022573248407936368,0.011286624203968181,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c10,A.2,10 (R.Alt.4),52,Dwelling State: new-build (ref. planned),condition,A_structural,dummy,binary,0.003,0.026,,,,,,high,state of dwelling: new-build vs planned (off-plan),log advertised monthly rent (EUR),log,OLS,7860.0,0.526,se,"Rent adverts 2018, Luxembourg; physical characteristics only; n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,0.2665546268023622,2.6078117117087802,100*(exp(b - se^2/2) - 1),reported,0.0013023050063752691,0.011286643388585664,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.11538461538461539,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c1,A.2,1 (S.Main),52,Dwelling State: good (ref. planned),condition,A_structural,dummy,binary,-0.032,0.007,,,***,,,high,state of dwelling: good vs planned,log advertised sales price (EUR),log,OLS,14759.0,0.824,se,"Sales adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-3.1517146041392663,0.6779546074554383,100*(exp(b - se^2/2) - 1),reported,-0.03761518402395636,0.008228321505240456,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.571428571428571,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c2,A.2,2 (S.Alt.1),52,Dwelling State: good (ref. planned),condition,A_structural,dummy,binary,-0.085,0.009,,,***,,,high,state of dwelling: good vs planned,log advertised sales price (EUR),log,OLS,14759.0,0.703,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-8.152491459277622,0.8266610559613116,100*(exp(b - se^2/2) - 1),reported,-0.07753286674996972,0.008209362361761499,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.444444444444446,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c3,A.2,3 (S.Alt.2),52,Dwelling State: good (ref. planned),condition,A_structural,dummy,binary,-0.038,0.007,,,***,,,high,state of dwelling: good vs planned,log advertised sales price (EUR),log,other,14759.0,0.819,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + linked-neighbour Markov random field spline (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-3.7310645286920407,0.6738990586238397,100*(exp(b - se^2/2) - 1),reported,-0.044655075547102845,0.008225934969203156,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.428571428571428,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c4,A.2,4 (S.Alt.3),52,Dwelling State: good (ref. planned),condition,A_structural,dummy,binary,-0.044,0.007,,,***,,,high,state of dwelling: good vs planned,log advertised sales price (EUR),log,OLS,14759.0,0.809,se,"Sales adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-4.306948761170792,0.6698677702311328,100*(exp(b - se^2/2) - 1),reported,-0.05168832084118772,0.008223141952007138,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.285714285714286,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c5,A.2,5 (S.Alt.4),52,Dwelling State: good (ref. planned),condition,A_structural,dummy,binary,-0.065,0.011,,,***,,,high,state of dwelling: good vs planned,log advertised sales price (EUR),log,OLS,14759.0,0.507,se,"Sales adverts 2018, Luxembourg; physical characteristics only; n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-6.298922748921488,1.0307742097151438,100*(exp(b - se^2/2) - 1),reported,-0.04859884057869502,0.00822441917485608,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.90909090909091,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c6,A.2,6 (R.Main),52,Dwelling State: good (ref. planned),condition,A_structural,dummy,binary,-0.033,0.01,,,**,,,high,state of dwelling: good vs planned,log advertised monthly rent (EUR),log,OLS,7860.0,0.744,se,"Rent adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-3.25098161295444,0.967538559589032,100*(exp(b - se^2/2) - 1),reported,-0.03722014668274072,0.011278832328103247,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.3000000000000003,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c7,A.2,7 (R.Alt.1),52,Dwelling State: good (ref. planned),condition,A_structural,dummy,binary,-0.02,0.011,,,.,,,high,state of dwelling: good vs planned,log advertised monthly rent (EUR),log,OLS,7860.0,0.679,se,"Rent adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-1.986062691912982,1.0782185406374307,100*(exp(b - se^2/2) - 1),reported,-0.020516867631437938,0.011284277197290866,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8181818181818183,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c9,A.2,9 (R.Alt.3),52,Dwelling State: good (ref. planned),condition,A_structural,dummy,binary,-0.039,0.01,,,***,,,high,state of dwelling: good vs planned,log advertised monthly rent (EUR),log,OLS,7860.0,0.742,se,"Rent adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-3.8297377186922277,0.9617507091463668,100*(exp(b - se^2/2) - 1),reported,-0.043975364274581104,0.011275734429379772,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.9,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c10,A.2,10 (R.Alt.4),52,Dwelling State: good (ref. planned),condition,A_structural,dummy,binary,0.04,0.013,,,**,,,high,state of dwelling: good vs planned,log advertised monthly rent (EUR),log,OLS,7860.0,0.526,se,"Rent adverts 2018, Luxembourg; physical characteristics only; n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,4.07228293976889,1.3530540064501047,100*(exp(b - se^2/2) - 1),reported,0.034707240007530636,0.011279853002447457,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.076923076923077,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c1,A.2,1 (S.Main),52,Dwelling State: average (ref. planned),condition,A_structural,dummy,binary,-0.054,0.005,,,***,,,high,state of dwelling: average vs planned; 'average' assigned when advert mentions neither improvements nor repairs,log advertised sales price (EUR),log,OLS,14759.0,0.824,se,"Sales adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-5.257973632551516,0.47371605325089916,100*(exp(b - se^2/2) - 1),reported,-0.0885792400123301,0.008201781482623157,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.799999999999999,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c2,A.2,2 (S.Alt.1),52,Dwelling State: average (ref. planned),condition,A_structural,dummy,binary,-0.078,0.006,,,***,,,high,state of dwelling: average vs planned; 'average' assigned when advert mentions neither improvements nor repairs,log advertised sales price (EUR),log,OLS,14759.0,0.703,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-7.505222266629518,0.5549786559261236,100*(exp(b - se^2/2) - 1),reported,-0.10643587894401649,0.008187375303385884,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.0,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c3,A.2,3 (S.Alt.2),52,Dwelling State: average (ref. planned),condition,A_structural,dummy,binary,-0.059,0.005,,,***,,,high,state of dwelling: average vs planned; 'average' assigned when advert mentions neither improvements nor repairs,log advertised sales price (EUR),log,other,14759.0,0.819,se,"Sales adverts 2018, Luxembourg; physical characteristics + interaction + linked-neighbour Markov random field spline (no locality dummies); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-5.730501460386606,0.47135338457854986,100*(exp(b - se^2/2) - 1),reported,-0.09670753793459366,0.008195554062253701,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.799999999999999,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c4,A.2,4 (S.Alt.3),52,Dwelling State: average (ref. planned),condition,A_structural,dummy,binary,-0.058,0.005,,,***,,,high,state of dwelling: average vs planned; 'average' assigned when advert mentions neither improvements nor repairs,log advertised sales price (EUR),log,OLS,14759.0,0.809,se,"Sales adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-5.636184811382206,0.4718249737183993,100*(exp(b - se^2/2) - 1),reported,-0.09508337264825192,0.008196842469676889,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.6,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c5,A.2,5 (S.Alt.4),52,Dwelling State: average (ref. planned),condition,A_structural,dummy,binary,-0.073,0.008,,,***,,,high,state of dwelling: average vs planned; 'average' assigned when advert mentions neither improvements nor repairs,log advertised sales price (EUR),log,OLS,14759.0,0.507,se,"Sales adverts 2018, Luxembourg; physical characteristics only; n is the number of adverts in Table 2 (5 Cook's-distance outliers dropped for sales per text, not reported in table); r2 is adjusted R2 from Table 5",pct_premium,-7.042891672481755,0.7436806640206342,100*(exp(b - se^2/2) - 1),reported,-0.07492540961375312,0.008211003793288013,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.125,14749.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c6,A.2,6 (R.Main),52,Dwelling State: average (ref. planned),condition,A_structural,dummy,binary,-0.059,0.008,,,***,,,high,state of dwelling: average vs planned; 'average' assigned when advert mentions neither improvements nor repairs,log advertised monthly rent (EUR),log,OLS,7860.0,0.744,se,"Rent adverts 2018, Luxembourg; physical characteristics + dwelling type x surface interaction + locality dummies (composite geography); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-5.732339697685251,0.7541654153256798,100*(exp(b - se^2/2) - 1),reported,-0.08295218450695516,0.01124775383145155,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.374999999999999,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c7,A.2,7 (R.Alt.1),52,Dwelling State: average (ref. planned),condition,A_structural,dummy,binary,-0.052,0.009,,,***,,,high,state of dwelling: average vs planned; 'average' assigned when advert mentions neither improvements nor repairs,log advertised monthly rent (EUR),log,OLS,7860.0,0.679,se,"Rent adverts 2018, Luxembourg; physical characteristics + interaction + travel distance to Luxembourg City (no locality dummies); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-5.070958019765969,0.8543959801586005,100*(exp(b - se^2/2) - 1),reported,-0.06507355435114054,0.011262730560774323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.777777777777778,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c9,A.2,9 (R.Alt.3),52,Dwelling State: average (ref. planned),condition,A_structural,dummy,binary,-0.063,0.008,,,***,,,high,state of dwelling: average vs planned; 'average' assigned when advert mentions neither improvements nor repairs,log advertised monthly rent (EUR),log,OLS,7860.0,0.742,se,"Rent adverts 2018, Luxembourg; physical characteristics + locality dummies (no interaction); n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-6.108657202129086,0.7511547789513066,100*(exp(b - se^2/2) - 1),reported,-0.08853336969267049,0.01124233265938673,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.875,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,17f8f1569fa95f6eb5e22b566b1a1962d7ce1a43:TA2-c10,A.2,10 (R.Alt.4),52,Dwelling State: average (ref. planned),condition,A_structural,dummy,binary,-0.038,0.011,,,***,,,high,state of dwelling: average vs planned; 'average' assigned when advert mentions neither improvements nor repairs,log advertised monthly rent (EUR),log,OLS,7860.0,0.526,se,"Rent adverts 2018, Luxembourg; physical characteristics only; n from Table 2; r2 is adjusted R2 from Table 5",pct_premium,-3.7345301479874915,1.0589842349803193,100*(exp(b - se^2/2) - 1),reported,-0.03896065215402182,0.011278083518269475,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.4545454545454546,7850.0,binary,,2024.0,Luxembourg,,,2018.0,2018.0,mixed,listing,journal,False,True,unknown,,2018.0,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-A,4,GSHP (A),8,C(GSHP)[T.True],heating,A_structural,binary,binary,0.0519,0.006,,,***,,,high,Ground source heat pump vs all other heating types,log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec A: GSHP true/false; full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",pct_premium,5.325145150906163,0.63196224612349,100*(exp(b - se^2/2) - 1),reported,0.06263378020388717,0.007240899445536088,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.65,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-B,4,Heating type (B),8,C(heating_type)[T.district_heating],heating,A_structural,binary,binary,0.0126,0.0046,,,***,,,high,District heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec B: heating type categories (direct electricity omitted); full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",pct_premium,1.2669000354148308,0.46583266864647077,100*(exp(b - se^2/2) - 1),reported,0.019868863732984937,0.007253712156486565,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.739130434782609,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-B,4,Heating type (B),8,C(heating_type)[T.GSHP],heating,A_structural,binary,binary,0.0474,0.0062,,,***,,,high,Ground source heat pump vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec B: heating type categories (direct electricity omitted); full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",pct_premium,4.85211889733097,0.650095631881422,100*(exp(b - se^2/2) - 1),reported,0.05538162180019943,0.00724400960255773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.645161290322581,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-B,4,Heating type (B),8,C(heating_type)[T.oil],heating,A_structural,binary,binary,-0.0228,0.0041,,,***,,,high,Oil heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec B: heating type categories (direct electricity omitted); full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",pct_premium,-2.25502596830085,0.40075776188479967,100*(exp(b - se^2/2) - 1),reported,-0.040312884045480404,0.00724924669238902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.560975609756097,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-A,4,GSHP (A),8,Age,age,A_structural,level,years,-0.0051,0.0001,,,***,,,high,Building age in years,log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec A: GSHP true/false; full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",semi_elasticity,-0.51,0.01,100*b/1 (per year),reported,-0.3470190798363288,0.00680429568306527,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-51.0,18998.0,years,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-A,4,GSHP (A),8,Distance to CBD,cbd_distance,D_location,level,km,-0.0161,0.0015,,,***,,,high,Kilometres to CBD (Table 1),log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec A: GSHP true/false; full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",semi_elasticity,-1.6099999999999999,0.15,100*b/1 (X per km->km),reported,-0.0776368425146061,0.007233246197012992,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.733333333333333,18998.0,km,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-A,4,GSHP (A),8,C(condition)[T.excellent],condition,A_structural,dummy,ordinal,0.3189,0.02,,,***,,,high,Condition excellent vs decent,log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec A: GSHP true/false; full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",pct_premium,37.533866141118686,2.751227513304152,100*(exp(b - se^2/2) - 1),reported,0.11491688783380577,0.007207079826516511,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.945,18998.0,ordinal,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-A,4,GSHP (A),8,C(condition)[T.good],condition,A_structural,dummy,ordinal,0.18,0.0037,,,***,,,high,Condition good vs decent,log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec A: GSHP true/false; full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",pct_premium,19.720916819700673,0.4429704243550697,100*(exp(b - se^2/2) - 1),reported,0.33283000606237884,0.006841505680171121,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),48.648648648648646,18998.0,ordinal,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-A,4,GSHP (A),8,C(condition)[T.poor],condition,A_structural,dummy,ordinal,-0.2987,0.008,,,***,,,high,Condition poor vs decent,log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec A: GSHP true/false; full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",pct_premium,-25.82418260100002,0.5934255285050813,100*(exp(b - se^2/2) - 1),reported,-0.26146549109358697,0.007002758382151643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-37.3375,18998.0,ordinal,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-B,4,Heating type (B),8,Age,age,A_structural,level,years,-0.0049,0.0001,,,***,,,high,Building age in years,log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec B: heating type categories (direct electricity omitted); full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",semi_elasticity,-0.49,0.01,100*b/1 (per year),reported,-0.33496493061694127,0.006836018992182475,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-48.99999999999999,18998.0,years,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-B,4,Heating type (B),8,Distance to CBD,cbd_distance,D_location,level,km,-0.016,0.0015,,,***,,,high,Kilometres to CBD (Table 1),log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec B: heating type categories (direct electricity omitted); full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",semi_elasticity,-1.6,0.15,100*b/1 (X per km->km),reported,-0.07715750578855231,0.0072335161676767784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.666666666666666,18998.0,km,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-B,4,Heating type (B),8,C(condition)[T.excellent],condition,A_structural,dummy,ordinal,0.317,0.02,,,***,,,high,Condition excellent vs decent,log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec B: heating type categories (direct electricity omitted); full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",pct_premium,37.27279988692946,2.7460051438509177,100*(exp(b - se^2/2) - 1),reported,0.11424117737141508,0.0072076452600261885,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.85,18998.0,ordinal,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-B,4,Heating type (B),8,C(condition)[T.good],condition,A_structural,dummy,ordinal,0.1791,0.0037,,,***,,,high,Condition good vs decent,log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec B: heating type categories (direct electricity omitted); full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",pct_premium,19.613216466991435,0.44257193032236336,100*(exp(b - se^2/2) - 1),reported,0.3313489750744137,0.00684528870896332,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),48.4054054054054,18998.0,ordinal,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T4-B,4,Heating type (B),8,C(condition)[T.poor],condition,A_structural,dummy,ordinal,-0.2995,0.008,,,***,,,high,Condition poor vs decent,log sales price (EUR),log,OLS,19008.0,0.851,se,"Spec B: heating type categories (direct electricity omitted); full controls, year+month FE, postcode FE, neighbourhood characteristics; adj. R2",pct_premium,-25.883499524986053,0.5929509779278176,100*(exp(b - se^2/2) - 1),reported,-0.2621177138467971,0.007001474827293412,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-37.4375,18998.0,ordinal,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-A-c1,5,A-1,9,C(GSHP)[T.True],heating,A_structural,binary,binary,0.2175,0.014,,,***,,,high,Ground source heat pump vs all other heating types,log sales price (EUR),log,OLS,19008.0,0.1309,se,"Spec A (GSHP true/false), sensitivity column 1: year+month FE only; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,24.284362486416434,1.7401516013108234,100*(exp(b - se^2/2) - 1),reported,0.11200461896270085,0.007209492714840515,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.535714285714285,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c1,5,B-1,9,C(heating_type)[T.district_heating],heating,A_structural,binary,binary,0.0661,0.0089,,,***,,,high,District heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.148,se,"Spec B (heating type categories), sensitivity column 1: year+month FE only; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,6.82912346668243,0.9508168552093291,100*(exp(b - se^2/2) - 1),reported,0.05380565808885141,0.007244634750238691,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.426966292134832,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c1,5,B-1,9,C(heating_type)[T.GSHP],heating,A_structural,binary,binary,0.2023,0.0142,,,***,,,high,Ground source heat pump vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.148,se,"Spec B (heating type categories), sensitivity column 1: year+month FE only; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,22.40917984358861,1.7383856089812928,100*(exp(b - se^2/2) - 1),reported,0.10281252909093981,0.0072166975437041305,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.246478873239436,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c1,5,B-1,9,C(heating_type)[T.oil],heating,A_structural,binary,binary,-0.1354,0.0089,,,***,,,high,Oil heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.148,se,"Spec B (heating type categories), sensitivity column 1: year+month FE only; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,-12.66680937837763,0.777296180738069,100*(exp(b - se^2/2) - 1),reported,-0.10970975003400231,0.007211349891452146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.213483146067414,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-A-c2,5,A-2,9,C(GSHP)[T.True],heating,A_structural,binary,binary,0.0976,0.0096,,,***,,,high,Ground source heat pump vs all other heating types,log sales price (EUR),log,OLS,19008.0,0.6179,se,"Spec A (GSHP true/false), sensitivity column 2: + postcode FE; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,10.247088519084091,1.0584208206909342,100*(exp(b - se^2/2) - 1),reported,0.07356079719335024,0.007235488248526251,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.166666666666668,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c2,5,B-2,9,C(heating_type)[T.district_heating],heating,A_structural,binary,binary,0.0394,0.0071,,,***,,,high,District heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.6228,se,"Spec B (heating type categories), sensitivity column 2: + postcode FE; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,4.016025746665353,0.7385323972758076,100*(exp(b - se^2/2) - 1),reported,0.040228351206604465,0.007249271410327202,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.549295774647887,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c2,5,B-2,9,C(heating_type)[T.GSHP],heating,A_structural,binary,binary,0.081,0.0097,,,***,,,high,Ground source heat pump vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.6228,se,"Spec B (heating type categories), sensitivity column 2: + postcode FE; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,8.431988353789466,1.0518397696697577,100*(exp(b - se^2/2) - 1),reported,0.060473314850933005,0.007241866099432718,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.350515463917526,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c2,5,B-2,9,C(heating_type)[T.oil],heating,A_structural,binary,binary,-0.0832,0.0064,,,***,,,high,Oil heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.6228,se,"Spec B (heating type categories), sensitivity column 2: + postcode FE; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,-7.985174943266548,0.588906941053745,100*(exp(b - se^2/2) - 1),reported,-0.09390014888741624,0.007223088375955095,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.999999999999998,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-A-c3,5,A-3,9,C(GSHP)[T.True],heating,A_structural,binary,binary,0.0898,0.0094,,,***,,,high,Ground source heat pump vs all other heating types,log sales price (EUR),log,OLS,19008.0,0.6332,se,"Spec A (GSHP true/false), sensitivity column 3: + neighbourhood characteristics; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,9.39071408454144,1.0283181424866663,100*(exp(b - se^2/2) - 1),reported,0.06914390400249462,0.007237780597143089,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.553191489361703,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c3,5,B-3,9,C(heating_type)[T.district_heating],heating,A_structural,binary,binary,0.0353,0.007,,,***,,,high,District heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.6368,se,"Spec B (heating type categories), sensitivity column 3: + neighbourhood characteristics; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,3.5905061334904342,0.7251513089238676,100*(exp(b - se^2/2) - 1),reported,0.036562193972489596,0.007250293422306718,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.042857142857143,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c3,5,B-3,9,C(heating_type)[T.GSHP],heating,A_structural,binary,binary,0.0762,0.0096,,,***,,,high,Ground source heat pump vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.6368,se,"Spec B (heating type categories), sensitivity column 3: + neighbourhood characteristics; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,7.9128660858402755,1.036011252722693,100*(exp(b - se^2/2) - 1),reported,0.05749245488887264,0.007243143923007575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.937500000000001,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c3,5,B-3,9,C(heating_type)[T.oil],heating,A_structural,binary,binary,-0.071,0.0063,,,***,,,high,Oil heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.6368,se,"Spec B (heating type categories), sensitivity column 3: + neighbourhood characteristics; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,-6.8556592550242375,0.5868209920403831,100*(exp(b - se^2/2) - 1),reported,-0.08149237434578006,0.007231013498287527,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.269841269841269,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-A-c4a,5,A-4a,9,C(GSHP)[T.True],heating,A_structural,binary,binary,0.0555,0.0064,,,***,,,high,Ground source heat pump vs all other heating types,log sales price (EUR),log,OLS,19008.0,0.8282,se,"Spec A (GSHP true/false), sensitivity column 4a: full model excluding age; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,5.704736852063519,0.6765241709263506,100*(exp(b - se^2/2) - 1),reported,0.062791551148654,0.007240827519844785,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.671875,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c4a,5,B-4a,9,C(heating_type)[T.district_heating],heating,A_structural,binary,binary,0.0262,0.0049,,,***,,,high,District heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.8303,se,"Spec B (heating type categories), sensitivity column 4a: full model excluding age; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,2.6533913577719392,0.5030076562237489,100*(exp(b - se^2/2) - 1),reported,0.038763656299617845,0.0072496914453483744,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.346938775510204,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c4a,5,B-4a,9,C(heating_type)[T.GSHP],heating,A_structural,binary,binary,0.0436,0.0066,,,***,,,high,Ground source heat pump vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.8303,se,"Spec B (heating type categories), sensitivity column 4a: full model excluding age; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,4.454169516806017,0.6894125340523948,100*(exp(b - se^2/2) - 1),reported,0.047872970731610204,0.007246825844693288,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.606060606060606,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c4a,5,B-4a,9,C(heating_type)[T.oil],heating,A_structural,binary,binary,-0.0564,0.0043,,,***,,,high,Oil heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.8303,se,"Spec B (heating type categories), sensitivity column 4a: full model excluding age; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,-5.484774210392917,0.4064192282237071,100*(exp(b - se^2/2) - 1),reported,-0.09473253857602182,0.007222516238952018,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.116279069767442,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-A-c4b,5,A-4b,9,C(GSHP)[T.True],heating,A_structural,binary,binary,0.0363,0.0067,,,***,,,high,Ground source heat pump vs all other heating types,log sales price (EUR),log,OLS,19008.0,0.8119,se,"Spec A (GSHP true/false), sensitivity column 4b: full model excluding condition; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,3.6943615438404187,0.6947678162323632,100*(exp(b - se^2/2) - 1),reported,0.039277390454697594,0.007249545896597077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.4179104477611935,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c4b,5,B-4b,9,C(heating_type)[T.district_heating],heating,A_structural,binary,binary,0.0121,0.0051,,,**,,,high,District heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.8124,se,"Spec B (heating type categories), sensitivity column 4b: full model excluding condition; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,1.2160337924706166,0.5162084855893022,100*(exp(b - se^2/2) - 1),reported,0.017210636127247107,0.007254069772641345,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3725490196078427,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c4b,5,B-4b,9,C(heating_type)[T.GSHP],heating,A_structural,binary,binary,0.0297,0.0069,,,***,,,high,Ground source heat pump vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.8124,se,"Spec B (heating type categories), sensitivity column 4b: full model excluding condition; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,3.012092163873281,0.7108003563318123,100*(exp(b - se^2/2) - 1),reported,0.031213448428566933,0.007251609230879185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.304347826086957,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c4b,5,B-4b,9,C(heating_type)[T.oil],heating,A_structural,binary,binary,-0.0305,0.0046,,,***,,,high,Oil heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.8124,se,"Spec B (heating type categories), sensitivity column 4b: full model excluding condition; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,-3.004983005987394,0.44618179875091685,100*(exp(b - se^2/2) - 1),reported,-0.04804919908931362,0.0072467644528145135,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.630434782608695,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-A-c4c,5,A-4c,9,C(GSHP)[T.True],heating,A_structural,binary,binary,0.0374,0.0076,,,***,,,high,Ground source heat pump vs all other heating types,log sales price (EUR),log,OLS,19008.0,0.7609,se,"Spec A (GSHP true/false), sensitivity column 4c: full model excluding age and condition; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,3.80782009416496,0.7889622176154829,100*(exp(b - se^2/2) - 1),reported,0.03568021369967563,0.007250524709024995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.921052631578948,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c4c,5,B-4c,9,C(heating_type)[T.district_heating],heating,A_structural,binary,binary,0.0338,0.0057,,,***,,,high,District heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.7658,se,"Spec B (heating type categories), sensitivity column 4c: full model excluding age and condition; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,3.436090716766338,0.5895952949833385,100*(exp(b - se^2/2) - 1),reported,0.04298197460245034,0.00724843950396352,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.929824561403508,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c4c,5,B-4c,9,C(heating_type)[T.GSHP],heating,A_structural,binary,binary,0.0184,0.0077,,,**,,,high,Ground source heat pump vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.7658,se,"Spec B (heating type categories), sensitivity column 4c: full model excluding age and condition; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,1.854012797459137,0.784299148744072,100*(exp(b - se^2/2) - 1),reported,0.01733436343964642,0.007254054265504207,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3896103896103895,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25,18a3ce8a193301208557e0d6f2d027166917cb25:T5-B-c4c,5,B-4c,9,C(heating_type)[T.oil],heating,A_structural,binary,binary,-0.0874,0.0051,,,***,,,high,Oil heating vs direct electricity,log sales price (EUR),log,OLS,19008.0,0.7658,se,"Spec B (heating type categories), sensitivity column 4c: full model excluding age and condition; adj. R2; column 4 = Table 4 (not duplicated)",pct_premium,-8.37014184212508,0.4673183540408378,100*(exp(b - se^2/2) - 1),reported,-0.12338323981706109,0.007199708501910888,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.137254901960784,18998.0,binary,,2023.0,Finland,Europe,High income,1999.0,2018.0,single_family,transaction,journal,True,True,unknown,,2008.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,BATHS,bathrooms,A_structural,level,count,0.146,,3.37,,,,,high,total number of baths (full plus half),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",semi_elasticity,14.6,4.332344213649851,100*b/1 (per unit count),|b/t|,0.138231253548581,0.04101817612717537,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.37,583.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,FIREPLACES,fireplace,B_interior,level,count,0.061,,4.7,,,,,high,number of fireplaces,ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",semi_elasticity,6.1,1.2978723404255317,100*b/1 (per unit count),|b/t|,0.19106796148464633,0.040652757762690714,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.7,583.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,ROOMS,bedrooms,A_structural,level,count,0.0336,,2.1,,,,,high,total listed number of rooms (not bedrooms per se),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",semi_elasticity,3.36,1.5999999999999996,100*b/1 (per unit count),|b/t|,0.08664602165648265,0.041260010312610784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1,583.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,SQFT,living_area,A_structural,level,sqft,1.2e-05,,2.67,,,,,medium,"finished living space in square feet; printed SQFT coefficient inconsistent across columns (0.000012 vs 0.000128), transcribed as printed",ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",semi_elasticity,0.012916692500051667,0.004837712546835831,100*b/0.092903 (X per sqft->m2),|b/t|,0.10991015480906013,0.041164851988412035,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.67,583.0,sqft,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,BRICK,roof_materials,A_structural,binary,binary,0.25,,4.04,,,,,high,brick exterior (=1); exterior material,ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",pct_premium,28.156932135788626,7.945701835938994,100*(exp(b - se^2/2) - 1),|b/t|,0.16502563022318165,0.040847928273064764,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.04,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,DECK,terrace_balcony,C_exterior,binary,binary,0.144,,3.32,,,,,high,exterior deck (=1),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",pct_premium,15.3798300649431,5.009135892397215,100*(exp(b - se^2/2) - 1),|b/t|,0.13621868160828807,0.04102972337599038,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.32,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,CTYD,garden,C_exterior,binary,binary,0.21,,4.6,,,,,high,private courtyard (=1),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",pct_premium,23.23931623780129,5.632008534585132,100*(exp(b - se^2/2) - 1),|b/t|,0.18714655953493428,0.04068403468150746,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.6,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,SPRINKLER,landscaping,C_exterior,binary,binary,0.216,,2.99,,,,,high,underground sprinkler system (=1),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",pct_premium,23.786810920857903,8.965823206158698,100*(exp(b - se^2/2) - 1),|b/t|,0.12289446054826032,0.041101826270321176,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.99,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,STORIES,storeys,A_structural,level,count,0.195,,3.1,,,,,high,number of stories/floors,ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",semi_elasticity,19.5,6.290322580645161,100*b/1 (per unit count),|b/t|,0.12734362427420484,0.041078588475549946,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1,583.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,STUCCO,roof_materials,A_structural,binary,binary,0.35,,5.6,,,,,high,stucco exterior (=1); exterior material,ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",pct_premium,41.62986371826736,8.869172178707856,100*(exp(b - se^2/2) - 1),|b/t|,0.22593138318568567,0.04034488985458674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.6,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,GARAGESP,garage,A_structural,level,count,0.106,,3.26,,,,,high,number of garage spaces,ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",semi_elasticity,10.6,3.2515337423312882,100*b/1 (per unit count),|b/t|,0.13380136922282077,0.04104336479227631,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.26,583.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,BALCNY,terrace_balcony,C_exterior,binary,binary,0.011,,0.21,,,,,high,balcony (=1),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",pct_premium,0.9674617355335036,5.296032355662816,100*(exp(b - se^2/2) - 1),|b/t|,0.008696982421229535,0.041414202005854925,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.21,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,POOLTUB,pool,C_exterior,binary,binary,0.229,,1.64,,,,,high,hot-tub and/or swimming pool (=1),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",pct_premium,24.51439585477633,17.55678822763739,100*(exp(b - se^2/2) - 1),|b/t|,0.06776572543813854,0.041320564291547894,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.64,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,NEW,age,A_structural,binary,binary,0.296,,4.2,,,,,high,"house new at time of sale (=1); new-construction dummy, not years",ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",pct_premium,34.113537942659164,9.475313486244943,100*(exp(b - se^2/2) - 1),|b/t|,0.17137290747088343,0.0408030732073532,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.2,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-ab,1,(a)-(b),7,PARKSQ,green_space,E_environment,binary,binary,0.088,,0.76,,,,,high,located across from or adjacent to a park or square (=1),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, full specification",pct_premium,8.46923505359305,12.644072991905443,100*(exp(b - se^2/2) - 1),|b/t|,0.03146040328584296,0.041395267481372316,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.76,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-cd,1,(c)-(d),7,BATHS,bathrooms,A_structural,level,count,0.144,,3.37,,,,,high,total number of baths (full plus half),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, restricted specification",semi_elasticity,14.399999999999999,4.272997032640949,100*b/1 (per unit count),|b/t|,0.138231253548581,0.04101817612717537,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.37,583.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-cd,1,(c)-(d),7,FIREPLACES,fireplace,B_interior,level,count,0.062,,4.82,,,,,high,number of fireplaces,ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, restricted specification",semi_elasticity,6.2,1.2863070539419086,100*b/1 (per unit count),|b/t|,0.1957615822285687,0.04061443614700595,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.82,583.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-cd,1,(c)-(d),7,ROOMS,bedrooms,A_structural,level,count,0.0385,,2.47,,,,,high,total listed number of rooms (not bedrooms per se),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, restricted specification",semi_elasticity,3.85,1.5587044534412955,100*b/1 (per unit count),|b/t|,0.10176586071947681,0.041200753327723404,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.47,583.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-cd,1,(c)-(d),7,SQFT,living_area,A_structural,level,sqft,0.000128,,2.9,,,,,medium,"finished living space in square feet; printed SQFT coefficient inconsistent across columns (0.000012 vs 0.000128), transcribed as printed",ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, restricted specification",semi_elasticity,0.13777805333388443,0.047509673563408426,100*b/0.092903 (X per sqft->m2),|b/t|,0.11924870352745057,0.0411202425956726,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9,583.0,sqft,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-cd,1,(c)-(d),7,BRICK,roof_materials,A_structural,binary,binary,0.254,,4.16,,,,,high,brick exterior (=1); exterior material,ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, restricted specification",pct_premium,28.677099935784867,7.871385535673612,100*(exp(b - se^2/2) - 1),|b/t|,0.1697880549793755,0.04081443629311911,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.16,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-cd,1,(c)-(d),7,DECK,terrace_balcony,C_exterior,binary,binary,0.146,,3.36,,,,,high,exterior deck (=1),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, restricted specification",pct_premium,15.610424705172687,5.028292959982626,100*(exp(b - se^2/2) - 1),|b/t|,0.13782887530225418,0.04102049860186136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.36,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-cd,1,(c)-(d),7,CTYD,garden,C_exterior,binary,binary,0.23,,5.02,,,,,high,private courtyard (=1),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, restricted specification",pct_premium,25.727969334635546,5.766494069398007,100*(exp(b - se^2/2) - 1),|b/t|,0.20355433999201003,0.04054867330518128,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.02,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,True
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-cd,1,(c)-(d),7,SPRINKLER,landscaping,C_exterior,binary,binary,0.206,,2.79,,,,,high,underground sprinkler system (=1),ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, restricted specification",pct_premium,22.540841339934282,9.072514696166103,100*(exp(b - se^2/2) - 1),|b/t|,0.11478623310408428,0.041142019033721965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.79,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-cd,1,(c)-(d),7,STORIES,storeys,A_structural,level,count,0.188,,3.17,,,,,high,number of stories/floors,ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, restricted specification",semi_elasticity,18.8,5.930599369085174,100*b/1 (per unit count),|b/t|,0.13017093066224605,0.04106338506695459,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.17,583.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-cd,1,(c)-(d),7,STUCCO,roof_materials,A_structural,binary,binary,0.366,,5.82,,,,,high,stucco exterior (=1); exterior material,ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, restricted specification",pct_premium,43.910679214477796,9.06796595896139,100*(exp(b - se^2/2) - 1),|b/t|,0.23432860919509355,0.040262647628022945,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.82,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-cd,1,(c)-(d),7,GARAGESP,garage,A_structural,level,count,0.098,,3.11,,,,,high,number of garage spaces,ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, restricted specification",semi_elasticity,9.8,3.1511254019292605,100*b/1 (per unit count),|b/t|,0.12774771694976383,0.041076436318252044,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.11,583.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T1-cd,1,(c)-(d),7,NEW,age,A_structural,binary,binary,0.289,,4.09,,,,,high,"house new at time of sale (=1); new-construction dummy, not years",ln real sales price (2005 USD),log,OLS,593.0,0.62,t,"Inside Savannah Historic Landmark District, restricted specification",pct_premium,33.17629247221001,9.433777739480169,100*(exp(b - se^2/2) - 1),|b/t|,0.16701139708693138,0.04083408241734265,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.09,583.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,BATHS,bathrooms,A_structural,level,count,0.121,,3.07,,,,,high,total number of baths (full plus half),ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",semi_elasticity,12.1,3.9413680781758957,100*b/1 (per unit count),|b/t|,0.0702934164338514,0.022896878317215437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.07,1898.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,FIREPLACES,fireplace,B_interior,level,count,0.06,,3.82,,,,,high,number of fireplaces,ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",semi_elasticity,6.0,1.5706806282722512,100*b/1 (per unit count),|b/t|,0.08734783600838444,0.022865925656645143,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.82,1898.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,True
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,ROOMS,bedrooms,A_structural,level,count,0.032,,2.14,,,,,high,total listed number of rooms (not bedrooms per se),ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",semi_elasticity,3.2,1.4953271028037383,100*b/1 (per unit count),|b/t|,0.04906167321556152,0.02292601552129043,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.14,1898.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,SQFT,living_area,A_structural,level,sqft,1.1e-05,,2.65,,,,,medium,"finished living space in square feet; printed SQFT coefficient inconsistent across columns (0.000012 vs 0.000128), transcribed as printed",ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",semi_elasticity,0.011840301458380694,0.004468038286181393,100*b/0.092903 (X per sqft->m2),|b/t|,0.0607149748164644,0.022911311251496,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.65,1898.0,sqft,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,True
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,BRICK,roof_materials,A_structural,binary,binary,0.2,,3.98,,,,,high,brick exterior (=1); exterior material,ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",pct_premium,21.986159503999005,6.1377023023124115,100*(exp(b - se^2/2) - 1),|b/t|,0.09097670700742888,0.022858469097343938,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.98,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,DECK,terrace_balcony,C_exterior,binary,binary,0.11,,2.99,,,,,high,exterior deck (=1),ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",pct_premium,11.552291137648908,4.106708620417252,100*(exp(b - se^2/2) - 1),|b/t|,0.06847036809533213,0.022899788660646198,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.99,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,CTYD,garden,C_exterior,binary,binary,0.09,,2.11,,,,,high,private courtyard (=1),ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",pct_premium,9.317938447280127,4.667094101112272,100*(exp(b - se^2/2) - 1),|b/t|,0.04837551370216429,0.02292678374510156,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.11,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,SPRINKLER,landscaping,C_exterior,binary,binary,0.24,,3.15,,,,,high,underground sprinkler system (=1),ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",pct_premium,26.756470649450947,9.685707811972607,100*(exp(b - se^2/2) - 1),|b/t|,0.07211576070309567,0.02289389228669704,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.15,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,STORIES,storeys,A_structural,level,count,0.18,,2.09,,,,,high,number of stories/floors,ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",semi_elasticity,18.0,8.61244019138756,100*b/1 (per unit count),|b/t|,0.047918035914461775,0.02292728991122573,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.09,1898.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,STUCCO,roof_materials,A_structural,binary,binary,0.28,,3.04,,,,,high,stucco exterior (=1); exterior material,ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",pct_premium,31.752939219283526,12.186721955739552,100*(exp(b - se^2/2) - 1),|b/t|,0.06960985485375422,0.022897978570313886,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.04,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,GARAGESP,garage,A_structural,level,count,0.11,,3.05,,,,,high,number of garage spaces,ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",semi_elasticity,11.0,3.606557377049181,100*b/1 (per unit count),|b/t|,0.06983771965665282,0.022897613002181252,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.05,1898.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,BALCNY,terrace_balcony,C_exterior,binary,binary,0.01,,0.56,,,,,high,balcony (=1),ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",pct_premium,0.9889138759744842,1.8036610126502997,100*(exp(b - se^2/2) - 1),|b/t|,0.012852986383067717,0.022951761398335203,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.56,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,POOLTUB,pool,C_exterior,binary,binary,0.16,,2.18,,,,,high,hot-tub and/or swimming pool (=1),ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",pct_premium,17.035441766735595,8.612923823793102,100*(exp(b - se^2/2) - 1),|b/t|,0.04997644435620161,0.022924974475321838,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.18,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,NEW,age,A_structural,binary,binary,0.302,,3.97,,,,,high,"house new at time of sale (=1); new-construction dummy, not years",ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",pct_premium,34.865343258102044,10.289004797638881,100*(exp(b - se^2/2) - 1),|b/t|,0.09075000719162483,0.022858943876983586,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.97,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,True
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-ab,2,(a)-(b),7,PARKSQ,green_space,E_environment,binary,binary,0.066,,1.81,,,,,high,located across from or adjacent to a park or square (=1),ln real sales price (2005 USD),log,OLS,1908.0,0.63,t,"Outside the district (metro Savannah), full specification",pct_premium,6.751678017294105,3.8951913443621855,100*(exp(b - se^2/2) - 1),|b/t|,0.041510310352749026,0.02293387312306576,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.81,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,BATHS,bathrooms,A_structural,level,count,0.122,,3.09,,,,,high,total number of baths (full plus half),ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",semi_elasticity,12.2,3.9482200647249193,100*b/1 (per unit count),|b/t|,0.07074906920654925,0.022896138901795874,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.09,1898.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,FIREPLACES,fireplace,B_interior,level,count,0.061,,3.69,,,,,high,number of fireplaces,ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",semi_elasticity,6.1,1.6531165311653118,100*b/1 (per unit count),|b/t|,0.08439680897788568,0.022871763950646527,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.69,1898.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,ROOMS,bedrooms,A_structural,level,count,0.033,,2.55,,,,,high,total listed number of rooms (not bedrooms per se),ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",semi_elasticity,3.3000000000000003,1.2941176470588238,100*b/1 (per unit count),|b/t|,0.058431819087844325,0.022914438857978166,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.55,1898.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,SQFT,living_area,A_structural,level,sqft,0.00012,,2.71,,,,,medium,"finished living space in square feet; printed SQFT coefficient inconsistent across columns (0.000012 vs 0.000128), transcribed as printed",ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",semi_elasticity,0.12916692500051666,0.04766307195591021,100*b/0.092903 (X per sqft->m2),|b/t|,0.062084413263495855,0.02290937758800585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.71,1898.0,sqft,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,BRICK,roof_materials,A_structural,binary,binary,0.21,,4.01,,,,,high,brick exterior (=1); exterior material,ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",pct_premium,23.19875257670938,6.460658169349528,100*(exp(b - se^2/2) - 1),|b/t|,0.09165672146165825,0.0228570377709871,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.01,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,DECK,terrace_balcony,C_exterior,binary,binary,0.114,,3.01,,,,,high,exterior deck (=1),ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",pct_premium,11.994859773371092,4.244709044411743,100*(exp(b - se^2/2) - 1),|b/t|,0.06892619520752961,0.022899068175259007,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.01,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,CTYD,garden,C_exterior,binary,binary,0.11,,2.23,,,,,high,private courtyard (=1),ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",pct_premium,11.49208390910761,5.50630438342941,100*(exp(b - se^2/2) - 1),|b/t|,0.05111973116695662,0.022923646263209245,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.23,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,SPRINKLER,landscaping,C_exterior,binary,binary,0.242,,2.87,,,,,high,underground sprinkler system (=1),ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",pct_premium,26.92739217126665,10.740703646742828,100*(exp(b - se^2/2) - 1),|b/t|,0.06573451464772291,0.02290401207237732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.87,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,True
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,STORIES,storeys,A_structural,level,count,0.19,,2.19,,,,,high,number of stories/floors,ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",semi_elasticity,19.0,8.675799086757992,100*b/1 (per unit count),|b/t|,0.050205117580583235,0.022924711224010613,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.19,1898.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,STUCCO,roof_materials,A_structural,binary,binary,0.29,,3.12,,,,,high,stucco exterior (=1); exterior material,ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",pct_premium,33.06669303179828,12.421922164339321,100*(exp(b - se^2/2) - 1),|b/t|,0.0714324652457378,0.02289502091209545,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.12,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,GARAGESP,garage,A_structural,level,count,0.11,,3.14,,,,,high,number of garage spaces,ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",semi_elasticity,11.0,3.5031847133757963,100*b/1 (per unit count),|b/t|,0.07188800678457123,0.022894269676615044,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.14,1898.0,count,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,POOLTUB,pool,C_exterior,binary,binary,0.17,,2.21,,,,,high,hot-tub and/or swimming pool (=1),ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",pct_premium,18.18032147236215,9.117729625541273,100*(exp(b - se^2/2) - 1),|b/t|,0.05066244030718153,0.022924181134471283,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.21,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,False
1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,1aa52b387c00d728ed5f6e7b8aeacbd09246f0d3:T2-cd,2,(c)-(d),7,NEW,age,A_structural,binary,binary,0.31,,4.01,,,,,high,"house new at time of sale (=1); new-construction dummy, not years",ln real sales price (2005 USD),log,OLS,1908.0,0.61,t,"Outside the district (metro Savannah), restricted specification",pct_premium,35.93570552926397,10.5401941491515,100*(exp(b - se^2/2) - 1),|b/t|,0.09165672146165825,0.0228570377709871,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.01,1898.0,binary,,2011.0,United States,North America,High income,2000.0,2005.0,single_family,transaction,journal,False,False,robust,,2002.5,ols,journal,True,True,True
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c1,3,1,10,beta1 (ln house plot area),lot_size,A_structural,log,m2,0.0785,,,,,0.0633,0.0936,high,ln plot area (m2); lower-level covariate. Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,"Linear model without multilevel effects (Bayesian, WinBUGS); posterior means; dependent variable is log of price per m2",elasticity,0.0785,0.007729733811437355,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.27567249359523277,0.027144904390144182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.155589042904289,1254.0,m2,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c2,3,2,10,beta1 (ln house plot area),lot_size,A_structural,log,m2,0.072,,,,,0.0559,0.088,high,ln plot area (m2); lower-level covariate. Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random-intercept model (district level); posterior means; dependent variable is log of price per m2,elasticity,0.072,0.008188925919047492,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.24097204887607834,0.027406975788990245,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.792361869158878,1254.0,m2,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c3,3,3,10,beta1 (ln house plot area),lot_size,A_structural,log,m2,0.0696,,,,,0.0538,0.0854,high,ln plot area (m2); lower-level covariate. Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random intercepts with intrinsic CAR spatial effect at district level; posterior means; dependent variable is log of price per m2,elasticity,0.0696,0.008061372555822455,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.2368713952267552,0.027435467884200267,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.63376546835443,1254.0,m2,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c1,3,1,10,beta2 (ln travel time to CBD),cbd_distance,D_location,log,minutes,0.613,,,,,0.426,0.801,high,ln estimated travel time to CBD San Jose (min); quadratic in logs with beta3. Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,"Linear model without multilevel effects (Bayesian, WinBUGS); posterior means; dependent variable is log of price per m2",elasticity,0.613,0.09566502241877914,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.17805838132854845,0.02778786140562335,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.407775637333332,1254.0,minutes,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c2,3,2,10,beta2 (ln travel time to CBD),cbd_distance,D_location,log,minutes,0.506,,,,,0.264,0.756,high,ln estimated travel time to CBD San Jose (min); quadratic in logs with beta3. Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random-intercept model (district level); posterior means; dependent variable is log of price per m2,elasticity,0.506,0.1255125094134382,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.11311453937217979,0.028057884758394148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.031470666666667,1254.0,minutes,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c3,3,3,10,beta2 (ln travel time to CBD),cbd_distance,D_location,log,minutes,0.383,,,,,0.118,0.647,high,ln estimated travel time to CBD San Jose (min); quadratic in logs with beta3. Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random intercepts with intrinsic CAR spatial effect at district level; posterior means; dependent variable is log of price per m2,elasticity,0.383,0.13495145829209107,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.07988810602187686,0.028148867905601737,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.838057512287335,1254.0,minutes,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c1,3,1,10,beta4 (ln distance to major road),highway_distance,D_location,log,m,-0.0111,,,,,-0.0207,-0.00147,high,ln Euclidean distance to nearest major road (m). Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,"Linear model without multilevel effects (Bayesian, WinBUGS); posterior means; dependent variable is log of price per m2",elasticity,-0.0111,0.004905702349634993,b (log-log),(ci_hi-ci_lo)/(2*1.96),-0.06376586819417203,0.028181654903303148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.262672948517941,1254.0,m,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c2,3,2,10,beta4 (ln distance to major road),highway_distance,D_location,log,m,-0.012,,,,,-0.0224,-0.00165,high,ln Euclidean distance to nearest major road (m). Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random-intercept model (district level); posterior means; dependent variable is log of price per m2,elasticity,-0.012,0.005293464573839111,b (log-log),(ci_hi-ci_lo)/(2*1.96),-0.06388580762123373,0.028181438284508455,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.2669463132530123,1254.0,m,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c3,3,3,10,beta4 (ln distance to major road),highway_distance,D_location,log,m,-0.0113,,,,,-0.0218,-0.000723,high,ln Euclidean distance to nearest major road (m). Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random intercepts with intrinsic CAR spatial effect at district level; posterior means; dependent variable is log of price per m2,elasticity,-0.0113,0.005376884473388286,b (log-log),(ci_hi-ci_lo)/(2*1.96),-0.05924279036412947,0.0281895256344323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1015887650045073,1254.0,m,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c1,3,1,10,beta5 (ln distance to bus route),transit_distance,D_location,log,m,0.0112,,,,,0.00463,0.0178,high,ln Euclidean distance to nearest bus route (m). Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,"Linear model without multilevel effects (Bayesian, WinBUGS); posterior means; dependent variable is log of price per m2",elasticity,0.0112,0.003359755587347523,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.09372290153620519,0.02811482518738278,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.333575823842065,1254.0,m,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c2,3,2,10,beta5 (ln distance to bus route),transit_distance,D_location,log,m,0.0084,,,,,0.00183,0.015,high,ln Euclidean distance to nearest bus route (m). Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random-intercept model (district level); posterior means; dependent variable is log of price per m2,elasticity,0.0084,0.0033597555873475225,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.0704276328405674,0.02816900392139955,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.500181867881549,1254.0,m,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c3,3,3,10,beta5 (ln distance to bus route),transit_distance,D_location,log,m,0.00806,,,,,0.0016,0.0145,high,ln Euclidean distance to nearest bus route (m). Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random intercepts with intrinsic CAR spatial effect at district level; posterior means; dependent variable is log of price per m2,elasticity,0.00806,0.0032908767712060017,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.06899830111515441,0.028171824614458912,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.449195324031008,1254.0,m,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c1,3,1,10,gamma2 (ln crime rate),crime,F_neighbourhood,log,count,0.000414,,,,,-0.00336,0.00419,high,"ln homicides per 100,000 residents in district (2018), 0.001 added; district-level covariate. Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.","ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,"Linear model without multilevel effects (Bayesian, WinBUGS); posterior means; dependent variable is log of price per m2",elasticity,0.000414,0.0019260557846980863,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.00606980460729523,0.028238604531082307,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.21494704529801323,1254.0,count,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c2,3,2,10,gamma2 (ln crime rate),crime,F_neighbourhood,log,count,-6.36e-05,,,,,-0.00642,0.00641,high,"ln homicides per 100,000 residents in district (2018), 0.001 added; district-level covariate. Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.","ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random-intercept model (district level); posterior means; dependent variable is log of price per m2,elasticity,-6.36e-05,0.0032730193003544963,b (log-log),(ci_hi-ci_lo)/(2*1.96),-0.000548731277764295,0.028239120484759773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.019431599438815277,1254.0,count,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c3,3,3,10,gamma2 (ln crime rate),crime,F_neighbourhood,log,count,0.000859,,,,,-0.00455,0.00622,high,"ln homicides per 100,000 residents in district (2018), 0.001 added; district-level covariate. Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.","ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random intercepts with intrinsic CAR spatial effect at district level; posterior means; dependent variable is log of price per m2,elasticity,0.000859,0.002747499443867336,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.008828559667563997,0.02823802418717308,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3126479249767874,1254.0,count,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c1,3,1,10,gamma3 (ln number of jobs in district),employment_access,D_location,log,count,0.0188,,,,,0.00934,0.0283,high,ln number of jobs in district (2018); district-level covariate. Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,"Linear model without multilevel effects (Bayesian, WinBUGS); posterior means; dependent variable is log of price per m2",elasticity,0.0188,0.004836823533493471,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.10910593753869006,0.028070540762287488,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8868484388185665,1254.0,count,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c2,3,2,10,gamma3 (ln number of jobs in district),employment_access,D_location,log,count,0.0203,,,,,0.00406,0.0367,high,ln number of jobs in district (2018); district-level covariate. Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random-intercept model (district level); posterior means; dependent variable is log of price per m2,elasticity,0.0203,0.008326683551330535,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.06868286919853864,0.02817243927160879,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4379454166666665,1254.0,count,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c3,3,3,10,gamma3 (ln number of jobs in district),employment_access,D_location,log,count,0.0108,,,,,-0.00437,0.0261,high,ln number of jobs in district (2018); district-level covariate. Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.,"ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random intercepts with intrinsic CAR spatial effect at district level; posterior means; dependent variable is log of price per m2,elasticity,0.0108,0.0077731019549338665,b (log-log),(ci_hi-ci_lo)/(2*1.96),0.03920546382433876,0.02821741365713487,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3894067082376107,1254.0,count,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c1,3,1,10,gamma4 (ln poverty proxy),income,F_neighbourhood,log,count,-0.0195,,,,,-0.0346,-0.00427,high,"ln number of households with unsatisfied housing needs (Census 2011), poverty proxy; district-level covariate; closest leaf income (sign negative = poorer). Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.","ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,"Linear model without multilevel effects (Bayesian, WinBUGS); posterior means; dependent variable is log of price per m2",elasticity,-0.0195,0.007737387013230855,b (log-log),(ci_hi-ci_lo)/(2*1.96),-0.07098955259457293,0.028167879093349602,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5202306627101883,1254.0,count,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c2,3,2,10,gamma4 (ln poverty proxy),income,F_neighbourhood,log,count,-0.0259,,,,,-0.0542,0.00214,high,"ln number of households with unsatisfied housing needs (Census 2011), poverty proxy; district-level covariate; closest leaf income (sign negative = poorer). Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.","ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random-intercept model (district level); posterior means; dependent variable is log of price per m2,elasticity,-0.0259,0.014372712968197376,b (log-log),(ci_hi-ci_lo)/(2*1.96),-0.050821871787894844,0.02820263226694751,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8020258288959885,1254.0,count,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,True
1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c,1cd473df8f393883694de4530b0d1c667382890c:T3-c3,3,3,10,gamma4 (ln poverty proxy),income,F_neighbourhood,log,count,-0.0117,,,,,-0.0349,0.0114,high,"ln number of households with unsatisfied housing needs (Census 2011), poverty proxy; district-level covariate; closest leaf income (sign negative = poorer). Bayesian posterior mean with 2.5% and 97.5% percentiles (95% posterior interval) recorded as ci_lo/ci_hi; no SE or stars printed.","ln housing price per m2 of living area (US$/m2), from listings",log,other,1264.0,,none,Multilevel random intercepts with intrinsic CAR spatial effect at district level; posterior means; dependent variable is log of price per m2,elasticity,-0.0117,0.011811441434638595,b (log-log),(ci_hi-ci_lo)/(2*1.96),-0.027961749942060028,0.02822808306415821,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.990564958963283,1254.0,count,,2021.0,Costa Rica,,,,,single_family,listing,journal,False,True,unknown,,2018.0,other,journal,True,True,False
1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de:T2-c1,2,1,10,Number of rooms (ln),bedrooms,A_structural,log,count,0.64,0.052,,0.0,***,,,high,number of rooms (log),ln of house appraisal value (LKR),log,OLS,1523.0,0.41,none,conventional hedonic model; SE and p value in separate columns; adj. R2,elasticity,0.64,0.052,b (log-log),reported,0.3016736878466599,0.024510987137541112,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.307692307692308,1513.0,count,,2012.0,Sri Lanka,Asia,Lower middle income,2003.0,2004.0,single_family,appraisal,journal,False,True,unknown,,2003.5,ols,journal,True,True,False
1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de:T3-c1,3,1,11,Number of rooms (ln),bedrooms,A_structural,log,count,0.556,0.052,,0.0,***,,,high,number of rooms (log),ln of house appraisal value (LKR),log,OLS,1491.0,0.45,none,adjusted hedonic model with household socio-economic characteristics; SE and p value in separate columns; adj. R2,elasticity,0.556,0.052,b (log-log),reported,0.2676990327819065,0.025036600188235857,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.692307692307693,1481.0,count,,2012.0,Sri Lanka,Asia,Lower middle income,2003.0,2004.0,single_family,appraisal,journal,False,True,unknown,,2003.5,ols,journal,True,True,False
1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de:T2-c1,2,1,10,Number of toilets (0/1/2),bathrooms,A_structural,level,"count (0 = none, 1 = one, 2 = two or more sealed toilets)",0.467,0.052,,0.0,***,,,high,,ln of house appraisal value (LKR),log,OLS,1523.0,0.41,none,conventional hedonic model; SE and p value in separate columns; adj. R2,semi_elasticity,46.7,5.2,100*b/1 (per unit count),reported,0.22496579409640255,0.0250497243961733,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.980769230769232,1513.0,count,,2012.0,Sri Lanka,Asia,Lower middle income,2003.0,2004.0,single_family,appraisal,journal,False,True,unknown,,2003.5,ols,journal,True,True,True
1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de:T3-c1,3,1,11,Number of toilets (0/1/2),bathrooms,A_structural,level,"count (0 = none, 1 = one, 2 = two or more sealed toilets)",0.334,0.052,,0.0,***,,,high,,ln of house appraisal value (LKR),log,OLS,1491.0,0.45,none,adjusted hedonic model with household socio-economic characteristics; SE and p value in separate columns; adj. R2,semi_elasticity,33.4,5.2,100*b/1 (per unit count),reported,0.16462632663858204,0.025630446063491817,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.423076923076923,1481.0,count,,2012.0,Sri Lanka,Asia,Lower middle income,2003.0,2004.0,single_family,appraisal,journal,False,True,unknown,,2003.5,ols,journal,True,True,True
1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de:T2-c1,2,1,10,Wall is made of red bricks or cement (otherwise reference),roof_materials,A_structural,binary,binary,0.929,0.113,,0.0,***,,,high,wall material,ln of house appraisal value (LKR),log,OLS,1523.0,0.41,none,conventional hedonic model; SE and p value in separate columns; adj. R2,pct_premium,151.58620292662155,28.611328068579404,100*(exp(b - se^2/2) - 1),reported,0.2067891864268558,0.025153044204773625,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.221238938053098,1513.0,binary,,2012.0,Sri Lanka,Asia,Lower middle income,2003.0,2004.0,single_family,appraisal,journal,False,True,unknown,,2003.5,ols,journal,True,True,True
1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de:T3-c1,3,1,11,Wall is made of red bricks or cement (otherwise reference),roof_materials,A_structural,binary,binary,0.847,0.111,,0.0,***,,,high,wall material,ln of house appraisal value (LKR),log,OLS,1491.0,0.45,none,adjusted hedonic model with household socio-economic characteristics; SE and p value in separate columns; adj. R2,pct_premium,131.8312383328244,25.892286564791856,100*(exp(b - se^2/2) - 1),reported,0.19449532296836514,0.025488761333516564,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.63063063063063,1481.0,binary,,2012.0,Sri Lanka,Asia,Lower middle income,2003.0,2004.0,single_family,appraisal,journal,False,True,unknown,,2003.5,ols,journal,True,True,False
1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de:T2-c1,2,1,10,Roof is made of tiles (otherwise reference case),roof_materials,A_structural,binary,binary,0.143,0.054,,0.008,**,,,high,roof material,ln of house appraisal value (LKR),log,OLS,1523.0,0.41,none,conventional hedonic model; SE and p value in separate columns; adj. R2,pct_premium,15.204888929806625,6.230140928996457,100*(exp(b - se^2/2) - 1),reported,0.06792328332438545,0.02564935174487283,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.648148148148148,1513.0,binary,,2012.0,Sri Lanka,Asia,Lower middle income,2003.0,2004.0,single_family,appraisal,journal,False,True,unknown,,2003.5,ols,journal,True,True,False
1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de:T3-c1,3,1,11,Roof is made of tiles (otherwise reference case),roof_materials,A_structural,binary,binary,0.138,0.053,,0.009,**,,,high,roof material,ln of house appraisal value (LKR),log,OLS,1491.0,0.45,none,adjusted hedonic model with household socio-economic characteristics; SE and p value in separate columns; adj. R2,pct_premium,14.636435034382679,6.084270416453147,100*(exp(b - se^2/2) - 1),reported,0.06750468447641196,0.025925712153984298,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6037735849056607,1481.0,binary,,2012.0,Sri Lanka,Asia,Lower middle income,2003.0,2004.0,single_family,appraisal,journal,False,True,unknown,,2003.5,ols,journal,True,True,False
1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de:T2-c1,2,1,10,Mean household income by municipality (ln),income,F_neighbourhood,log,"currency (LKR, mean household income by municipality), log",0.355,0.112,,0.002,***,,,high,,ln of house appraisal value (LKR),log,OLS,1523.0,0.41,none,conventional hedonic model; SE and p value in separate columns; adj. R2,elasticity,0.355,0.112,b (log-log),reported,0.08121826907175965,0.02562379193249882,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1696428571428568,1513.0,currency log,,2012.0,Sri Lanka,Asia,Lower middle income,2003.0,2004.0,single_family,appraisal,journal,False,True,unknown,,2003.5,ols,journal,True,True,False
1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de:T3-c1,3,1,11,Mean household income by municipality (ln),income,F_neighbourhood,log,"currency (LKR, mean household income by municipality), log",0.31,0.109,,0.005,***,,,high,,ln of house appraisal value (LKR),log,OLS,1491.0,0.45,none,adjusted hedonic model with household socio-economic characteristics; SE and p value in separate columns; adj. R2,elasticity,0.31,0.109,b (log-log),reported,0.07370126371713216,0.02591431530699163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8440366972477062,1481.0,currency log,,2012.0,Sri Lanka,Asia,Lower middle income,2003.0,2004.0,single_family,appraisal,journal,False,True,unknown,,2003.5,ols,journal,True,True,False
1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de:T2-c1,2,1,10,Distance to road in km (ln),highway_distance,D_location,log,km,-0.071,0.022,,0.001,***,,,high,distance to paved road,ln of house appraisal value (LKR),log,OLS,1523.0,0.41,none,conventional hedonic model; SE and p value in separate columns; adj. R2,elasticity,-0.071,0.022,b (log-log),reported,-0.08268495853207729,0.025620691376136626,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.227272727272727,1513.0,km,,2012.0,Sri Lanka,Asia,Lower middle income,2003.0,2004.0,single_family,appraisal,journal,False,True,unknown,,2003.5,ols,journal,True,True,False
1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de,1ce55be799df6cb17762fb0541fe95340687f3de:T3-c1,3,1,11,Distance to road in km (ln),highway_distance,D_location,log,km,-0.071,0.021,,0.0,***,,,high,distance to paved road,ln of house appraisal value (LKR),log,OLS,1491.0,0.45,none,adjusted hedonic model with household socio-economic characteristics; SE and p value in separate columns; adj. R2,elasticity,-0.071,0.021,b (log-log),reported,-0.08751690421358357,0.02588528152796134,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.3809523809523805,1481.0,km,,2012.0,Sri Lanka,Asia,Lower middle income,2003.0,2004.0,single_family,appraisal,journal,False,True,unknown,,2003.5,ols,journal,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M1,2,1,29,Distance (100kms) to: Coastline,water_proximity,E_environment,level,100 km,-0.15,0.11,,,,,,high,distance to coastline in 100 km,ln house sale price,log,OLS,1013125.0,0.516,se,England 1996-2008,semi_elasticity,-0.15,0.11,100*b/100 (X per 100km->km),reported,-0.0013547800806881461,0.0009935053925046405,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3636363636363635,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M2,2,2,29,Distance (100kms) to: Coastline,water_proximity,E_environment,level,100 km,-0.15,0.08,,,**,,,high,distance to coastline in 100 km,ln house sale price,log,OLS,1013125.0,0.766,se,England 1996-2008,semi_elasticity,-0.15,0.08,100*b/100 (X per 100km->km),reported,-0.0018628210883895545,0.000993504580474429,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.875,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M3,2,3,29,Distance (100kms) to: Coastline,water_proximity,E_environment,level,100 km,-0.14,0.13,,,,,,high,distance to coastline in 100 km,ln house sale price,log,OLS,1013125.0,0.865,se,England 1996-2008,semi_elasticity,-0.14,0.13,100*b/100 (X per 100km->km),reported,-0.0010699292537258676,0.0009935057356025914,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.076923076923077,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M4,2,4,29,Distance (100kms) to: Coastline,water_proximity,E_environment,level,100 km,-0.53,0.24,,,***,,,high,distance to coastline in 100 km,ln house sale price,log,OLS,448936.0,0.854,se,"Metropolitan TTWAs (North West, West Midlands, London), sales within 2 km of nearest church",semi_elasticity,-0.53,0.24,100*b/100 (X per 100km->km),reported,-0.003295906551102407,0.0014924859854048636,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.2083333333333335,448926.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M5,2,5,29,Distance (100kms) to: Coastline,water_proximity,E_environment,level,100 km,-0.2,0.12,,,*,,,high,distance to coastline in 100 km,ln house sale price,log,OLS,1135234.0,0.854,se,All Great Britain,semi_elasticity,-0.2,0.12,100*b/100 (X per 100km->km),reported,-0.0015642545836930218,0.0009385527502158131,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6666666666666667,1135224.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M1,2,1,29,Distance (100kms) to: Rivers,water_proximity,E_environment,level,100 km,1.35,0.97,,,,,,high,distance to rivers in 100 km,ln house sale price,log,OLS,1013125.0,0.516,se,England 1996-2008,semi_elasticity,1.35,0.97,100*b/100 (X per 100km->km),reported,0.0013827136377325125,0.0009935053545189162,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3917525773195878,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,True
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M2,2,2,29,Distance (100kms) to: Rivers,water_proximity,E_environment,level,100 km,0.92,1.01,,,,,,high,distance to rivers in 100 km,ln house sale price,log,OLS,1013125.0,0.766,se,England 1996-2008,semi_elasticity,0.92,1.01,100*b/100 (X per 100km->km),reported,0.0009049756689450239,0.000993505897428776,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9108910891089109,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M3,2,3,29,Distance (100kms) to: Rivers,water_proximity,E_environment,level,100 km,-0.91,0.69,,,*,,,high,distance to rivers in 100 km,ln house sale price,log,OLS,1013125.0,0.865,se,England 1996-2008,semi_elasticity,-0.91,0.69,100*b/100 (X per 100km->km),reported,-0.0013102753055004752,0.0009935054514234373,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.318840579710145,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M4,2,4,29,Distance (100kms) to: Rivers,water_proximity,E_environment,level,100 km,-2.16,0.48,,,***,,,high,distance to rivers in 100 km,ln house sale price,log,OLS,448936.0,0.854,se,"Metropolitan TTWAs (North West, West Midlands, London), sales within 2 km of nearest church",semi_elasticity,-2.16,0.48,100*b/100 (X per 100km->km),reported,-0.006716071942161937,0.001492460431591541,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.500000000000001,448926.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M5,2,5,29,Distance (100kms) to: Rivers,water_proximity,E_environment,level,100 km,-1.05,0.62,,,*,,,high,distance to rivers in 100 km,ln house sale price,log,OLS,1135234.0,0.854,se,All Great Britain,semi_elasticity,-1.05,0.62,100*b/100 (X per 100km->km),reported,-0.0015894844330967383,0.0009385527128761692,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6935483870967742,1135224.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M1,2,1,29,Distance (100kms) to: National Parks,green_space,E_environment,level,100 km,0.22,0.09,,,**,,,high,distance to National Parks in 100 km,ln house sale price,log,OLS,1013125.0,0.516,se,England 1996-2008,semi_elasticity,0.22,0.09,100*b/100 (X per 100km->km),reported,0.002428563804197652,0.000993503374444494,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4444444444444446,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M2,2,2,29,Distance (100kms) to: National Parks,green_space,E_environment,level,100 km,0.17,0.06,,,**,,,high,distance to National Parks in 100 km,ln house sale price,log,OLS,1013125.0,0.766,se,England 1996-2008,semi_elasticity,0.17,0.06,100*b/100 (X per 100km->km),reported,0.0028149233762351147,0.0009935023680829815,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8333333333333335,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M3,2,3,29,Distance (100kms) to: National Parks,green_space,E_environment,level,100 km,-0.24,0.09,,,***,,,high,distance to National Parks in 100 km,ln house sale price,log,OLS,1013125.0,0.865,se,England 1996-2008,semi_elasticity,-0.24,0.09,100*b/100 (X per 100km->km),reported,-0.002649340846774138,0.0009935028175403018,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6666666666666665,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M4,2,4,29,Distance (100kms) to: National Parks,green_space,E_environment,level,100 km,-0.4,0.14,,,***,,,high,distance to National Parks in 100 km,ln house sale price,log,OLS,448936.0,0.854,se,"Metropolitan TTWAs (North West, West Midlands, London), sales within 2 km of nearest church",semi_elasticity,-0.4,0.14,100*b/100 (X per 100km->km),reported,-0.004264230063845008,0.0014924805223457528,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.857142857142857,448926.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M1,2,1,29,Distance (100kms) to: Nature Reserves,green_space,E_environment,level,100 km,-0.54,0.2,,,***,,,high,distance to nature reserves in 100 km,ln house sale price,log,OLS,1013125.0,0.516,se,England 1996-2008,semi_elasticity,-0.54,0.2,100*b/100 (X per 100km->km),reported,-0.0026824573705355372,0.0009935027298279768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.7,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M2,2,2,29,Distance (100kms) to: Nature Reserves,green_space,E_environment,level,100 km,-0.42,0.19,,,***,,,high,distance to nature reserves in 100 km,ln house sale price,log,OLS,1013125.0,0.766,se,England 1996-2008,semi_elasticity,-0.42,0.19,100*b/100 (X per 100km->km),reported,-0.002196166534233326,0.0009935039083436474,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.2105263157894735,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M3,2,3,29,Distance (100kms) to: Nature Reserves,green_space,E_environment,level,100 km,-0.07,0.23,,,,,,high,distance to nature reserves in 100 km,ln house sale price,log,OLS,1013125.0,0.865,se,England 1996-2008,semi_elasticity,-0.07,0.23,100*b/100 (X per 100km->km),reported,-0.00030237147008260165,0.000993506258842834,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.30434782608695654,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M4,2,4,29,Distance (100kms) to: Nature Reserves,green_space,E_environment,level,100 km,-0.28,0.51,,,,,,high,distance to nature reserves in 100 km,ln house sale price,log,OLS,448936.0,0.854,se,"Metropolitan TTWAs (North West, West Midlands, London), sales within 2 km of nearest church",semi_elasticity,-0.28,0.51,100*b/100 (X per 100km->km),reported,-0.0008194082459600968,0.0014924935908558904,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5490196078431373,448926.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M2,2,2,30,Distance to station,transit_distance,D_location,level,100 km,-1.15,0.25,,,***,,,high,distance to railway station in 100 km (table unit header),ln house sale price,log,OLS,1013125.0,0.766,se,England 1996-2008,semi_elasticity,-1.15,0.25,100*b/100 (X per 100km->km),reported,-0.004570081274306839,0.000993495929197139,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.6,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M3,2,3,30,Distance to station,transit_distance,D_location,level,100 km,-0.14,0.21,,,,,,high,distance to railway station in 100 km (table unit header),ln house sale price,log,OLS,1013125.0,0.865,se,England 1996-2008,semi_elasticity,-0.14,0.21,100*b/100 (X per 100km->km),reported,-0.0006623373908927749,0.0009935060863391623,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6666666666666667,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M4,2,4,30,Distance to station,transit_distance,D_location,level,100 km,-0.15,0.58,,,,,,high,distance to railway station in 100 km (table unit header),ln house sale price,log,OLS,448936.0,0.854,se,"Metropolitan TTWAs (North West, West Midlands, London), sales within 2 km of nearest church",semi_elasticity,-0.15,0.58,100*b/100 (X per 100km->km),reported,-0.0003859898226016988,0.0014924939807265684,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.25862068965517243,448926.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M5,2,5,30,Distance to station,transit_distance,D_location,level,100 km,0.06,0.2,,,,,,high,distance to railway station in 100 km (table unit header),ln house sale price,log,OLS,1135234.0,0.854,se,All Great Britain,semi_elasticity,0.06,0.2,100*b/100 (X per 100km->km),reported,0.00028156615838480215,0.0009385538612826739,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3,1135224.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M2,2,2,30,Distance to motorways,highway_distance,D_location,level,100 km,-0.27,0.07,,,***,,,high,,ln house sale price,log,OLS,1013125.0,0.766,se,England 1996-2008,semi_elasticity,-0.27,0.07,100*b/100 (X per 100km->km),reported,-0.0038320676082314997,0.0009934990095414999,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.857142857142857,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M3,2,3,30,Distance to motorways,highway_distance,D_location,level,100 km,-0.17,0.11,,,,,,high,,ln house sale price,log,OLS,1013125.0,0.865,se,England 1996-2008,semi_elasticity,-0.17,0.11,100*b/100 (X per 100km->km),reported,-0.001535417023976533,0.000993505133161286,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5454545454545456,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M4,2,4,30,Distance to motorways,highway_distance,D_location,level,100 km,-0.38,0.41,,,,,,high,,ln house sale price,log,OLS,448936.0,0.854,se,"Metropolitan TTWAs (North West, West Midlands, London), sales within 2 km of nearest church",semi_elasticity,-0.38,0.41,100*b/100 (X per 100km->km),reported,-0.0013832858836880168,0.001492492663979176,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.926829268292683,448926.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M5,2,5,30,Distance to motorways,highway_distance,D_location,level,100 km,-0.06,0.1,,,,,,high,,ln house sale price,log,OLS,1135234.0,0.854,se,All Great Britain,semi_elasticity,-0.06,0.1,100*b/100 (X per 100km->km),reported,-0.0005631322498023422,0.0009385537496705704,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6,1135224.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M2,2,2,30,Distance to primary road,highway_distance,D_location,level,100 km,0.69,0.38,,,,,,high,,ln house sale price,log,OLS,1013125.0,0.766,se,England 1996-2008,semi_elasticity,0.69,0.38,100*b/100 (X per 100km->km),reported,0.0018039953538469182,0.0009935046876258392,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8157894736842104,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M3,2,3,30,Distance to primary road,highway_distance,D_location,level,100 km,-0.17,0.17,,,,,,high,,ln house sale price,log,OLS,1013125.0,0.865,se,England 1996-2008,semi_elasticity,-0.17,0.17,100*b/100 (X per 100km->km),reported,-0.0009935058139380248,0.0009935058139380248,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M4,2,4,30,Distance to primary road,highway_distance,D_location,level,100 km,0.06,0.46,,,,,,high,,ln house sale price,log,OLS,448936.0,0.854,se,"Metropolitan TTWAs (North West, West Midlands, London), sales within 2 km of nearest church",semi_elasticity,0.06,0.46,100*b/100 (X per 100km->km),reported,0.0001946731387340268,0.001492494063627539,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.13043478260869565,448926.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M5,2,5,30,Distance to primary road,highway_distance,D_location,level,100 km,0.1,0.18,,,,,,high,,ln house sale price,log,OLS,1135234.0,0.854,se,All Great Britain,semi_elasticity,0.1,0.18,100*b/100 (X per 100km->km),reported,0.0005214187616115852,0.0009385537709008532,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5555555555555556,1135224.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M2,2,2,30,Distance to A-road,highway_distance,D_location,level,100 km,-0.64,0.24,,,***,,,high,,ln house sale price,log,OLS,1013125.0,0.766,se,England 1996-2008,semi_elasticity,-0.64,0.24,100*b/100 (X per 100km->km),reported,-0.0026493408467741382,0.0009935028175403018,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.666666666666667,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M3,2,3,30,Distance to A-road,highway_distance,D_location,level,100 km,0.16,0.2,,,,,,high,,ln house sale price,log,OLS,1013125.0,0.865,se,England 1996-2008,semi_elasticity,0.16,0.2,100*b/100 (X per 100km->km),reported,0.000794804792363149,0.0009935059904539363,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7999999999999999,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M4,2,4,30,Distance to A-road,highway_distance,D_location,level,100 km,0.33,0.58,,,,,,high,,ln house sale price,log,OLS,448936.0,0.854,se,"Metropolitan TTWAs (North West, West Midlands, London), sales within 2 km of nearest church",semi_elasticity,0.33,0.58,100*b/100 (X per 100km->km),reported,0.0008491773668104426,0.0014924935537880505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5689655172413793,448926.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M5,2,5,30,Distance to A-road,highway_distance,D_location,level,100 km,0.51,0.26,,,**,,,high,,ln house sale price,log,OLS,1135234.0,0.854,se,All Great Britain,semi_elasticity,0.51,0.26,100*b/100 (X per 100km->km),reported,0.0018410064502346769,0.0009385523079627765,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9615384615384615,1135224.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M2,2,2,30,Distance to School,school_distance,D_location,level,100 km,-0.17,0.27,,,,,,high,distance to nearest primary school; interacted with value added (interaction not extracted),ln house sale price,log,OLS,1013125.0,0.766,se,England 1996-2008,semi_elasticity,-0.17,0.27,100*b/100 (X per 100km->km),reported,-0.0006255408839985259,0.000993506109880012,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6296296296296297,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M3,2,3,30,Distance to School,school_distance,D_location,level,100 km,0.85,0.33,,,***,,,high,distance to nearest primary school; interacted with value added (interaction not extracted),ln house sale price,log,OLS,1013125.0,0.865,se,England 1996-2008,semi_elasticity,0.85,0.33,100*b/100 (X per 100km->km),reported,0.0025590230107125846,0.000993503051217827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5757575757575757,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M4,2,4,30,Distance to School,school_distance,D_location,level,100 km,4.49,1.34,,,***,,,high,distance to nearest primary school; interacted with value added (interaction not extracted),ln house sale price,log,OLS,448936.0,0.854,se,"Metropolitan TTWAs (North West, West Midlands, London), sales within 2 km of nearest church",semi_elasticity,4.49,1.34,100*b/100 (X per 100km->km),reported,0.005000906474282805,0.0014924754288505476,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3507462686567164,448926.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M2,2,2,30,Distance to TTWA centre,cbd_distance,D_location,level,100 km,0.98,0.14,,,***,,,high,distance to Travel-to-Work-Area centre,ln house sale price,log,OLS,1013125.0,0.766,se,England 1996-2008,semi_elasticity,0.98,0.14,100*b/100 (X per 100km->km),reported,0.006954375955279956,0.0009934822793257081,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.999999999999999,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M3,2,3,30,Distance to TTWA centre,cbd_distance,D_location,level,100 km,-0.61,0.27,,,**,,,high,distance to Travel-to-Work-Area centre,ln house sale price,log,OLS,1013125.0,0.865,se,England 1996-2008,semi_elasticity,-0.61,0.27,100*b/100 (X per 100km->km),reported,-0.00224458266273745,0.0009935038015395272,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.259259259259259,1013115.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M4,2,4,30,Distance to TTWA centre,cbd_distance,D_location,level,100 km,-1.09,0.49,,,**,,,high,distance to Travel-to-Work-Area centre,ln house sale price,log,OLS,448936.0,0.854,se,"Metropolitan TTWAs (North West, West Midlands, London), sales within 2 km of nearest church",semi_elasticity,-1.09,0.49,100*b/100 (X per 100km->km),reported,-0.0033200195802599855,0.0014924858663554062,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.2244897959183674,448926.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6,22e62fc82c4ed1c605cd41b5c6124856f4afd7c6:T2-M5,2,5,30,Distance to TTWA centre,cbd_distance,D_location,level,100 km,-0.6,0.26,,,**,,,high,distance to Travel-to-Work-Area centre,ln house sale price,log,OLS,1135234.0,0.854,se,All Great Britain,semi_elasticity,-0.6,0.26,100*b/100 (X per 100km->km),reported,-0.0021658885317038016,0.0009385516970716476,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3076923076923075,1135224.0,100km,,2014.0,United Kingdom,Europe,High income,1996.0,2008.0,mixed,transaction,working_paper,True,True,clustered,,2002.0,ols,other,True,True,False
2344ebd24eeebb31c33011f3e72a12383c3c1e88,2344ebd24eeebb31c33011f3e72a12383c3c1e88,2344ebd24eeebb31c33011f3e72a12383c3c1e88:T5-c1,5,1,9,Ln_S***,living_area,A_structural,log,m2,1.245,,32.311,0.0,***,,,high,Log of gross floor area (m2),"Ln(P), total price of new residence in 10,000 RMB",log,OLS,378.0,0.782,t,Final model after collinearity elimination; t-ratio and p-value in separate columns,elasticity,1.245,0.038531769366469626,b (log-log),|b/t|,0.8598702830185788,0.026612307976187015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.311,368.0,m2,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
2344ebd24eeebb31c33011f3e72a12383c3c1e88,2344ebd24eeebb31c33011f3e72a12383c3c1e88,2344ebd24eeebb31c33011f3e72a12383c3c1e88:T5-c1,5,1,9,Ln_DC***,cbd_distance,D_location,log,km,-0.268,,-0.924,0.0,***,,,medium,"Log straight-line distance to CBD (km); printed t-ratio -0.924 inconsistent with p=0.000 and ***, as printed","Ln(P), total price of new residence in 10,000 RMB",log,OLS,378.0,0.782,t,Final model after collinearity elimination; t-ratio and p-value in separate columns,elasticity,-0.268,0.29004329004329005,b (log-log),|b/t|,-0.04811105211367316,0.05206823821826099,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.924,368.0,km,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
2344ebd24eeebb31c33011f3e72a12383c3c1e88,2344ebd24eeebb31c33011f3e72a12383c3c1e88,2344ebd24eeebb31c33011f3e72a12383c3c1e88:T5-c1,5,1,9,HB***,floor_level,A_structural,dummy,binary,-0.142,,-4.538,0.0,***,,,high,"High-rise building above 12 floors dummy (building height, not unit floor)","Ln(P), total price of new residence in 10,000 RMB",log,OLS,378.0,0.782,t,Final model after collinearity elimination; t-ratio and p-value in separate columns,pct_premium,-13.2803403741924,2.7149012433010085,100*(exp(b - se^2/2) - 1),|b/t|,-0.23020606264099502,0.050728528567870204,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.538,368.0,binary,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
2344ebd24eeebb31c33011f3e72a12383c3c1e88,2344ebd24eeebb31c33011f3e72a12383c3c1e88,2344ebd24eeebb31c33011f3e72a12383c3c1e88:T5-c1,5,1,9,Ln_DS***,transit_distance,D_location,log,km,-0.061,,-3.174,0.002,***,,,high,Log straight-line distance to nearest subway station (km),"Ln(P), total price of new residence in 10,000 RMB",log,OLS,378.0,0.782,t,Final model after collinearity elimination; t-ratio and p-value in separate columns,elasticity,-0.061,0.01921865154379332,b (log-log),|b/t|,-0.1632369072374484,0.051429397365295657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.174,368.0,km,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
2344ebd24eeebb31c33011f3e72a12383c3c1e88,2344ebd24eeebb31c33011f3e72a12383c3c1e88,2344ebd24eeebb31c33011f3e72a12383c3c1e88:T5-c1,5,1,9,E**,school_quality,F_neighbourhood,dummy,binary,0.09,,2.097,0.037,**,,,high,Within 825 m buffer of a Key Primary School (attendance zone proxy),"Ln(P), total price of new residence in 10,000 RMB",log,OLS,378.0,0.782,t,Final model after collinearity elimination; t-ratio and p-value in separate columns,pct_premium,9.31670165122236,4.69602696869189,100*(exp(b - se^2/2) - 1),|b/t|,0.1086663563477336,0.051819912421427555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.097,368.0,binary,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
2344ebd24eeebb31c33011f3e72a12383c3c1e88,2344ebd24eeebb31c33011f3e72a12383c3c1e88,2344ebd24eeebb31c33011f3e72a12383c3c1e88:T5-c1,5,1,9,SN*,sunlight,E_environment,dummy,binary,0.044,,1.69,0.092,*,,,high,South-facing residence dummy,"Ln(P), total price of new residence in 10,000 RMB",log,OLS,378.0,0.782,t,Final model after collinearity elimination; t-ratio and p-value in separate columns,pct_premium,4.462824560622036,2.720664119236185,100*(exp(b - se^2/2) - 1),|b/t|,0.08775744916779234,0.05192748471467002,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.69,368.0,binary,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T7-c1,7,1,14,No_rooms,bedrooms,A_structural,level,count,0.31,,22.75,,***,,,high,"Number of rooms (all rooms, not only bedrooms)",ln(Price): log sale price of the apartment,log,OLS,765.0,0.4,t,"Bivariate regression: single regressor No_rooms, full sample of apartment transactions 2014-2018",semi_elasticity,31.0,1.3626373626373625,100*b/1 (per unit count),|b/t|,0.6377373317266176,0.02803241018578539,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.75,755.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T8-c1,8,1,15,No_rooms,bedrooms,A_structural,level,count,0.3,,22.31,,***,,,high,"Number of rooms (all rooms, not only bedrooms)",ln(Price): log sale price of the apartment,log,OLS,765.0,0.41,t,Bivariate regression: single regressor No_rooms plus Duration control,semi_elasticity,30.0,1.3446884805020172,100*b/1 (per unit count),|b/t|,0.6303326074052893,0.028253366535423104,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.31,755.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T7-c2,7,2,14,S_useful,living_area,A_structural,level,m2,0.01,,36.13,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,760.0,0.63,t,"Bivariate regression: single regressor S_useful, full sample of apartment transactions 2014-2018",semi_elasticity,1.0,0.02767783005812344,100*b/1 (X per m2->m2),|b/t|,0.7969337617966491,0.022057397226588688,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),36.13,750.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T8-c2,8,2,15,S_useful,living_area,A_structural,level,m2,0.01,,35.48,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,760.0,0.63,t,Bivariate regression: single regressor S_useful plus Duration control,semi_elasticity,1.0,0.028184892897406996,100*b/1 (X per m2->m2),|b/t|,0.7916112820618978,0.022311479201293623,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.48,750.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T7-c3,7,3,14,S_constructed,living_area,A_structural,level,m2,0.01,,35.2,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,762.0,0.62,t,"Bivariate regression: single regressor S_constructed, full sample of apartment transactions 2014-2018",semi_elasticity,1.0,0.028409090909090908,100*b/1 (X per m2->m2),|b/t|,0.7888649691609271,0.022410936623889967,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.2,752.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T8-c3,8,3,15,S_constructed,living_area,A_structural,level,m2,0.01,,34.56,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,762.0,0.62,t,Bivariate regression: single regressor S_constructed plus Duration control,semi_elasticity,1.0,0.028935185185185182,100*b/1 (X per m2->m2),|b/t|,0.7833546032972407,0.02266651051207294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.56,752.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T7-c4,7,4,14,Comfort,condition,A_structural,binary,binary,0.52,,11.05,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,734.0,0.14,t,"Bivariate regression: single regressor Comfort, full sample of apartment transactions 2014-2018",pct_premium,68.01662276732216,7.915424233877113,100*(exp(b - se^2/2) - 1),|b/t|,0.3798838133462677,0.034378625642196174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.05,724.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T8-c4,8,4,15,Comfort,condition,A_structural,binary,binary,0.51,,10.72,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,734.0,0.15,t,Bivariate regression: single regressor Comfort plus Duration control,pct_premium,66.34076965477256,7.922560722223899,100*(exp(b - se^2/2) - 1),|b/t|,0.3701134991568745,0.03452551298105172,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.72,724.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T7-c5,7,5,14,Floor,floor_level,A_structural,level,count,-0.02,,-4.26,,***,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,765.0,0.02,t,"Bivariate regression: single regressor Floor, full sample of apartment transactions 2014-2018",semi_elasticity,-2.0,0.4694835680751174,100*b/1 (per unit count),|b/t|,-0.15320692396775779,0.03596406665909808,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.26,755.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T8-c5,8,5,15,Floor,floor_level,A_structural,level,count,-0.02,,-4.23,,***,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,765.0,0.05,t,Bivariate regression: single regressor Floor plus Duration control,semi_elasticity,-2.0,0.4728132387706856,100*b/1 (per unit count),|b/t|,-0.15215306612011023,0.03596999199056979,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.23,755.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T7-c6,7,6,14,No_bathrooms,bathrooms,A_structural,level,count,0.49,,17.23,,***,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,765.0,0.28,t,"Bivariate regression: single regressor No_bathrooms, full sample of apartment transactions 2014-2018",semi_elasticity,49.0,2.8438769587928032,100*b/1 (per unit count),|b/t|,0.5312557508279308,0.030833183449096385,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.23,755.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T8-c6,8,6,15,No_bathrooms,bathrooms,A_structural,level,count,0.48,,17.01,,***,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,765.0,0.29,t,Bivariate regression: single regressor No_bathrooms plus Duration control,semi_elasticity,48.0,2.8218694885361546,100*b/1 (per unit count),|b/t|,0.5263605554522475,0.03094418315415916,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.01,755.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T7-c7,7,7,14,No_balconies,terrace_balcony,C_exterior,level,count,0.29,,8.71,,***,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,706.0,0.1,t,"Bivariate regression: single regressor No_balconies, full sample of apartment transactions 2014-2018",semi_elasticity,28.999999999999996,3.3295063145809407,100*b/1 (per unit count),|b/t|,0.3135073549981706,0.035993955797723375,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.71,696.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T8-c7,8,7,15,No_balconies,terrace_balcony,C_exterior,level,count,0.28,,8.47,,***,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,706.0,0.11,t,Bivariate regression: single regressor No_balconies plus Duration control,semi_elasticity,28.000000000000004,3.3057851239669422,100*b/1 (per unit count),|b/t|,0.30568636777518854,0.03609048025681092,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.47,696.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T7-c8,7,8,14,No_parking,parking,A_structural,level,count,0.3,,4.74,,***,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,317.0,0.07,t,"Bivariate regression: single regressor No_parking, full sample of apartment transactions 2014-2018",semi_elasticity,30.0,6.329113924050632,100*b/1 (per unit count),|b/t|,0.2611391496139819,0.055092647597886485,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.74,307.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T8-c8,8,8,15,No_parking,parking,A_structural,level,count,0.28,,4.39,,***,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,317.0,0.07,t,Bivariate regression: single regressor No_parking plus Duration control,semi_elasticity,28.000000000000004,6.378132118451026,100*b/1 (per unit count),|b/t|,0.2430382062058144,0.05536177817900101,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.39,307.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T7-c11,7,11,14,Structure,roof_materials,A_structural,binary,binary,0.08,,1.65,,†,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,669.0,0.0,t,"Bivariate regression: single regressor Structure, full sample of apartment transactions 2014-2018",pct_premium,8.201453061035036,5.252300934181618,100*(exp(b - se^2/2) - 1),|b/t|,0.06414251630948829,0.038874252308780784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.65,659.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T8-c11,8,11,15,Structure,roof_materials,A_structural,binary,binary,0.1,,1.97,,*,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,669.0,0.03,t,Bivariate regression: single regressor Structure plus Duration control,pct_premium,10.37479758532347,5.610004660282476,100*(exp(b - se^2/2) - 1),|b/t|,0.07651533312171237,0.03884027062015856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.97,659.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T9-c1,9,1,16,Height_regime_1,storeys,A_structural,dummy,binary,-0.23,,-7.75,,***,,,high,1 if building height regime is Ground Floor +10 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.07,t,Bivariate regression: single height-regime dummy Height_regime_1 (base = all other height regimes),pct_premium,-20.58162128912644,2.3579706913002174,100*(exp(b - se^2/2) - 1),|b/t|,-0.27146025103791244,0.03502712916618225,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.75,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T10-c1,10,1,16,Height_regime_1,storeys,A_structural,dummy,binary,-0.22,,-7.35,,***,,,high,1 if building height regime is Ground Floor +10 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.09,t,Bivariate regression: single height-regime dummy Height_regime_1 plus Duration control,pct_premium,-19.78406190515458,2.4020970823366703,100*(exp(b - se^2/2) - 1),|b/t|,-0.2584086451506488,0.03515763879600665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.35,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T9-c2,9,2,16,Height_regime_2,storeys,A_structural,dummy,binary,0.18,,2.06,,*,,,high,1 if building height regime is Ground Floor +11 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.01,t,Bivariate regression: single height-regime dummy Height_regime_2 (base = all other height regimes),pct_premium,19.265568243566,10.461122590384747,100*(exp(b - se^2/2) - 1),|b/t|,0.07476126658991274,0.03629187698539453,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.06,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T10-c2,10,2,16,Height_regime_2,storeys,A_structural,dummy,binary,0.18,,2.04,,*,,,high,1 if building height regime is Ground Floor +11 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.03,t,Bivariate regression: single height-regime dummy Height_regime_2 plus Duration control,pct_premium,19.256597409174937,10.563682615780676,100*(exp(b - se^2/2) - 1),|b/t|,0.07403942736970325,0.03629383694593297,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.04,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T9-c3,9,3,16,Height_regime_3,storeys,A_structural,dummy,binary,0.3,,3.09,,**,,,high,1 if building height regime is Ground Floor +2 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.01,t,Bivariate regression: single height-regime dummy Height_regime_3 (base = all other height regimes),pct_premium,34.3511918753137,13.105425316271875,100*(exp(b - se^2/2) - 1),|b/t|,0.11175219772321075,0.03616575978097436,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.09,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T10-c3,10,3,16,Height_regime_3,storeys,A_structural,dummy,binary,0.27,,2.87,,**,,,high,1 if building height regime is Ground Floor +2 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.03,t,Bivariate regression: single height-regime dummy Height_regime_3 plus Duration control,pct_premium,30.41803921657007,12.323707376236126,100*(exp(b - se^2/2) - 1),|b/t|,0.10388485005727441,0.03619681186664613,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.87,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T9-c4,9,4,16,Height_regime_4,storeys,A_structural,dummy,binary,-0.01,,-0.23,,,,,high,1 if building height regime is Ground Floor +3 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.0,t,Bivariate regression: single height-regime dummy Height_regime_4 (base = all other height regimes),pct_premium,-1.0885499042591729,4.3045644945616,100*(exp(b - se^2/2) - 1),|b/t|,-0.008370263809080588,0.036392451343828645,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.23,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T10-c4,10,4,16,Height_regime_4,storeys,A_structural,dummy,binary,-0.05,,-0.99,,,,,high,1 if building height regime is Ground Floor +3 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.02,t,Bivariate regression: single height-regime dummy Height_regime_4 plus Duration control,pct_premium,-4.998298123948352,4.80418901262987,100*(exp(b - se^2/2) - 1),|b/t|,-0.03600642578615333,0.03637012705672053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.99,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T9-c5,9,5,16,Height_regime_5,storeys,A_structural,dummy,binary,0.04,,1.04,,,,,high,1 if building height regime is Ground Floor +4 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.0,t,Bivariate regression: single height-regime dummy Height_regime_5 (base = all other height regimes),pct_premium,4.00412283685363,4.003118362278417,100*(exp(b - se^2/2) - 1),|b/t|,0.037822393154129844,0.036367685725124846,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.04,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T10-c5,10,5,16,Height_regime_5,storeys,A_structural,dummy,binary,0.04,,1.09,,,,,high,1 if building height regime is Ground Floor +4 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.02,t,Bivariate regression: single height-regime dummy Height_regime_5 plus Duration control,pct_premium,4.011018640281749,3.819489079605094,100*(exp(b - se^2/2) - 1),|b/t|,0.03963798587870104,0.03636512465935875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.09,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T9-c6,9,6,16,Height_regime_6,storeys,A_structural,dummy,binary,0.23,,3.37,,***,,,high,1 if building height regime is Ground Floor +5 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.01,t,Bivariate regression: single height-regime dummy Height_regime_6 (base = all other height regimes),pct_premium,25.567216566807694,8.589851699815428,100*(exp(b - se^2/2) - 1),|b/t|,0.1217346930087746,0.03612305430527436,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.37,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T10-c6,10,6,16,Height_regime_6,storeys,A_structural,dummy,binary,0.19,,2.78,,**,,,high,1 if building height regime is Ground Floor +5 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.03,t,Bivariate regression: single height-regime dummy Height_regime_6 plus Duration control,pct_premium,20.642864038431274,8.264655523556755,100*(exp(b - se^2/2) - 1),|b/t|,0.10066067472932196,0.03620887580191438,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.78,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T9-c7,9,7,16,Height_regime_7,storeys,A_structural,dummy,binary,0.17,,2.19,,*,,,high,1 if building height regime is Ground Floor +6 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.01,t,Bivariate regression: single height-regime dummy Height_regime_7 (base = all other height regimes),pct_premium,18.173906258757498,9.200996562760828,100*(exp(b - se^2/2) - 1),|b/t|,0.0794503079426398,0.036278679425862916,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.19,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T10-c7,10,7,16,Height_regime_7,storeys,A_structural,dummy,binary,0.17,,2.21,,*,,,high,1 if building height regime is Ground Floor +6 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.03,t,Bivariate regression: single height-regime dummy Height_regime_7 plus Duration control,pct_premium,18.18032147236215,9.117729625541273,100*(exp(b - se^2/2) - 1),|b/t|,0.08017123892720256,0.036276578700091655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.21,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T9-c8,9,8,16,Height_regime_8,storeys,A_structural,dummy,binary,0.06,,0.71,,,,,high,1 if building height regime is Ground Floor +7 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.0,t,Bivariate regression: single height-regime dummy Height_regime_8 (base = all other height regimes),pct_premium,5.805178663123223,8.973266590524165,100*(exp(b - se^2/2) - 1),|b/t|,0.025830923662282835,0.036381582622933575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.71,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T10-c8,10,8,16,Height_regime_8,storeys,A_structural,dummy,binary,0.07,,0.86,,,,,high,1 if building height regime is Ground Floor +7 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.02,t,Bivariate regression: single height-regime dummy Height_regime_8 plus Duration control,pct_premium,6.896126714465689,8.729717754394787,100*(exp(b - se^2/2) - 1),|b/t|,0.03128328574149982,0.03637591365290677,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.86,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T9-c9,9,9,16,Height_regime_9,storeys,A_structural,dummy,binary,0.13,,3.38,,***,,,high,1 if building height regime is Ground Floor +8 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.01,t,Bivariate regression: single height-regime dummy Height_regime_9 (base = all other height regimes),pct_premium,13.798636607403015,4.380109166633161,100*(exp(b - se^2/2) - 1),|b/t|,0.1220905468595488,0.03612146356791385,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.38,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T10-c9,10,9,16,Height_regime_9,storeys,A_structural,dummy,binary,0.14,,3.63,,***,,,high,1 if building height regime is Ground Floor +8 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.04,t,Bivariate regression: single height-regime dummy Height_regime_9 plus Duration control,pct_premium,14.9418628644556,4.436317681543026,100*(exp(b - se^2/2) - 1),|b/t|,0.1309712593264584,0.036080236729051904,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.63,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T9-c10,9,10,16,Height_regime_10,storeys,A_structural,dummy,binary,-0.05,,-0.66,,,,,high,1 if building height regime is Ground Floor +9 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.0,t,Bivariate regression: single height-regime dummy Height_regime_10 (base = all other height regimes),pct_premium,-5.149631557804213,7.206283518944804,100*(exp(b - se^2/2) - 1),|b/t|,-0.02401293315739747,0.036383232056662836,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.66,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T10-c10,10,10,16,Height_regime_10,storeys,A_structural,dummy,binary,-0.03,,-0.48,,,,,high,1 if building height regime is Ground Floor +9 Floors,ln(Price): log sale price of the apartment,log,OLS,765.0,0.02,t,Bivariate regression: single height-regime dummy Height_regime_10 plus Duration control,pct_premium,-3.1448018110717735,6.065284584678176,100*(exp(b - se^2/2) - 1),|b/t|,-0.017466323748954828,0.03638817447698923,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.48,755.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c1,11,1,17,No_rooms,bedrooms,A_structural,level,count,0.23,,9.19,,***,,,high,"Number of rooms (all rooms, not only bedrooms)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration not included",semi_elasticity,23.0,2.50272034820457,100*b/1 (per unit count),|b/t|,0.5842065600926486,0.06356981067384641,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.19,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,No_rooms,bedrooms,A_structural,level,count,0.24,,9.95,,***,,,high,"Number of rooms (all rooms, not only bedrooms)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,semi_elasticity,24.0,2.412060301507538,100*b/1 (per unit count),|b/t|,0.6147101201288447,0.06177991157073817,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.95,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c1,11,1,17,Comfort,condition,A_structural,binary,binary,0.34,,5.79,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration not included",pct_premium,40.252736135501024,8.25012402058069,100*(exp(b - se^2/2) - 1),|b/t|,0.4130195942405717,0.07133326325398476,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.79,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,Comfort,condition,A_structural,binary,binary,0.31,,5.21,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,pct_premium,36.101373831430415,8.112510276026393,100*(exp(b - se^2/2) - 1),|b/t|,0.37782987639681886,0.0725201298266447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.21,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c3,11,3,17,Comfort,condition,A_structural,binary,binary,0.26,,4.33,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration not included,pct_premium,29.459412310079045,7.787570959194011,100*(exp(b - se^2/2) - 1),|b/t|,0.32118259363543356,0.07417611862250198,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.33,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c4,11,4,17,Comfort,condition,A_structural,binary,binary,0.14,,2.54,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.75,t,Multivariate specification: useful surface + square; complete-case subsample; Duration not included,pct_premium,14.852785584430617,6.340091804724876,100*(exp(b - se^2/2) - 1),|b/t|,0.1951240850641541,0.07682050593076933,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.54,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,Comfort,condition,A_structural,binary,binary,0.2,,3.32,,**,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,21.91885483357334,7.357847940723915,100*(exp(b - se^2/2) - 1),|b/t|,0.2516723513898991,0.07580492511743948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.32,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,Comfort,condition,A_structural,binary,binary,0.12,,2.07,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,12.560388774052722,6.536213632344207,100*(exp(b - se^2/2) - 1),|b/t|,0.16004494992527651,0.07731640093008528,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.07,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c7,11,7,17,Comfort,condition,A_structural,binary,binary,0.26,,4.28,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration not included,pct_premium,29.45392763433925,7.878547255446278,100*(exp(b - se^2/2) - 1),|b/t|,0.31785044952466784,0.0742641237207168,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.28,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c8,11,8,17,Comfort,condition,A_structural,binary,binary,0.15,,2.51,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,183.0,0.72,t,Multivariate specification: constructed surface + square (Structure omitted); complete-case subsample; Duration not included,pct_premium,15.97614229080997,6.94323252626464,100*(exp(b - se^2/2) - 1),|b/t|,0.187449141439015,0.07468093284422908,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.51,173.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,Comfort,condition,A_structural,binary,binary,0.21,,3.26,,**,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,23.112109498487676,7.947005907696812,100*(exp(b - se^2/2) - 1),|b/t|,0.2474048556487383,0.0758910600149504,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.26,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,Comfort,condition,A_structural,binary,binary,0.12,,2.06,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,12.558548046768125,6.567942824734227,100*(exp(b - se^2/2) - 1),|b/t|,0.1592914504015278,0.07732594679685816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.06,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c1,11,1,17,Floor,floor_level,A_structural,level,count,-0.01,,-2.03,,*,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration not included",semi_elasticity,-1.0,0.4926108374384237,100*b/1 (per unit count),|b/t|,-0.1570292856479949,0.07735432790541621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.03,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,Floor,floor_level,A_structural,level,count,-0.01,,-1.49,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,semi_elasticity,-1.0,0.6711409395973155,100*b/1 (per unit count),|b/t|,-0.11591905394981178,0.07779802278510858,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.49,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c3,11,3,17,Floor,floor_level,A_structural,level,count,-0.01,,-1.45,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration not included,semi_elasticity,-1.0,0.6896551724137931,100*b/1 (per unit count),|b/t|,-0.11284730128956229,0.07782572502728434,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.45,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c4,11,4,17,Floor,floor_level,A_structural,level,count,-0.01,,-2.66,,**,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.75,t,Multivariate specification: useful surface + square; complete-case subsample; Duration not included,semi_elasticity,-1.0,0.37593984962406013,100*b/1 (per unit count),|b/t|,-0.2039673393366316,0.07667945087843293,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.66,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,Floor,floor_level,A_structural,level,count,-0.01,,-1.37,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,-1.0,0.7299270072992701,100*b/1 (per unit count),|b/t|,-0.10669416293216134,0.07787895104537323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.37,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,Floor,floor_level,A_structural,level,count,-0.01,,-2.42,,*,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,-1.0,0.4132231404958678,100*b/1 (per unit count),|b/t|,-0.18623298443757855,0.07695577869321428,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.42,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c7,11,7,17,Floor,floor_level,A_structural,level,count,-0.01,,-1.2,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration not included,semi_elasticity,-1.0,0.8333333333333334,100*b/1 (per unit count),|b/t|,-0.09357880867084666,0.07798234055903888,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c8,11,8,17,Floor,floor_level,A_structural,level,count,-0.01,,-2.09,,*,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,183.0,0.72,t,Multivariate specification: constructed surface + square (Structure omitted); complete-case subsample; Duration not included,semi_elasticity,-1.0,0.47846889952153115,100*b/1 (per unit count),|b/t|,-0.15693092304356518,0.0750865660495527,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.09,173.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,Floor,floor_level,A_structural,level,count,-0.01,,-1.35,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,-1.0,0.7407407407407407,100*b/1 (per unit count),|b/t|,-0.10515393275111268,0.07789180203786124,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.35,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,Floor,floor_level,A_structural,level,count,-0.01,,-2.19,,*,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,-1.0,0.45662100456621013,100*b/1 (per unit count),|b/t|,-0.16906479552348647,0.07719853676871528,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.19,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c1,11,1,17,No_bathrooms,bathrooms,A_structural,level,count,0.09,,1.92,,†,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration not included",semi_elasticity,9.0,4.6875,100*b/1 (per unit count),|b/t|,0.14871375690053495,0.07745508171902862,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.92,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,No_bathrooms,bathrooms,A_structural,level,count,0.03,,0.7,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,semi_elasticity,3.0,4.285714285714286,100*b/1 (per unit count),|b/t|,0.054746006305799545,0.07820858043685651,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c3,11,3,17,No_bathrooms,bathrooms,A_structural,level,count,0.07,,1.52,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration not included,semi_elasticity,7.000000000000001,4.605263157894737,100*b/1 (per unit count),|b/t|,0.11822069266068613,0.0777767714872935,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.52,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c4,11,4,17,No_bathrooms,bathrooms,A_structural,level,count,0.06,,1.41,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.75,t,Multivariate specification: useful surface + square; complete-case subsample; Duration not included,semi_elasticity,6.0,4.25531914893617,100*b/1 (per unit count),|b/t|,0.10977230965416428,0.07785270188238601,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.41,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,No_bathrooms,bathrooms,A_structural,level,count,0.04,,0.9,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,4.0,4.444444444444445,100*b/1 (per unit count),|b/t|,0.07031893818579951,0.07813215353977723,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,No_bathrooms,bathrooms,A_structural,level,count,0.03,,0.8,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,3.0,3.75,100*b/1 (per unit count),|b/t|,0.06253818193281793,0.07817272741602241,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c7,11,7,17,No_bathrooms,bathrooms,A_structural,level,count,0.09,,1.8,,†,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration not included,semi_elasticity,9.0,5.0,100*b/1 (per unit count),|b/t|,0.13960621092548198,0.07755900606971221,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c8,11,8,17,No_bathrooms,bathrooms,A_structural,level,count,0.08,,1.85,,†,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,183.0,0.72,t,Multivariate specification: constructed surface + square (Structure omitted); complete-case subsample; Duration not included,semi_elasticity,8.0,4.324324324324324,100*b/1 (per unit count),|b/t|,0.13928191920566704,0.07528752389495516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.85,173.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,No_bathrooms,bathrooms,A_structural,level,count,0.06,,1.14,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,6.0,5.2631578947368425,100*b/1 (per unit count),|b/t|,0.08893784421580979,0.07801565282088578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.14,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,No_bathrooms,bathrooms,A_structural,level,count,0.05,,1.19,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,5.0,4.201680672268908,100*b/1 (per unit count),|b/t|,0.09280572978466087,0.0779880082224041,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.19,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c1,11,1,17,No_balconies,terrace_balcony,C_exterior,level,count,-0.03,,-0.71,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration not included",semi_elasticity,-3.0,4.225352112676056,100*b/1 (per unit count),|b/t|,-0.05552569778801017,0.07820520815212702,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.71,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,No_balconies,terrace_balcony,C_exterior,level,count,-0.04,,-0.89,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,semi_elasticity,-4.0,4.49438202247191,100*b/1 (per unit count),|b/t|,-0.06954141625164179,0.07813642275465368,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.89,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c3,11,3,17,No_balconies,terrace_balcony,C_exterior,level,count,-0.05,,-1.12,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration not included,semi_elasticity,-5.0,4.464285714285714,100*b/1 (per unit count),|b/t|,-0.0873895527330593,0.07802638636880294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.12,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c4,11,4,17,No_balconies,terrace_balcony,C_exterior,level,count,-0.02,,-0.6,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.75,t,Multivariate specification: useful surface + square; complete-case subsample; Duration not included,semi_elasticity,-2.0,3.3333333333333335,100*b/1 (per unit count),|b/t|,-0.04694381579433043,0.07823969299055072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,No_balconies,terrace_balcony,C_exterior,level,count,-0.06,,-1.41,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,-6.0,4.25531914893617,100*b/1 (per unit count),|b/t|,-0.10977230965416428,0.07785270188238601,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.41,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,No_balconies,terrace_balcony,C_exterior,level,count,-0.03,,-0.82,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,-3.0,3.6585365853658534,100*b/1 (per unit count),|b/t|,-0.06409529150234007,0.0781649896370001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.82,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c7,11,7,17,No_balconies,terrace_balcony,C_exterior,level,count,-0.08,,-1.81,,†,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration not included,semi_elasticity,-8.0,4.41988950276243,100*b/1 (per unit count),|b/t|,-0.14036656109869525,0.07755058624237307,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.81,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c8,11,8,17,No_balconies,terrace_balcony,C_exterior,level,count,-0.05,,-1.21,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,183.0,0.72,t,Multivariate specification: constructed surface + square (Structure omitted); complete-case subsample; Duration not included,semi_elasticity,-5.0,4.132231404958678,100*b/1 (per unit count),|b/t|,-0.09160777460527436,0.07570890463245815,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.21,173.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,No_balconies,terrace_balcony,C_exterior,level,count,-0.09,,-1.97,,†,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,-9.0,4.568527918781726,100*b/1 (per unit count),|b/t|,-0.15249756513080967,0.07740993153848208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.97,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,No_balconies,terrace_balcony,C_exterior,level,count,-0.05,,-1.3,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,-5.0,3.8461538461538463,100*b/1 (per unit count),|b/t|,-0.10130006814979362,0.0779231293459951,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c1,11,1,17,No_parking,parking,A_structural,level,count,0.21,,3.05,,**,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration not included",semi_elasticity,21.0,6.885245901639345,100*b/1 (per unit count),|b/t|,0.23235608476109681,0.07618232287249077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.05,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,No_parking,parking,A_structural,level,count,0.23,,3.15,,**,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,semi_elasticity,23.0,7.301587301587302,100*b/1 (per unit count),|b/t|,0.23954372623574144,0.07604562737642585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.15,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c3,11,3,17,No_parking,parking,A_structural,level,count,0.09,,1.35,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration not included,semi_elasticity,9.0,6.666666666666667,100*b/1 (per unit count),|b/t|,0.10515393275111268,0.07789180203786124,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.35,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c4,11,4,17,No_parking,parking,A_structural,level,count,0.16,,2.53,,*,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.75,t,Multivariate specification: useful surface + square; complete-case subsample; Duration not included,semi_elasticity,16.0,6.32411067193676,100*b/1 (per unit count),|b/t|,0.19438496221732968,0.0768320008764149,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.53,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,No_parking,parking,A_structural,level,count,0.13,,1.71,,†,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,13.0,7.602339181286551,100*b/1 (per unit count),|b/t|,0.1327520924133248,0.07763280258089171,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.71,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,No_parking,parking,A_structural,level,count,0.19,,2.83,,**,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,19.0,6.713780918727916,100*b/1 (per unit count),|b/t|,0.21640987730547695,0.07646992130935581,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.83,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c7,11,7,17,No_parking,parking,A_structural,level,count,0.06,,0.82,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration not included,semi_elasticity,6.0,7.317073170731707,100*b/1 (per unit count),|b/t|,0.06409529150234007,0.0781649896370001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.82,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c8,11,8,17,No_parking,parking,A_structural,level,count,0.16,,2.43,,*,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,183.0,0.72,t,Multivariate specification: constructed surface + square (Structure omitted); complete-case subsample; Duration not included,semi_elasticity,16.0,6.584362139917695,100*b/1 (per unit count),|b/t|,0.18167499454258063,0.07476337223974511,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.43,173.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,No_parking,parking,A_structural,level,count,0.09,,1.12,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,9.0,8.035714285714285,100*b/1 (per unit count),|b/t|,0.0873895527330593,0.07802638636880294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.12,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,No_parking,parking,A_structural,level,count,0.16,,2.23,,*,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,16.0,7.174887892376682,100*b/1 (per unit count),|b/t|,0.17206211339621486,0.07715789838395284,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.23,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c1,11,1,17,Structure,roof_materials,A_structural,binary,binary,0.07,,0.92,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration not included",pct_premium,6.940817451536296,8.160388335629909,100*(exp(b - se^2/2) - 1),|b/t|,0.07187359623253212,0.07812347416579578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.92,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,Structure,roof_materials,A_structural,binary,binary,0.09,,1.09,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,pct_premium,9.0450807965053,9.034466562703571,100*(exp(b - se^2/2) - 1),|b/t|,0.08506593097263847,0.07804213850700777,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.09,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c3,11,3,17,Structure,roof_materials,A_structural,binary,binary,0.14,,1.9,,†,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration not included,pct_premium,14.71554065599694,8.475701675790097,100*(exp(b - se^2/2) - 1),|b/t|,0.14719839301007198,0.07747283842635369,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c4,11,4,17,Structure,roof_materials,A_structural,binary,binary,0.04,,0.6,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.75,t,Multivariate specification: useful surface + square; complete-case subsample; Duration not included,pct_premium,3.850042936142084,6.938738494615921,100*(exp(b - se^2/2) - 1),|b/t|,0.04694381579433043,0.07823969299055072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,Structure,roof_materials,A_structural,binary,binary,0.12,,1.51,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,12.394210682465223,8.960239880101,100*(exp(b - se^2/2) - 1),|b/t|,0.11745368957370614,0.07778390037993785,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.51,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,Structure,roof_materials,A_structural,binary,binary,0.04,,0.61,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,3.8575476745496218,6.824988683228776,100*(exp(b - se^2/2) - 1),|b/t|,0.047724445293116674,0.07823679556248635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.61,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c7,11,7,17,Structure,roof_materials,A_structural,binary,binary,0.24,,3.14,,**,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration not included,pct_premium,26.75412356429363,9.71655401519545,100*(exp(b - se^2/2) - 1),|b/t|,0.2388267101342657,0.07605946182619927,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.14,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,Structure,roof_materials,A_structural,binary,binary,0.2,,2.45,,*,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,21.733988371508307,9.970634760491182,100*(exp(b - se^2/2) - 1),|b/t|,0.18846014453071327,0.07692250797171969,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.45,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,Structure,roof_materials,A_structural,binary,binary,0.14,,1.83,,†,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,14.69126338515152,8.799908843716494,100*(exp(b - se^2/2) - 1),|b/t|,0.14188651541975236,0.07753361498347124,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.83,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,Height_regime_1,storeys,A_structural,dummy,binary,0.05,,0.43,,,,,high,1 if building height regime is Ground Floor +10 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,pct_premium,4.418804081737182,12.224082516000282,100*(exp(b - se^2/2) - 1),|b/t|,0.03366111292083537,0.0782816579554311,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.43,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,Height_regime_1,storeys,A_structural,dummy,binary,0.05,,0.39,,,,,high,1 if building height regime is Ground Floor +10 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,4.266686324688607,13.477834568923388,100*(exp(b - se^2/2) - 1),|b/t|,0.030532915299387793,0.07828952640868665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.39,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,Height_regime_1,storeys,A_structural,dummy,binary,0.09,,0.85,,,,,high,1 if building height regime is Ground Floor +10 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,8.805800852102251,11.585374768643403,100*(exp(b - se^2/2) - 1),|b/t|,0.06643007487109245,0.07815302926010877,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.85,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,Height_regime_1,storeys,A_structural,dummy,binary,0.02,,0.21,,,,,high,1 if building height regime is Ground Floor +10 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,1.558505226477136,9.716203238350056,100*(exp(b - se^2/2) - 1),|b/t|,0.016446244816782134,0.07831545150848634,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.21,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,Height_regime_2,storeys,A_structural,dummy,binary,0.02,,0.11,,,,,high,1 if building height regime is Ground Floor +11 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,pct_premium,0.34771055350184543,18.54911527321374,100*(exp(b - se^2/2) - 1),|b/t|,0.00861554517636434,0.07832313796694854,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.11,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,Height_regime_2,storeys,A_structural,dummy,binary,-0.02,,-0.14,,,,,high,1 if building height regime is Ground Floor +11 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,-2.9752496352559166,14.002838190096503,100*(exp(b - se^2/2) - 1),|b/t|,-0.010964987075026307,0.0783213362501879,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.14,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,Height_regime_2,storeys,A_structural,dummy,binary,0.05,,0.35,,,,,high,1 if building height regime is Ground Floor +11 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,4.059838550336048,15.01815851965749,100*(exp(b - se^2/2) - 1),|b/t|,0.027403820235783725,0.07829662924509635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.35,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,Height_regime_2,storeys,A_structural,dummy,binary,-0.04,,-0.24,,,,,high,1 if building height regime is Ground Floor +11 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,-5.2462617415583,16.013157319205387,100*(exp(b - se^2/2) - 1),|b/t|,-0.018794930270996775,0.07831220946248657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.24,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,Height_regime_2,storeys,A_structural,dummy,binary,0.01,,0.05,,,,,high,1 if building height regime is Ground Floor +11 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,-0.9950166250831893,20.201003341683357,100*(exp(b - se^2/2) - 1),|b/t|,0.00391627221729254,0.0783254443458508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.05,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,Height_regime_3,storeys,A_structural,dummy,binary,0.27,,1.86,,†,,,high,1 if building height regime is Ground Floor +2 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,pct_premium,29.623524789608503,19.015612994514882,100*(exp(b - se^2/2) - 1),|b/t|,0.14416456333874586,0.0775078297520139,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.86,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,Height_regime_3,storeys,A_structural,dummy,binary,0.09,,0.65,,,,,high,1 if building height regime is Ground Floor +2 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,8.373585939900142,15.150105466687526,100*(exp(b - se^2/2) - 1),|b/t|,0.05084607475894782,0.07822473039838125,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.65,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,Height_regime_3,storeys,A_structural,dummy,binary,0.22,,1.67,,†,,,high,1 if building height regime is Ground Floor +2 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,23.531097960946656,16.415382079594238,100*(exp(b - se^2/2) - 1),|b/t|,0.129699632680199,0.077664450706706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.67,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,Height_regime_3,storeys,A_structural,dummy,binary,-0.05,,-0.34,,,,,high,1 if building height regime is Ground Floor +2 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,-5.900094983755255,13.988668007363442,100*(exp(b - se^2/2) - 1),|b/t|,-0.02662141698558542,0.0782982852517218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.34,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,Height_regime_3,storeys,A_structural,dummy,binary,0.08,,0.54,,,,,high,1 if building height regime is Ground Floor +2 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,7.146413446146438,16.048697298888275,100*(exp(b - se^2/2) - 1),|b/t|,0.042258282063579004,0.07825607789551667,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.54,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,Height_regime_4,storeys,A_structural,dummy,binary,0.03,,0.2,,,,,high,1 if building height regime is Ground Floor +3 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,pct_premium,1.8926885052026332,15.456818009302754,100*(exp(b - se^2/2) - 1),|b/t|,0.015663287241915964,0.07831643620957981,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,Height_regime_4,storeys,A_structural,dummy,binary,-0.01,,-0.07,,,,,high,1 if building height regime is Ground Floor +3 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,-2.000134682790544,14.143569053559542,100*(exp(b - se^2/2) - 1),|b/t|,-0.005482740741241676,0.07832486773202393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.07,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,Height_regime_4,storeys,A_structural,dummy,binary,0.04,,0.36,,,,,high,1 if building height regime is Ground Floor +3 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,3.440580508803559,11.564564157693203,100*(exp(b - se^2/2) - 1),|b/t|,0.028186173125265654,0.07829492534796015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.36,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,Height_regime_4,storeys,A_structural,dummy,binary,-0.09,,-0.61,,,,,high,1 if building height regime is Ground Floor +3 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,-9.59622593201913,13.484230602362384,100*(exp(b - se^2/2) - 1),|b/t|,-0.047724445293116674,0.07823679556248635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.61,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,Height_regime_4,storeys,A_structural,dummy,binary,-0.04,,-0.34,,,,,high,1 if building height regime is Ground Floor +3 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,-4.583666855712954,11.30340516649792,100*(exp(b - se^2/2) - 1),|b/t|,-0.02662141698558542,0.0782982852517218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.34,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,Height_regime_5,storeys,A_structural,dummy,binary,0.09,,0.69,,,,,high,1 if building height regime is Ground Floor +4 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,pct_premium,8.490603954297903,14.27183848311144,100*(exp(b - se^2/2) - 1),|b/t|,0.053966214667216864,0.07821190531480704,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.69,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,Height_regime_5,storeys,A_structural,dummy,binary,0.09,,0.74,,,,,high,1 if building height regime is Ground Floor +4 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,8.611172155118464,13.307525072090396,100*(exp(b - se^2/2) - 1),|b/t|,0.05786415721199271,0.0781948070432334,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.74,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,Height_regime_5,storeys,A_structural,dummy,binary,0.09,,0.81,,,,,high,1 if building height regime is Ground Floor +4 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,8.74409248126231,12.157492041169004,100*(exp(b - se^2/2) - 1),|b/t|,0.06331679451827393,0.07816888212132585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.81,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,Height_regime_5,storeys,A_structural,dummy,binary,0.04,,0.33,,,,,high,1 if building height regime is Ground Floor +4 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,3.3192797170577437,12.61588817202895,100*(exp(b - se^2/2) - 1),|b/t|,0.025838964808374536,0.07829989335871071,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.33,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,Height_regime_5,storeys,A_structural,dummy,binary,0.03,,0.25,,,,,high,1 if building height regime is Ground Floor +4 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,2.306190670327446,12.365454407442204,100*(exp(b - se^2/2) - 1),|b/t|,0.01957775820486337,0.0783110328194535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.25,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,Height_regime_6,storeys,A_structural,dummy,binary,0.12,,0.75,,,,,high,1 if building height regime is Ground Floor +5 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,pct_premium,11.315686359039056,18.039949625270012,100*(exp(b - se^2/2) - 1),|b/t|,0.05864343398897361,0.07819124531863149,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.75,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,Height_regime_6,storeys,A_structural,dummy,binary,0.03,,0.18,,,,,high,1 if building height regime is Ground Floor +5 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,1.6241594865993747,17.174242232558615,100*(exp(b - se^2/2) - 1),|b/t|,0.01409728708933399,0.07831826160741105,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.18,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,Height_regime_6,storeys,A_structural,dummy,binary,0.08,,0.62,,,,,high,1 if building height regime is Ground Floor +5 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,7.430650114507498,13.97789764741882,100*(exp(b - se^2/2) - 1),|b/t|,0.04850498735522779,0.07823385057294804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.62,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,Height_regime_6,storeys,A_structural,dummy,binary,0.02,,0.17,,,,,high,1 if building height regime is Ground Floor +5 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,1.3165496699512946,12.002368706197126,100*(exp(b - se^2/2) - 1),|b/t|,0.013314247389992906,0.0783191022940759,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.17,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,Height_regime_7,storeys,A_structural,dummy,binary,0.24,,1.44,,,,,high,1 if building height regime is Ground Floor +6 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,pct_premium,25.37149592016259,21.18748583869008,100*(exp(b - se^2/2) - 1),|b/t|,0.11207885376546127,0.07783253733712589,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.44,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,Height_regime_7,storeys,A_structural,dummy,binary,-0.09,,-0.56,,,,,high,1 if building height regime is Ground Floor +6 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,-9.779592818942673,14.688179763287595,100*(exp(b - se^2/2) - 1),|b/t|,-0.04382045179337803,0.07825080677388933,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.56,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,Height_regime_7,storeys,A_structural,dummy,binary,0.11,,0.74,,,,,high,1 if building height regime is Ground Floor +6 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,10.401307339431408,16.593322668983223,100*(exp(b - se^2/2) - 1),|b/t|,0.05786415721199271,0.0781948070432334,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.74,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,Height_regime_7,storeys,A_structural,dummy,binary,-0.1,,-0.58,,,,,high,1 if building height regime is Ground Floor +6 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,-10.851196059331036,15.600645138551027,100*(exp(b - se^2/2) - 1),|b/t|,-0.045382300157365094,0.07824534509890534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.58,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,Height_regime_7,storeys,A_structural,dummy,binary,0.03,,0.16,,,,,high,1 if building height regime is Ground Floor +6 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,1.249934693917143,19.321022511628442,100*(exp(b - se^2/2) - 1),|b/t|,0.0125311831946079,0.07831989496629937,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.16,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,Height_regime_9,storeys,A_structural,dummy,binary,0.19,,1.59,,,,,high,1 if building height regime is Ground Floor +8 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,pct_premium,20.064660693071357,14.45015242483508,100*(exp(b - se^2/2) - 1),|b/t|,0.12358371871647124,0.07772560925564229,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.59,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,Height_regime_9,storeys,A_structural,dummy,binary,0.18,,1.5,,,,,high,1 if building height regime is Ground Floor +8 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,18.862835563875247,14.36660835746172,100*(exp(b - se^2/2) - 1),|b/t|,0.1166864762376621,0.07779098415844139,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,Height_regime_9,storeys,A_structural,dummy,binary,0.19,,1.76,,†,,,high,1 if building height regime is Ground Floor +8 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,20.22236792872667,13.054399065618055,100*(exp(b - se^2/2) - 1),|b/t|,0.1365623523826234,0.07759224567194511,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.76,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,Height_regime_9,storeys,A_structural,dummy,binary,0.13,,1.06,,,,,high,1 if building height regime is Ground Floor +8 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,13.029598277098353,13.966763191717058,100*(exp(b - se^2/2) - 1),|b/t|,0.08274092047284654,0.07805747214419485,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.06,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,Height_regime_9,storeys,A_structural,dummy,binary,0.13,,1.13,,,,,high,1 if building height regime is Ground Floor +8 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,13.131696575274576,13.10156547187618,100*(exp(b - se^2/2) - 1),|b/t|,0.08816377835032914,0.07802104278790191,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.13,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c2,11,2,17,Height_regime_10,storeys,A_structural,dummy,binary,0.25,,1.82,,†,,,high,1 if building height regime is Ground Floor +9 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration not included,pct_premium,27.196856673769588,17.637711767688753,100*(exp(b - se^2/2) - 1),|b/t|,0.14112666300859447,0.07754212253219477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.82,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,Height_regime_10,storeys,A_structural,dummy,binary,0.22,,1.6,,,,,high,1 if building height regime is Ground Floor +9 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,23.43529121588619,17.133555045576482,100*(exp(b - se^2/2) - 1),|b/t|,0.12434899333339904,0.0777181208333744,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,Height_regime_10,storeys,A_structural,dummy,binary,0.27,,2.16,,*,,,high,1 if building height regime is Ground Floor +9 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,29.97702265007551,16.374555634165592,100*(exp(b - se^2/2) - 1),|b/t|,0.16681372002476,0.07722857408553703,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.16,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,Height_regime_10,storeys,A_structural,dummy,binary,0.16,,1.12,,,,,high,1 if building height regime is Ground Floor +9 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,pct_premium,16.159715789230788,16.764441014168717,100*(exp(b - se^2/2) - 1),|b/t|,0.0873895527330593,0.07802638636880294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.12,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,Height_regime_10,storeys,A_structural,dummy,binary,0.19,,1.45,,,,,high,1 if building height regime is Ground Floor +9 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,pct_premium,19.891260342171368,15.845339555508813,100*(exp(b - se^2/2) - 1),|b/t|,0.11284730128956229,0.07782572502728434,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.45,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c3,11,3,17,S_useful,living_area,A_structural,level,m2,0.01,,9.63,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration not included,semi_elasticity,1.0,0.10384215991692627,100*b/1 (X per m2->m2),|b/t|,0.6021845224140387,0.06253214147601648,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.63,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c4,11,4,17,S_useful,living_area,A_structural,level,m2,0.03,,9.82,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.75,t,Multivariate specification: useful surface + square; complete-case subsample; Duration not included,semi_elasticity,3.0,0.30549898167006106,100*b/1 (X per m2->m2),|b/t|,0.6096763956663303,0.062085172674779046,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.82,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c5,11,5,17,S_useful,living_area,A_structural,level,m2,0.01,,10.24,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,1.0,0.09765625,100*b/1 (X per m2->m2),|b/t|,0.6256738009765551,0.061100957126616694,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.24,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c6,11,6,17,S_useful,living_area,A_structural,level,m2,0.03,,9.54,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,3.0,0.3144654088050315,100*b/1 (X per m2->m2),|b/t|,0.5985791699146055,0.06274414778979095,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.54,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c7,11,7,17,S_constructed,living_area,A_structural,level,m2,0.01,,8.86,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration not included,semi_elasticity,1.0,0.11286681715575622,100*b/1 (X per m2->m2),|b/t|,0.5701321267090858,0.06434899849989682,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.86,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c8,11,8,17,S_constructed,living_area,A_structural,level,m2,0.03,,9.93,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,183.0,0.72,t,Multivariate specification: constructed surface + square (Structure omitted); complete-case subsample; Duration not included,semi_elasticity,3.0,0.3021148036253776,100*b/1 (X per m2->m2),|b/t|,0.6025324595345515,0.06067799189673228,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.93,173.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c9,11,9,17,S_constructed,living_area,A_structural,level,m2,0.01,,9.37,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,1.0,0.10672358591248667,100*b/1 (X per m2->m2),|b/t|,0.5916685824113874,0.06314499278670092,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.37,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T11-c10,11,10,17,S_constructed,living_area,A_structural,level,m2,0.02,,9.28,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration not included,semi_elasticity,2.0,0.2155172413793104,100*b/1 (X per m2->m2),|b/t|,0.5879563338913402,0.06335736356587718,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.28,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c1,12,1,18,No_rooms,bedrooms,A_structural,level,count,0.23,,9.05,,***,,,high,"Number of rooms (all rooms, not only bedrooms)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration control included",semi_elasticity,23.0,2.5414364640883975,100*b/1 (per unit count),|b/t|,0.5782983723495626,0.06390037263531077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.05,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,No_rooms,bedrooms,A_structural,level,count,0.25,,9.7,,***,,,high,"Number of rooms (all rooms, not only bedrooms)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,semi_elasticity,25.0,2.577319587628866,100*b/1 (per unit count),|b/t|,0.60496345752378,0.062367366755028866,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.7,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c1,12,1,18,Comfort,condition,A_structural,binary,binary,0.34,,5.81,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration control included",pct_premium,40.25439809465801,8.221724282127745,100*(exp(b - se^2/2) - 1),|b/t|,0.4142018455012256,0.0712911954391094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.81,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,Comfort,condition,A_structural,binary,binary,0.31,,5.23,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,pct_premium,36.103212953285535,8.081487292179256,100*(exp(b - se^2/2) - 1),|b/t|,0.37907220375186784,0.07248034488563437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.23,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c3,12,3,18,Comfort,condition,A_structural,binary,binary,0.26,,4.32,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration control included,pct_premium,29.458330573942206,7.8055977438217745,100*(exp(b - se^2/2) - 1),|b/t|,0.32051711359830654,0.07419377629590429,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.32,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c4,12,4,18,Comfort,condition,A_structural,binary,binary,0.14,,2.47,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: useful surface + square; complete-case subsample; Duration control included,pct_premium,14.842757382416515,6.519770519838536,100*(exp(b - se^2/2) - 1),|b/t|,0.18994330645012425,0.0769001240688762,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.47,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,Comfort,condition,A_structural,binary,binary,0.2,,3.3,,**,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,21.91616528112361,7.402440958546484,100*(exp(b - se^2/2) - 1),|b/t|,0.2502514693627675,0.07583377859477804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,Comfort,condition,A_structural,binary,binary,0.12,,2.05,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,12.5566803471304,6.599981570220737,100*(exp(b - se^2/2) - 1),|b/t|,0.15853767239265218,0.07733544994763521,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.05,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c7,12,7,18,Comfort,condition,A_structural,binary,binary,0.26,,4.26,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration control included,pct_premium,29.451679567130217,7.915535740213632,100*(exp(b - se^2/2) - 1),|b/t|,0.3165142787122256,0.07429912645826893,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.26,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c8,12,8,18,Comfort,condition,A_structural,binary,binary,0.14,,2.5,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,183.0,0.73,t,Multivariate specification: constructed surface + square (Structure omitted); complete-case subsample; Duration control included,pct_premium,14.84715828472185,6.4415332736004745,100*(exp(b - se^2/2) - 1),|b/t|,0.18672842174331777,0.0746913686973271,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5,173.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,Comfort,condition,A_structural,binary,binary,0.21,,3.25,,**,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,23.110535205154115,7.971458233566648,100*(exp(b - se^2/2) - 1),|b/t|,0.24669219681861024,0.07590529132880315,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.25,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,Comfort,condition,A_structural,binary,binary,0.12,,2.03,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,12.552861900135536,6.665006019188429,100*(exp(b - se^2/2) - 1),|b/t|,0.1570292856479949,0.07735432790541621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.03,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c1,12,1,18,Floor,floor_level,A_structural,level,count,-0.01,,-2.01,,*,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration control included",semi_elasticity,-1.0,0.49751243781094534,100*b/1 (per unit count),|b/t|,-0.15551979917162387,0.07737303441374323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.01,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,Floor,floor_level,A_structural,level,count,-0.01,,-1.47,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,semi_elasticity,-1.0,0.6802721088435375,100*b/1 (per unit count),|b/t|,-0.11438358771689541,0.07781196443326219,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.47,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c3,12,3,18,Floor,floor_level,A_structural,level,count,-0.01,,-1.44,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration control included,semi_elasticity,-1.0,0.6944444444444445,100*b/1 (per unit count),|b/t|,-0.11207885376546127,0.07783253733712589,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.44,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c4,12,4,18,Floor,floor_level,A_structural,level,count,-0.01,,-2.64,,**,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: useful surface + square; complete-case subsample; Duration control included,semi_elasticity,-1.0,0.3787878787878788,100*b/1 (per unit count),|b/t|,-0.2024968634671151,0.07670335737390722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.64,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,Floor,floor_level,A_structural,level,count,-0.01,,-1.36,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,-1.0,0.7352941176470588,100*b/1 (per unit count),|b/t|,-0.10592414314269169,0.07788539936962624,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.36,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,Floor,floor_level,A_structural,level,count,-0.01,,-2.41,,*,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,-1.0,0.4149377593360996,100*b/1 (per unit count),|b/t|,-0.1854899574949399,0.07696678734229871,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.41,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c7,12,7,18,Floor,floor_level,A_structural,level,count,-0.01,,-1.2,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration control included,semi_elasticity,-1.0,0.8333333333333334,100*b/1 (per unit count),|b/t|,-0.09357880867084666,0.07798234055903888,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c8,12,8,18,Floor,floor_level,A_structural,level,count,-0.01,,-1.98,,*,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,183.0,0.73,t,Multivariate specification: constructed surface + square (Structure omitted); complete-case subsample; Duration control included,semi_elasticity,-1.0,0.5050505050505051,100*b/1 (per unit count),|b/t|,-0.14885938964601347,0.07518150992222902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.98,173.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,Floor,floor_level,A_structural,level,count,-0.01,,-1.35,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,-1.0,0.7407407407407407,100*b/1 (per unit count),|b/t|,-0.10515393275111268,0.07789180203786124,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.35,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,Floor,floor_level,A_structural,level,count,-0.01,,-2.18,,*,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,-1.0,0.45871559633027514,100*b/1 (per unit count),|b/t|,-0.1683147291176314,0.07720859133836303,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.18,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c1,12,1,18,No_bathrooms,bathrooms,A_structural,level,count,0.08,,1.65,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration control included",semi_elasticity,8.0,4.8484848484848495,100*b/1 (per unit count),|b/t|,0.12817201327964664,0.07768000804827069,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.65,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,No_bathrooms,bathrooms,A_structural,level,count,0.03,,0.55,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,semi_elasticity,3.0,5.454545454545453,100*b/1 (per unit count),|b/t|,0.04303940638866546,0.07825346616120993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.55,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c3,12,3,18,No_bathrooms,bathrooms,A_structural,level,count,0.07,,1.48,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration control included,semi_elasticity,7.000000000000001,4.72972972972973,100*b/1 (per unit count),|b/t|,0.11515142400924942,0.07780501622246584,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.48,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c4,12,4,18,No_bathrooms,bathrooms,A_structural,level,count,0.05,,1.14,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: useful surface + square; complete-case subsample; Duration control included,semi_elasticity,5.0,4.385964912280702,100*b/1 (per unit count),|b/t|,0.08893784421580979,0.07801565282088578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.14,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,No_bathrooms,bathrooms,A_structural,level,count,0.04,,0.9,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,4.0,4.444444444444445,100*b/1 (per unit count),|b/t|,0.07031893818579951,0.07813215353977723,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,No_bathrooms,bathrooms,A_structural,level,count,0.03,,0.64,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,3.0,4.6875,100*b/1 (per unit count),|b/t|,0.050065803503583264,0.07822781797434884,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.64,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c7,12,7,18,No_bathrooms,bathrooms,A_structural,level,count,0.09,,1.79,,†,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration control included,semi_elasticity,9.0,5.027932960893854,100*b/1 (per unit count),|b/t|,0.13884561372651844,0.07756738197012203,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.79,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c8,12,8,18,No_bathrooms,bathrooms,A_structural,level,count,0.07,,1.59,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,183.0,0.73,t,Multivariate specification: constructed surface + square (Structure omitted); complete-case subsample; Duration control included,semi_elasticity,7.000000000000001,4.402515723270441,100*b/1 (per unit count),|b/t|,0.12001175822494643,0.07547909322323675,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.59,173.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,No_bathrooms,bathrooms,A_structural,level,count,0.06,,1.15,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,6.0,5.217391304347826,100*b/1 (per unit count),|b/t|,0.08971174897143021,0.07801021649689584,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.15,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,No_bathrooms,bathrooms,A_structural,level,count,0.05,,1.04,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,5.0,4.807692307692308,100*b/1 (per unit count),|b/t|,0.08119016016629894,0.07806746169836437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.04,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c1,12,1,18,No_balconies,terrace_balcony,C_exterior,level,count,-0.04,,-0.82,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration control included",semi_elasticity,-4.0,4.878048780487805,100*b/1 (per unit count),|b/t|,-0.06409529150234007,0.0781649896370001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.82,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,No_balconies,terrace_balcony,C_exterior,level,count,-0.04,,-0.97,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,semi_elasticity,-4.0,4.123711340206185,100*b/1 (per unit count),|b/t|,-0.07575792603081245,0.07810095467094068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.97,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c3,12,3,18,No_balconies,terrace_balcony,C_exterior,level,count,-0.05,,-1.12,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration control included,semi_elasticity,-5.0,4.464285714285714,100*b/1 (per unit count),|b/t|,-0.0873895527330593,0.07802638636880294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.12,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c4,12,4,18,No_balconies,terrace_balcony,C_exterior,level,count,-0.03,,-0.73,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: useful surface + square; complete-case subsample; Duration control included,semi_elasticity,-3.0,4.10958904109589,100*b/1 (per unit count),|b/t|,-0.057084774648618365,0.07819832143646352,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.73,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,No_balconies,terrace_balcony,C_exterior,level,count,-0.06,,-1.39,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,-6.0,4.316546762589928,100*b/1 (per unit count),|b/t|,-0.1082336254184039,0.07786591756719705,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.39,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,No_balconies,terrace_balcony,C_exterior,level,count,-0.04,,-0.92,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,-4.0,4.3478260869565215,100*b/1 (per unit count),|b/t|,-0.07187359623253212,0.07812347416579578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.92,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c7,12,7,18,No_balconies,terrace_balcony,C_exterior,level,count,-0.08,,-1.78,,†,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration control included,semi_elasticity,-8.0,4.49438202247191,100*b/1 (per unit count),|b/t|,-0.13808477074149605,0.07757571389971687,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.78,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c8,12,8,18,No_balconies,terrace_balcony,C_exterior,level,count,-0.06,,-1.38,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,183.0,0.73,t,Multivariate specification: constructed surface + square (Structure omitted); complete-case subsample; Duration control included,semi_elasticity,-6.0,4.3478260869565215,100*b/1 (per unit count),|b/t|,-0.10434669999987986,0.07561355072455063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.38,173.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,No_balconies,terrace_balcony,C_exterior,level,count,-0.09,,-1.92,,†,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,-9.0,4.6875,100*b/1 (per unit count),|b/t|,-0.14871375690053495,0.07745508171902862,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.92,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,No_balconies,terrace_balcony,C_exterior,level,count,-0.06,,-1.4,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,-6.0,4.285714285714286,100*b/1 (per unit count),|b/t|,-0.10900306547625242,0.07785933248303746,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c1,12,1,18,No_parking,parking,A_structural,level,count,0.21,,3.11,,**,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration control included",semi_elasticity,21.0,6.752411575562702,100*b/1 (per unit count),|b/t|,0.2366733203280875,0.07610074608620178,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.11,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,No_parking,parking,A_structural,level,count,0.23,,3.19,,**,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,semi_elasticity,23.0,7.210031347962382,100*b/1 (per unit count),|b/t|,0.24240786447110518,0.07598992616649065,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.19,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c3,12,3,18,No_parking,parking,A_structural,level,count,0.09,,1.35,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration control included,semi_elasticity,9.0,6.666666666666667,100*b/1 (per unit count),|b/t|,0.10515393275111268,0.07789180203786124,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.35,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c4,12,4,18,No_parking,parking,A_structural,level,count,0.16,,2.63,,**,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: useful surface + square; complete-case subsample; Duration control included,semi_elasticity,16.0,6.083650190114069,100*b/1 (per unit count),|b/t|,0.20176111088380483,0.0767152512866178,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.63,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,No_parking,parking,A_structural,level,count,0.13,,1.69,,†,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,13.0,7.6923076923076925,100*b/1 (per unit count),|b/t|,0.1312263290940617,0.0776487154402732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.69,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,No_parking,parking,A_structural,level,count,0.2,,2.92,,**,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,20.0,6.849315068493151,100*b/1 (per unit count),|b/t|,0.2229550763794247,0.07635447821213175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.92,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c7,12,7,18,No_parking,parking,A_structural,level,count,0.06,,0.81,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration control included,semi_elasticity,6.0,7.4074074074074066,100*b/1 (per unit count),|b/t|,0.06331679451827393,0.07816888212132585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.81,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c8,12,8,18,No_parking,parking,A_structural,level,count,0.16,,2.52,,*,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,183.0,0.73,t,Multivariate specification: constructed surface + square (Structure omitted); complete-case subsample; Duration control included,semi_elasticity,16.0,6.349206349206349,100*b/1 (per unit count),|b/t|,0.1881695585203947,0.07467045973031534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.52,173.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,No_parking,parking,A_structural,level,count,0.09,,1.1,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,9.0,8.18181818181818,100*b/1 (per unit count),|b/t|,0.08584062768258548,0.07803693425689588,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,No_parking,parking,A_structural,level,count,0.17,,2.3,,*,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,17.0,7.391304347826089,100*b/1 (per unit count),|b/t|,0.17729589519341188,0.07708517182322257,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c1,12,1,18,Structure,roof_materials,A_structural,binary,binary,0.06,,0.72,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.68,t,"Multivariate specification: rooms, no surface, no height regimes; complete-case subsample; Duration control included",pct_premium,5.81560076144243,8.848637887877995,100*(exp(b - se^2/2) - 1),|b/t|,0.056305287704943245,0.07820178847908785,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.72,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,Structure,roof_materials,A_structural,binary,binary,0.08,,0.91,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,pct_premium,7.910903427587801,9.523402792746888,100*(exp(b - se^2/2) - 1),|b/t|,0.07109633197544415,0.07812783733565291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.91,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c3,12,3,18,Structure,roof_materials,A_structural,binary,binary,0.14,,1.85,,†,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration control included,pct_premium,14.698481142136322,8.704774694054693,100*(exp(b - se^2/2) - 1),|b/t|,0.14340546681487304,0.07751646854858002,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.85,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c4,12,4,18,Structure,roof_materials,A_structural,binary,binary,0.02,,0.32,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: useful surface + square; complete-case subsample; Duration control included,pct_premium,1.821070389791668,6.3762583751672235,100*(exp(b - se^2/2) - 1),|b/t|,0.02505646513830408,0.07830145355720024,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.32,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,Structure,roof_materials,A_structural,binary,binary,0.12,,1.48,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,12.379677407986666,9.141866364157101,100*(exp(b - se^2/2) - 1),|b/t|,0.11515142400924942,0.07780501622246584,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.48,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,Structure,roof_materials,A_structural,binary,binary,0.03,,0.34,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,2.6451046313887394,9.092245887825149,100*(exp(b - se^2/2) - 1),|b/t|,0.02662141698558542,0.0782982852517218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.34,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c7,12,7,18,Structure,roof_materials,A_structural,binary,binary,0.25,,3.11,,**,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration control included,pct_premium,27.98834990113248,10.321747722570269,100*(exp(b - se^2/2) - 1),|b/t|,0.2366733203280875,0.07610074608620178,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.11,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,Structure,roof_materials,A_structural,binary,binary,0.21,,2.44,,*,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,22.911740942384064,10.617721007824429,100*(exp(b - se^2/2) - 1),|b/t|,0.18771807904379892,0.0769336389523766,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.44,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,Structure,roof_materials,A_structural,binary,binary,0.12,,1.57,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,12.420822627343853,8.617810330543,100*(exp(b - se^2/2) - 1),|b/t|,0.12205250908544199,0.07774045164677833,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.57,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,Height_regime_1,storeys,A_structural,dummy,binary,0.06,,0.51,,,,,high,1 if building height regime is Ground Floor +10 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,pct_premium,5.451356500483562,12.492194665239523,100*(exp(b - se^2/2) - 1),|b/t|,0.039914449789453355,0.07826362703814382,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.51,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,Height_regime_1,storeys,A_structural,dummy,binary,0.05,,0.38,,,,,high,1 if building height regime is Ground Floor +10 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,4.2210033111480305,13.832514426000317,100*(exp(b - se^2/2) - 1),|b/t|,0.029750722089589628,0.07829137391997269,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.38,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,Height_regime_1,storeys,A_structural,dummy,binary,0.11,,1.0,,,,,high,1 if building height regime is Ground Floor +10 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,10.954497627981418,12.279058775047584,100*(exp(b - se^2/2) - 1),|b/t|,0.07808688094430304,0.07808688094430304,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,Height_regime_1,storeys,A_structural,dummy,binary,-0.01,,-0.06,,,,,high,1 if building height regime is Ground Floor +10 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,-2.3605808025439434,16.500830562486136,100*(exp(b - se^2/2) - 1),|b/t|,-0.004699510803775961,0.0783251800629327,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.06,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,Height_regime_1,storeys,A_structural,dummy,binary,0.04,,0.34,,,,,high,1 if building height regime is Ground Floor +10 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,3.3632797401716763,12.244832637557508,100*(exp(b - se^2/2) - 1),|b/t|,0.02662141698558542,0.0782982852517218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.34,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,Height_regime_2,storeys,A_structural,dummy,binary,0.03,,0.18,,,,,high,1 if building height regime is Ground Floor +11 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,pct_premium,1.6241594865993747,17.174242232558615,100*(exp(b - se^2/2) - 1),|b/t|,0.01409728708933399,0.07831826160741105,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.18,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,Height_regime_2,storeys,A_structural,dummy,binary,-0.02,,-0.15,,,,,high,1 if building height regime is Ground Floor +11 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,-2.8475594374056667,13.06931564409007,100*(exp(b - se^2/2) - 1),|b/t|,-0.011748095942956003,0.0783206396197067,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.15,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,Height_regime_2,storeys,A_structural,dummy,binary,0.06,,0.47,,,,,high,1 if building height regime is Ground Floor +11 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,5.321934523235283,13.555360168664164,100*(exp(b - se^2/2) - 1),|b/t|,0.03678832155190899,0.07827302457852976,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.47,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,Height_regime_2,storeys,A_structural,dummy,binary,-0.04,,-0.26,,,,,high,1 if building height regime is Ground Floor +11 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,-5.0513834870797965,14.78137598695882,100*(exp(b - se^2/2) - 1),|b/t|,-0.020360550133690272,0.07830980820650105,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.26,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,Height_regime_2,storeys,A_structural,dummy,binary,0.02,,0.15,,,,,high,1 if building height regime is Ground Floor +11 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,1.1173068766337835,13.602684533690077,100*(exp(b - se^2/2) - 1),|b/t|,0.011748095942956003,0.0783206396197067,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.15,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,Height_regime_3,storeys,A_structural,dummy,binary,0.27,,1.89,,†,,,high,1 if building height regime is Ground Floor +2 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,pct_premium,29.66654340625343,18.71377786761782,100*(exp(b - se^2/2) - 1),|b/t|,0.14644032150069775,0.07748165158767077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.89,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,Height_regime_3,storeys,A_structural,dummy,binary,0.09,,0.65,,,,,high,1 if building height regime is Ground Floor +2 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,8.373585939900142,15.150105466687526,100*(exp(b - se^2/2) - 1),|b/t|,0.05084607475894782,0.07822473039838125,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.65,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,Height_regime_3,storeys,A_structural,dummy,binary,0.22,,1.72,,†,,,high,1 if building height regime is Ground Floor +2 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,23.59252781663521,15.93819074007115,100*(exp(b - se^2/2) - 1),|b/t|,0.1335146210126104,0.07762477965849443,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.72,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,Height_regime_3,storeys,A_structural,dummy,binary,-0.05,,-0.34,,,,,high,1 if building height regime is Ground Floor +2 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,-5.900094983755255,13.988668007363442,100*(exp(b - se^2/2) - 1),|b/t|,-0.02662141698558542,0.0782982852517218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.34,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,Height_regime_3,storeys,A_structural,dummy,binary,0.08,,0.56,,,,,high,1 if building height regime is Ground Floor +2 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,7.228932436664737,15.475529538213694,100*(exp(b - se^2/2) - 1),|b/t|,0.04382045179337803,0.07825080677388933,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.56,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,Height_regime_4,storeys,A_structural,dummy,binary,0.04,,0.28,,,,,high,1 if building height regime is Ground Floor +3 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,pct_premium,3.0244258567254656,14.868725345605545,100*(exp(b - se^2/2) - 1),|b/t|,0.021926020227473576,0.0783072150981199,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.28,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,Height_regime_4,storeys,A_structural,dummy,binary,-0.01,,-0.08,,,,,high,1 if building height regime is Ground Floor +3 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,-1.7654795182503569,12.3756229218646,100*(exp(b - se^2/2) - 1),|b/t|,-0.006265960588387915,0.07832450735484893,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.08,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,Height_regime_4,storeys,A_structural,dummy,binary,0.06,,0.49,,,,,high,1 if building height regime is Ground Floor +3 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,5.3905854157488164,13.002080161779913,100*(exp(b - se^2/2) - 1),|b/t|,0.03835152642653928,0.07826842127865159,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.49,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,Height_regime_4,storeys,A_structural,dummy,binary,-0.09,,-0.62,,,,,high,1 if building height regime is Ground Floor +3 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,-9.564735452408723,13.2667430120017,100*(exp(b - se^2/2) - 1),|b/t|,-0.04850498735522779,0.07823385057294804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.62,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,Height_regime_4,storeys,A_structural,dummy,binary,-0.03,,-0.23,,,,,high,1 if building height regime is Ground Floor +3 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,-3.777466161145937,12.657985220197933,100*(exp(b - se^2/2) - 1),|b/t|,-0.018012067769695272,0.07831333812910987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.23,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,Height_regime_5,storeys,A_structural,dummy,binary,0.1,,0.78,,,,,high,1 if building height regime is Ground Floor +4 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,pct_premium,9.612553648050405,14.168857924046767,100*(exp(b - se^2/2) - 1),|b/t|,0.060980615555143815,0.07818027635274846,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.78,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,Height_regime_5,storeys,A_structural,dummy,binary,0.09,,0.72,,,,,high,1 if building height regime is Ground Floor +4 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,8.565935187536255,13.67717854631513,100*(exp(b - se^2/2) - 1),|b/t|,0.056305287704943245,0.07820178847908785,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.72,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,Height_regime_5,storeys,A_structural,dummy,binary,0.11,,0.95,,,,,high,1 if building height regime is Ground Floor +4 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,10.882001339798485,12.925325026365877,100*(exp(b - se^2/2) - 1),|b/t|,0.07420459794567237,0.07811010310070776,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.95,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,Height_regime_5,storeys,A_structural,dummy,binary,0.04,,0.3,,,,,high,1 if building height regime is Ground Floor +4 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,3.1600119754384925,13.877476989231843,100*(exp(b - se^2/2) - 1),|b/t|,0.023491329058363677,0.0783044301945456,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,Height_regime_5,storeys,A_structural,dummy,binary,0.04,,0.37,,,,,high,1 if building height regime is Ground Floor +4 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,3.474634406287591,11.252008369647442,100*(exp(b - se^2/2) - 1),|b/t|,0.028968474220789676,0.07829317356970182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.37,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,Height_regime_6,storeys,A_structural,dummy,binary,0.12,,0.78,,,,,high,1 if building height regime is Ground Floor +5 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,pct_premium,11.423233663544362,17.34610540891347,100*(exp(b - se^2/2) - 1),|b/t|,0.060980615555143815,0.07818027635274846,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.78,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,Height_regime_6,storeys,A_structural,dummy,binary,0.03,,0.18,,,,,high,1 if building height regime is Ground Floor +5 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,1.6241594865993747,17.174242232558615,100*(exp(b - se^2/2) - 1),|b/t|,0.01409728708933399,0.07831826160741105,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.18,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,Height_regime_6,storeys,A_structural,dummy,binary,0.09,,0.67,,,,,high,1 if building height regime is Ground Floor +5 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,8.434698221278492,14.69786351245805,100*(exp(b - se^2/2) - 1),|b/t|,0.05240633656110709,0.07821841277777176,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.67,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,Height_regime_6,storeys,A_structural,dummy,binary,0.03,,0.2,,,,,high,1 if building height regime is Ground Floor +5 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,1.8926885052026332,15.456818009302754,100*(exp(b - se^2/2) - 1),|b/t|,0.015663287241915964,0.07831643620957981,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,Height_regime_7,storeys,A_structural,dummy,binary,0.25,,1.52,,,,,high,1 if building height regime is Ground Floor +6 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,pct_premium,26.677487696860737,21.11883909025891,100*(exp(b - se^2/2) - 1),|b/t|,0.11822069266068613,0.0777767714872935,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.52,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,Height_regime_7,storeys,A_structural,dummy,binary,-0.09,,-0.56,,,,,high,1 if building height regime is Ground Floor +6 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,-9.779592818942673,14.688179763287595,100*(exp(b - se^2/2) - 1),|b/t|,-0.04382045179337803,0.07825080677388933,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.56,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,Height_regime_7,storeys,A_structural,dummy,binary,0.13,,0.87,,,,,high,1 if building height regime is Ground Floor +6 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,12.618525578572616,17.016975842781704,100*(exp(b - se^2/2) - 1),|b/t|,0.06798599350774875,0.07814482012384914,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.87,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,Height_regime_7,storeys,A_structural,dummy,binary,-0.1,,-0.59,,,,,high,1 if building height regime is Ground Floor +6 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,-10.80664891580938,15.336227424338299,100*(exp(b - se^2/2) - 1),|b/t|,-0.046163100276330755,0.07824254284123856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.59,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,Height_regime_7,storeys,A_structural,dummy,binary,0.04,,0.27,,,,,high,1 if building height regime is Ground Floor +6 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,2.945142482105978,15.419418876924269,100*(exp(b - se^2/2) - 1),|b/t|,0.021143304620203605,0.07830853563038372,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.27,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,Height_regime_9,storeys,A_structural,dummy,binary,0.2,,1.65,,,,,high,1 if building height regime is Ground Floor +8 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,pct_premium,21.246297931010915,14.804881917092969,100*(exp(b - se^2/2) - 1),|b/t|,0.12817201327964664,0.07768000804827069,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.65,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,Height_regime_9,storeys,A_structural,dummy,binary,0.18,,1.48,,,,,high,1 if building height regime is Ground Floor +8 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,18.83955149521004,14.560751713643635,100*(exp(b - se^2/2) - 1),|b/t|,0.11515142400924942,0.07780501622246584,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.48,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,Height_regime_9,storeys,A_structural,dummy,binary,0.2,,1.87,,†,,,high,1 if building height regime is Ground Floor +8 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,21.443706516507554,13.063131103317323,100*(exp(b - se^2/2) - 1),|b/t|,0.1449234054437153,0.07749914729610444,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.87,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,Height_regime_9,storeys,A_structural,dummy,binary,0.13,,1.03,,,,,high,1 if building height regime is Ground Floor +8 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,12.979371681417827,14.373562119631147,100*(exp(b - se^2/2) - 1),|b/t|,0.08041455812861766,0.0780723865326385,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.03,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,Height_regime_9,storeys,A_structural,dummy,binary,0.14,,1.22,,,,,high,1 if building height regime is Ground Floor +8 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,14.272498573339787,13.199863265574741,100*(exp(b - se^2/2) - 1),|b/t|,0.09512445741279114,0.07797086673179603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.22,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c2,12,2,18,Height_regime_10,storeys,A_structural,dummy,binary,0.26,,1.86,,†,,,high,1 if building height regime is Ground Floor +9 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.72,t,Multivariate specification: rooms + height-regime dummies (base GF+7); complete-case subsample; Duration control included,pct_premium,28.432088489895712,18.12913024371509,100*(exp(b - se^2/2) - 1),|b/t|,0.14416456333874586,0.0775078297520139,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.86,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,Height_regime_10,storeys,A_structural,dummy,binary,0.22,,1.59,,,,,high,1 if building height regime is Ground Floor +9 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,23.420568589887814,17.2413132534103,100*(exp(b - se^2/2) - 1),|b/t|,0.12358371871647124,0.07772560925564229,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.59,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,Height_regime_10,storeys,A_structural,dummy,binary,0.28,,2.25,,*,,,high,1 if building height regime is Ground Floor +9 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,31.292410396968705,16.465615442421438,100*(exp(b - se^2/2) - 1),|b/t|,0.17355898767151737,0.07713732785400773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.25,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,Height_regime_10,storeys,A_structural,dummy,binary,0.16,,1.1,,,,,high,1 if building height regime is Ground Floor +9 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,pct_premium,16.116230159783807,17.06924903260815,100*(exp(b - se^2/2) - 1),|b/t|,0.08584062768258548,0.07803693425689588,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,Height_regime_10,storeys,A_structural,dummy,binary,0.2,,1.52,,,,,high,1 if building height regime is Ground Floor +9 Floors,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,pct_premium,21.08753045838958,16.07108892316013,100*(exp(b - se^2/2) - 1),|b/t|,0.11822069266068613,0.0777767714872935,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.52,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c3,12,3,18,S_useful,living_area,A_structural,level,m2,0.01,,9.42,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.69,t,Multivariate specification: useful surface (linear); complete-case subsample; Duration control included,semi_elasticity,1.0,0.10615711252653928,100*b/1 (X per m2->m2),|b/t|,0.5937148261491466,0.06302705160818965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.42,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c4,12,4,18,S_useful,living_area,A_structural,level,m2,0.03,,9.89,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: useful surface + square; complete-case subsample; Duration control included,semi_elasticity,3.0,0.3033367037411526,100*b/1 (X per m2->m2),|b/t|,0.6123961103490635,0.06192073916572938,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.89,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c5,12,5,18,S_useful,living_area,A_structural,level,m2,0.01,,9.96,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.73,t,Multivariate specification: useful surface + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,1.0,0.1004016064257028,100*b/1 (X per m2->m2),|b/t|,0.6150942535183284,0.061756451156458655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.96,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c6,12,6,18,S_useful,living_area,A_structural,level,m2,0.03,,9.53,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.78,t,Multivariate specification: useful surface + square + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,3.0,0.3147953830010493,100*b/1 (X per m2->m2),|b/t|,0.5981763119611426,0.06276771374198768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.53,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c7,12,7,18,S_constructed,living_area,A_structural,level,m2,0.01,,8.65,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.67,t,Multivariate specification: constructed surface (linear); complete-case subsample; Duration control included,semi_elasticity,1.0,0.11560693641618498,100*b/1 (X per m2->m2),|b/t|,0.5609054210453405,0.06484455734628214,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.65,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c8,12,8,18,S_constructed,living_area,A_structural,level,m2,0.03,,10.13,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,183.0,0.73,t,Multivariate specification: constructed surface + square (Structure omitted); complete-case subsample; Duration control included,semi_elasticity,3.0,0.2961500493583415,100*b/1 (X per m2->m2),|b/t|,0.6101779697082571,0.06023474528215764,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.13,173.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c9,12,9,18,S_constructed,living_area,A_structural,level,m2,0.01,,9.09,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.71,t,Multivariate specification: constructed surface + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,1.0,0.11001100110011,100*b/1 (X per m2->m2),|b/t|,0.5799958135325068,0.06380592008058383,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.09,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T12-c10,12,10,18,S_constructed,living_area,A_structural,level,m2,0.03,,9.2,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,OLS,173.0,0.76,t,Multivariate specification: constructed surface + square + height-regime dummies; complete-case subsample; Duration control included,semi_elasticity,3.0,0.32608695652173914,100*b/1 (X per m2->m2),|b/t|,0.5846250629439848,0.06354620249391138,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.2,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c1,13,1,19,S_useful,living_area,A_structural,level,m2,0.01,,6.85,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4887",semi_elasticity,1.0,0.14598540145985403,100*b/1 (X per m2->m2),|b/t|,0.4727821557643431,0.06901929281231285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.85,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c2,13,2,19,S_useful,living_area,A_structural,level,m2,0.01,,6.34,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5165",semi_elasticity,1.0,0.1577287066246057,100*b/1 (X per m2->m2),|b/t|,0.4447665405253948,0.0701524511869708,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.34,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c3,13,3,19,S_useful,living_area,A_structural,level,m2,0.01,,9.78,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.527",semi_elasticity,1.0,0.10224948875255625,100*b/1 (X per m2->m2),|b/t|,0.6081125365183934,0.062179195963025916,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.78,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c4,13,4,19,S_useful,living_area,A_structural,level,m2,0.01,,14.08,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5213",semi_elasticity,1.0,0.07102272727272728,100*b/1 (X per m2->m2),|b/t|,0.7407998587965198,0.05261362633498009,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.08,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c5,13,5,19,S_useful,living_area,A_structural,level,m2,0.01,,14.41,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5132",semi_elasticity,1.0,0.06939625260235947,100*b/1 (X per m2->m2),|b/t|,0.7484849834846347,0.051942052982972546,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.41,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c6,13,6,19,S_useful,living_area,A_structural,level,m2,0.01,,9.2,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5084",semi_elasticity,1.0,0.10869565217391304,100*b/1 (X per m2->m2),|b/t|,0.5846250629439848,0.06354620249391138,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.2,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c7,13,7,19,S_useful,living_area,A_structural,level,m2,0.01,,6.82,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4991",semi_elasticity,1.0,0.1466275659824047,100*b/1 (X per m2->m2),|b/t|,0.471172037664912,0.06908680904177594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.82,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c8,13,8,19,S_useful,living_area,A_structural,level,m2,0.01,,6.47,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4787",semi_elasticity,1.0,0.15455950540958271,100*b/1 (X per m2->m2),|b/t|,0.4520377894762579,0.06986673716789148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.47,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c9,13,9,19,S_useful,living_area,A_structural,level,m2,0.01,,5.62,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4593",semi_elasticity,1.0,0.1779359430604982,100*b/1 (X per m2->m2),|b/t|,0.40288612018947934,0.07168792174190024,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.62,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c1,13,1,19,Comfort,condition,A_structural,binary,binary,0.14,,1.51,,,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4887",pct_premium,14.534046585398318,10.664790188080254,100*(exp(b - se^2/2) - 1),|b/t|,0.11745368957370614,0.07778390037993785,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.51,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c2,13,2,19,Comfort,condition,A_structural,binary,binary,0.12,,1.26,,,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5165",pct_premium,12.239506459536198,10.738065253136911,100*(exp(b - se^2/2) - 1),|b/t|,0.09821368109222837,0.077947365946213,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.26,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c3,13,3,19,Comfort,condition,A_structural,binary,binary,0.18,,2.73,,**,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.527",pct_premium,19.461785720376824,7.893740855748199,100*(exp(b - se^2/2) - 1),|b/t|,0.20910308960733248,0.0765945383177042,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.73,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c4,13,4,19,Comfort,condition,A_structural,binary,binary,0.18,,3.91,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5213",pct_premium,19.594940640911474,5.511486582146439,100*(exp(b - se^2/2) - 1),|b/t|,0.2928300077679118,0.07489258510688282,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.91,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c5,13,5,19,Comfort,condition,A_structural,binary,binary,0.2,,4.09,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5132",pct_premium,21.994333013338863,5.972629624255109,100*(exp(b - se^2/2) - 1),|b/t|,0.3050811089962229,0.07459195818978555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.09,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c6,13,6,19,Comfort,condition,A_structural,binary,binary,0.24,,3.86,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5084",pct_premium,26.879427811133482,7.904139794744485,100*(exp(b - se^2/2) - 1),|b/t|,0.2894008610108357,0.0749743163240507,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.86,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c7,13,7,19,Comfort,condition,A_structural,binary,binary,0.26,,3.25,,**,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4991",pct_premium,29.278654359318026,10.375440693326174,100*(exp(b - se^2/2) - 1),|b/t|,0.24669219681861024,0.07590529132880315,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.25,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c8,13,8,19,Comfort,condition,A_structural,binary,binary,0.29,,2.91,,**,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4787",pct_premium,32.9807646677611,13.318349537023604,100*(exp(b - se^2/2) - 1),|b/t|,0.22222930149559103,0.07636745755862234,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.91,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c9,13,9,19,Comfort,condition,A_structural,binary,binary,0.3,,2.57,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4593",pct_premium,34.06933109755457,15.757106703221826,100*(exp(b - se^2/2) - 1),|b/t|,0.1973394555861255,0.07678578038370643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.57,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c3,13,3,19,Floor,floor_level,A_structural,level,count,-0.01,,-0.95,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.527",semi_elasticity,-1.0,1.0526315789473686,100*b/1 (per unit count),|b/t|,-0.07420459794567237,0.07811010310070776,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.95,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c5,13,5,19,Floor,floor_level,A_structural,level,count,-0.01,,-1.3,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5132",semi_elasticity,-1.0,0.7692307692307692,100*b/1 (per unit count),|b/t|,-0.10130006814979362,0.0779231293459951,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c7,13,7,19,Floor,floor_level,A_structural,level,count,-0.01,,-1.04,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4991",semi_elasticity,-1.0,0.9615384615384616,100*b/1 (per unit count),|b/t|,-0.08119016016629894,0.07806746169836437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.04,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c8,13,8,19,Floor,floor_level,A_structural,level,count,-0.01,,-1.52,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4787",semi_elasticity,-1.0,0.6578947368421052,100*b/1 (per unit count),|b/t|,-0.11822069266068613,0.0777767714872935,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.52,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c9,13,9,19,Floor,floor_level,A_structural,level,count,-0.02,,-1.6,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4593",semi_elasticity,-2.0,1.25,100*b/1 (per unit count),|b/t|,-0.12434899333339904,0.0777181208333744,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c1,13,1,19,No_bathrooms,bathrooms,A_structural,level,count,0.03,,0.35,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4887",semi_elasticity,3.0,8.571428571428571,100*b/1 (per unit count),|b/t|,0.027403820235783725,0.07829662924509635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.35,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c2,13,2,19,No_bathrooms,bathrooms,A_structural,level,count,0.1,,1.25,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5165",semi_elasticity,10.0,8.0,100*b/1 (per unit count),|b/t|,0.09744163775668438,0.0779533102053475,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.25,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c3,13,3,19,No_bathrooms,bathrooms,A_structural,level,count,0.07,,1.31,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.527",semi_elasticity,7.000000000000001,5.34351145038168,100*b/1 (per unit count),|b/t|,0.10207121166292979,0.07791695546788532,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.31,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c4,13,4,19,No_bathrooms,bathrooms,A_structural,level,count,0.07,,2.07,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5213",semi_elasticity,7.000000000000001,3.381642512077295,100*b/1 (per unit count),|b/t|,0.16004494992527651,0.07731640093008528,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.07,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c5,13,5,19,No_bathrooms,bathrooms,A_structural,level,count,0.05,,1.3,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5132",semi_elasticity,5.0,3.8461538461538463,100*b/1 (per unit count),|b/t|,0.10130006814979362,0.0779231293459951,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c6,13,6,19,No_bathrooms,bathrooms,A_structural,level,count,0.12,,2.32,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5084",semi_elasticity,12.0,5.172413793103448,100*b/1 (per unit count),|b/t|,0.17878852324638245,0.07706401864068209,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.32,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c7,13,7,19,No_bathrooms,bathrooms,A_structural,level,count,0.13,,2.1,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4991",semi_elasticity,13.0,6.190476190476191,100*b/1 (per unit count),|b/t|,0.16230376580572478,0.0772875075265356,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c8,13,8,19,No_bathrooms,bathrooms,A_structural,level,count,0.07,,0.96,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4787",semi_elasticity,7.000000000000001,7.291666666666667,100*b/1 (per unit count),|b/t|,0.07498133021571891,0.07810555230804055,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.96,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c9,13,9,19,No_bathrooms,bathrooms,A_structural,level,count,0.07,,0.72,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4593",semi_elasticity,7.000000000000001,9.722222222222223,100*b/1 (per unit count),|b/t|,0.056305287704943245,0.07820178847908785,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.72,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c1,13,1,19,No_balconies,terrace_balcony,C_exterior,level,count,0.01,,0.11,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4887",semi_elasticity,1.0,9.090909090909092,100*b/1 (per unit count),|b/t|,0.00861554517636434,0.07832313796694854,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.11,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c3,13,3,19,No_balconies,terrace_balcony,C_exterior,level,count,0.01,,0.12,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.527",semi_elasticity,1.0,8.333333333333334,100*b/1 (per unit count),|b/t|,0.009398710251270781,0.07832258542725651,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.12,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c4,13,4,19,No_balconies,terrace_balcony,C_exterior,level,count,-0.02,,-0.69,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5213",semi_elasticity,-2.0,2.8985507246376816,100*b/1 (per unit count),|b/t|,-0.053966214667216864,0.07821190531480704,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.69,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c5,13,5,19,No_balconies,terrace_balcony,C_exterior,level,count,-0.02,,-0.59,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5132",semi_elasticity,-2.0,3.389830508474576,100*b/1 (per unit count),|b/t|,-0.046163100276330755,0.07824254284123856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.59,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c6,13,6,19,No_balconies,terrace_balcony,C_exterior,level,count,-0.04,,-0.95,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5084",semi_elasticity,-4.0,4.210526315789474,100*b/1 (per unit count),|b/t|,-0.07420459794567237,0.07811010310070776,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.95,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c7,13,7,19,No_balconies,terrace_balcony,C_exterior,level,count,-0.05,,-0.92,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4991",semi_elasticity,-5.0,5.434782608695652,100*b/1 (per unit count),|b/t|,-0.07187359623253212,0.07812347416579578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.92,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c8,13,8,19,No_balconies,terrace_balcony,C_exterior,level,count,-0.06,,-0.88,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4787",semi_elasticity,-6.0,6.8181818181818175,100*b/1 (per unit count),|b/t|,-0.06876376756217446,0.07814064495701643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.88,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c9,13,9,19,No_balconies,terrace_balcony,C_exterior,level,count,-0.02,,-0.23,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4593",semi_elasticity,-2.0,8.695652173913043,100*b/1 (per unit count),|b/t|,-0.018012067769695272,0.07831333812910987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.23,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c1,13,1,19,No_parking,parking,A_structural,level,count,-0.07,,-0.59,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4887",semi_elasticity,-7.000000000000001,11.864406779661019,100*b/1 (per unit count),|b/t|,-0.046163100276330755,0.07824254284123856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.59,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c2,13,2,19,No_parking,parking,A_structural,level,count,0.06,,0.5,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5165",semi_elasticity,6.0,12.0,100*b/1 (per unit count),|b/t|,0.03913302400974161,0.07826604801948324,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c3,13,3,19,No_parking,parking,A_structural,level,count,0.04,,0.53,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.527",semi_elasticity,4.0,7.547169811320755,100*b/1 (per unit count),|b/t|,0.04147708024010317,0.07825864196245881,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.53,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c4,13,4,19,No_parking,parking,A_structural,level,count,0.03,,0.65,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5213",semi_elasticity,3.0,4.615384615384615,100*b/1 (per unit count),|b/t|,0.05084607475894782,0.07822473039838125,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.65,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c5,13,5,19,No_parking,parking,A_structural,level,count,0.02,,0.27,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5132",semi_elasticity,2.0,7.4074074074074066,100*b/1 (per unit count),|b/t|,0.021143304620203605,0.07830853563038372,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.27,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c6,13,6,19,No_parking,parking,A_structural,level,count,0.1,,1.37,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5084",semi_elasticity,10.0,7.2992700729927,100*b/1 (per unit count),|b/t|,0.10669416293216134,0.07787895104537323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.37,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c7,13,7,19,No_parking,parking,A_structural,level,count,0.09,,0.92,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4991",semi_elasticity,9.0,9.782608695652172,100*b/1 (per unit count),|b/t|,0.07187359623253212,0.07812347416579578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.92,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c8,13,8,19,No_parking,parking,A_structural,level,count,0.06,,0.51,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4787",semi_elasticity,6.0,11.76470588235294,100*b/1 (per unit count),|b/t|,0.039914449789453355,0.07826362703814382,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.51,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c9,13,9,19,No_parking,parking,A_structural,level,count,0.1,,0.76,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4593",semi_elasticity,10.0,13.157894736842104,100*b/1 (per unit count),|b/t|,0.059422603574431083,0.07818763628214616,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.76,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c1,13,1,19,Structure,roof_materials,A_structural,binary,binary,0.87,,7.22,,***,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4887",pct_premium,136.96447322266724,28.76194518789641,100*(exp(b - se^2/2) - 1),|b/t|,0.4922529460177041,0.0681790783958039,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.22,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c2,13,2,19,Structure,roof_materials,A_structural,binary,binary,-0.02,,-0.16,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5165",pct_premium,-2.7429293286145295,12.25248341633444,100*(exp(b - se^2/2) - 1),|b/t|,-0.0125311831946079,0.07831989496629937,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.16,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c3,13,3,19,Structure,roof_materials,A_structural,binary,binary,0.06,,0.76,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.527",pct_premium,5.853264984809026,8.38292010430547,100*(exp(b - se^2/2) - 1),|b/t|,0.059422603574431083,0.07818763628214616,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.76,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c4,13,4,19,Structure,roof_materials,A_structural,binary,binary,0.04,,0.74,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5213",pct_premium,3.9291342675290775,5.626004184823721,100*(exp(b - se^2/2) - 1),|b/t|,0.05786415721199271,0.0781948070432334,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.74,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c5,13,5,19,Structure,roof_materials,A_structural,binary,binary,0.07,,1.12,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5132",pct_premium,7.041548302856615,6.703176132838854,100*(exp(b - se^2/2) - 1),|b/t|,0.0873895527330593,0.07802638636880294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.12,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c6,13,6,19,Structure,roof_materials,A_structural,binary,binary,0.14,,1.78,,†,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.5084",pct_premium,14.672144822677469,9.047097294382688,100*(exp(b - se^2/2) - 1),|b/t|,0.13808477074149605,0.07757571389971687,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.78,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c7,13,7,19,Structure,roof_materials,A_structural,binary,binary,0.08,,0.82,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4991",pct_premium,7.814387466396622,10.568654318780084,100*(exp(b - se^2/2) - 1),|b/t|,0.06409529150234007,0.0781649896370001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.82,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c8,13,8,19,Structure,roof_materials,A_structural,binary,binary,-0.09,,-0.75,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4787",pct_premium,-9.262548691804383,10.96717422325474,100*(exp(b - se^2/2) - 1),|b/t|,-0.05864343398897361,0.07819124531863149,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.75,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T13-c9,13,9,19,Structure,roof_materials,A_structural,binary,binary,-0.02,,-0.16,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface (linear), Duration control, no height regimes; pseudo-R2 = 0.4593",pct_premium,-2.7429293286145295,12.25248341633444,100*(exp(b - se^2/2) - 1),|b/t|,-0.0125311831946079,0.07831989496629937,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.16,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c1,14,1,20,S_useful,living_area,A_structural,level,m2,0.03,,5.56,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5844",semi_elasticity,3.0,0.539568345323741,100*b/1 (X per m2->m2),|b/t|,0.3992736565154539,0.07181180872580108,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.56,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c2,14,2,20,S_useful,living_area,A_structural,level,m2,0.03,,9.94,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.6082",semi_elasticity,3.0,0.3018108651911469,100*b/1 (X per m2->m2),|b/t|,0.6143255488460344,0.06180337513541593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.94,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c3,14,3,20,S_useful,living_area,A_structural,level,m2,0.03,,10.65,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5934",semi_elasticity,3.0,0.2816901408450704,100*b/1 (X per m2->m2),|b/t|,0.6405645679788211,0.0601469077914386,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.65,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c4,14,4,20,S_useful,living_area,A_structural,level,m2,0.03,,10.89,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.571",semi_elasticity,3.0,0.2754820936639118,100*b/1 (X per m2->m2),|b/t|,0.6489595778177493,0.05959224773349395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.89,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c5,14,5,20,S_useful,living_area,A_structural,level,m2,0.03,,8.98,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5546",semi_elasticity,3.0,0.3340757238307349,100*b/1 (X per m2->m2),|b/t|,0.5753096844287285,0.06406566641745307,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.98,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c6,14,6,20,S_useful,living_area,A_structural,level,m2,0.03,,8.31,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5453",semi_elasticity,3.0,0.3610108303249097,100*b/1 (X per m2->m2),|b/t|,0.5455122772628948,0.06564528005570333,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.31,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c7,14,7,20,S_useful,living_area,A_structural,level,m2,0.03,,6.46,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5363",semi_elasticity,3.0,0.46439628482972134,100*b/1 (X per m2->m2),|b/t|,0.4514816231577851,0.06988879615445591,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.46,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c8,14,8,20,S_useful,living_area,A_structural,level,m2,0.04,,6.84,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5186",semi_elasticity,4.0,0.584795321637427,100*b/1 (X per m2->m2),|b/t|,0.4722459744779502,0.06904180913420324,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.84,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c9,14,9,20,S_useful,living_area,A_structural,level,m2,0.04,,7.5,,***,,,high,Useful (interior usable) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5181",semi_elasticity,4.0,0.5333333333333333,100*b/1 (X per m2->m2),|b/t|,0.5065140100898807,0.06753520134531743,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.5,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c1,14,1,20,Comfort,condition,A_structural,binary,binary,0.11,,1.14,,,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5844",pct_premium,11.10935621329514,10.771104188638231,100*(exp(b - se^2/2) - 1),|b/t|,0.08893784421580979,0.07801565282088578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.14,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c2,14,2,20,Comfort,condition,A_structural,binary,binary,0.1,,1.82,,†,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.6082",pct_premium,10.35039436444627,6.0723676817343275,100*(exp(b - se^2/2) - 1),|b/t|,0.14112666300859447,0.07754212253219477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.82,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c3,14,3,20,Comfort,condition,A_structural,binary,binary,0.11,,2.15,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5934",pct_premium,11.481802400731222,5.711190127929108,100*(exp(b - se^2/2) - 1),|b/t|,0.166062779645818,0.07723850216084559,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.15,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c4,14,4,20,Comfort,condition,A_structural,binary,binary,0.1,,1.98,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.571",pct_premium,10.376230357060567,5.581671303412363,100*(exp(b - se^2/2) - 1),|b/t|,0.15325352828981126,0.07740077186354105,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.98,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c5,14,5,20,Comfort,condition,A_structural,binary,binary,0.13,,2.27,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5546",pct_premium,13.696240224322697,6.52192466221149,100*(exp(b - se^2/2) - 1),|b/t|,0.1750546600335824,0.07711659032316404,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.27,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c6,14,6,20,Comfort,condition,A_structural,binary,binary,0.16,,2.46,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5453",pct_premium,17.103135076161546,7.632591030841043,100*(exp(b - se^2/2) - 1),|b/t|,0.1892018873600817,0.07691133632523646,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.46,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c7,14,7,20,Comfort,condition,A_structural,binary,binary,0.18,,2.15,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5363",pct_premium,19.30289422980951,10.023215133112828,100*(exp(b - se^2/2) - 1),|b/t|,0.166062779645818,0.07723850216084559,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.15,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c8,14,8,20,Comfort,condition,A_structural,binary,binary,0.16,,1.65,,,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5186",pct_premium,16.800648770761818,11.3794993550721,100*(exp(b - se^2/2) - 1),|b/t|,0.12817201327964664,0.07768000804827069,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.65,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c9,14,9,20,Comfort,condition,A_structural,binary,binary,0.03,,0.24,,,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5181",pct_premium,2.2435473150278495,12.880681674418963,100*(exp(b - se^2/2) - 1),|b/t|,0.018794930270996775,0.07831220946248657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.24,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c1,14,1,20,Floor,floor_level,A_structural,level,count,-0.01,,-1.24,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5844",semi_elasticity,-1.0,0.8064516129032258,100*b/1 (per unit count),|b/t|,-0.09666941847029474,0.07795920844378608,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.24,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c2,14,2,20,Floor,floor_level,A_structural,level,count,-0.01,,-2.02,,*,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.6082",semi_elasticity,-1.0,0.49504950495049505,100*b/1 (per unit count),|b/t|,-0.15627467928229707,0.07736370261499854,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.02,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c3,14,3,20,Floor,floor_level,A_structural,level,count,-0.01,,-2.73,,**,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5934",semi_elasticity,-1.0,0.3663003663003663,100*b/1 (per unit count),|b/t|,-0.20910308960733248,0.0765945383177042,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.73,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c4,14,4,20,Floor,floor_level,A_structural,level,count,-0.01,,-1.5,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.571",semi_elasticity,-1.0,0.6666666666666667,100*b/1 (per unit count),|b/t|,-0.1166864762376621,0.07779098415844139,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c7,14,7,20,Floor,floor_level,A_structural,level,count,-0.01,,-1.37,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5363",semi_elasticity,-1.0,0.7299270072992701,100*b/1 (per unit count),|b/t|,-0.10669416293216134,0.07787895104537323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.37,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c8,14,8,20,Floor,floor_level,A_structural,level,count,-0.02,,-1.88,,†,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5186",semi_elasticity,-2.0,1.0638297872340428,100*b/1 (per unit count),|b/t|,-0.14568199190517223,0.07749042122615545,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.88,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c9,14,9,20,Floor,floor_level,A_structural,level,count,-0.03,,-3.32,,**,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5181",semi_elasticity,-3.0,0.9036144578313252,100*b/1 (per unit count),|b/t|,-0.2516723513898991,0.07580492511743948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.32,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c1,14,1,20,No_bathrooms,bathrooms,A_structural,level,count,0.08,,1.17,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5844",semi_elasticity,8.0,6.837606837606838,100*b/1 (per unit count),|b/t|,0.09125906972803648,0.07799920489575768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.17,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c2,14,2,20,No_bathrooms,bathrooms,A_structural,level,count,0.08,,2.09,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.6082",semi_elasticity,8.0,3.8277511961722492,100*b/1 (per unit count),|b/t|,0.1615511088030177,0.07729718124546302,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.09,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c3,14,3,20,No_bathrooms,bathrooms,A_structural,level,count,0.08,,2.19,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5934",semi_elasticity,8.0,3.652968036529681,100*b/1 (per unit count),|b/t|,0.16906479552348647,0.07719853676871528,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.19,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c4,14,4,20,No_bathrooms,bathrooms,A_structural,level,count,0.08,,2.13,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.571",semi_elasticity,8.0,3.755868544600939,100*b/1 (per unit count),|b/t|,0.1645600330113241,0.07725823146071555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.13,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c5,14,5,20,No_bathrooms,bathrooms,A_structural,level,count,0.1,,2.38,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5546",semi_elasticity,10.0,4.201680672268908,100*b/1 (per unit count),|b/t|,0.183258971223675,0.07699956774103991,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.38,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c6,14,6,20,No_bathrooms,bathrooms,A_structural,level,count,0.12,,2.47,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5453",semi_elasticity,12.0,4.8582995951417,100*b/1 (per unit count),|b/t|,0.18994330645012425,0.0769001240688762,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.47,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c7,14,7,20,No_bathrooms,bathrooms,A_structural,level,count,0.11,,1.75,,†,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5363",semi_elasticity,11.0,6.2857142857142865,100*b/1 (per unit count),|b/t|,0.1358007794987115,0.07760044542783513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.75,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c8,14,8,20,No_bathrooms,bathrooms,A_structural,level,count,0.03,,0.48,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5186",semi_elasticity,3.0,6.25,100*b/1 (per unit count),|b/t|,0.03756995846524677,0.07827074680259744,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.48,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c9,14,9,20,No_bathrooms,bathrooms,A_structural,level,count,0.04,,0.47,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5181",semi_elasticity,4.0,8.510638297872342,100*b/1 (per unit count),|b/t|,0.03678832155190899,0.07827302457852976,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.47,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c1,14,1,20,No_balconies,terrace_balcony,C_exterior,level,count,-0.05,,-0.86,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5844",semi_elasticity,-5.0,5.813953488372094,100*b/1 (per unit count),|b/t|,-0.06720809547985139,0.07814894823238534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.86,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c3,14,3,20,No_balconies,terrace_balcony,C_exterior,level,count,-0.02,,-0.54,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5934",semi_elasticity,-2.0,3.7037037037037033,100*b/1 (per unit count),|b/t|,-0.042258282063579004,0.07825607789551667,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.54,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c4,14,4,20,No_balconies,terrace_balcony,C_exterior,level,count,-0.01,,-0.2,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.571",semi_elasticity,-1.0,5.0,100*b/1 (per unit count),|b/t|,-0.015663287241915964,0.07831643620957981,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c5,14,5,20,No_balconies,terrace_balcony,C_exterior,level,count,-0.01,,-0.37,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5546",semi_elasticity,-1.0,2.7027027027027026,100*b/1 (per unit count),|b/t|,-0.028968474220789676,0.07829317356970182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.37,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c6,14,6,20,No_balconies,terrace_balcony,C_exterior,level,count,-0.02,,-0.56,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5453",semi_elasticity,-2.0,3.571428571428571,100*b/1 (per unit count),|b/t|,-0.04382045179337803,0.07825080677388933,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.56,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c7,14,7,20,No_balconies,terrace_balcony,C_exterior,level,count,-0.03,,-0.45,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5363",semi_elasticity,-3.0,6.666666666666667,100*b/1 (per unit count),|b/t|,-0.035224846576422025,0.07827743683649338,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.45,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c8,14,8,20,No_balconies,terrace_balcony,C_exterior,level,count,-0.05,,-0.72,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5186",semi_elasticity,-5.0,6.944444444444445,100*b/1 (per unit count),|b/t|,-0.056305287704943245,0.07820178847908785,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.72,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c9,14,9,20,No_balconies,terrace_balcony,C_exterior,level,count,-0.02,,-0.3,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5181",semi_elasticity,-2.0,6.666666666666667,100*b/1 (per unit count),|b/t|,-0.023491329058363677,0.0783044301945456,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c1,14,1,20,No_parking,parking,A_structural,level,count,0.11,,1.05,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5844",semi_elasticity,11.0,10.476190476190476,100*b/1 (per unit count),|b/t|,0.08196561473788967,0.07806249022656159,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.05,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c2,14,2,20,No_parking,parking,A_structural,level,count,0.23,,3.9,,***,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.6082",semi_elasticity,23.0,5.897435897435898,100*b/1 (per unit count),|b/t|,0.2921450767369252,0.07490899403510903,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c3,14,3,20,No_parking,parking,A_structural,level,count,0.18,,3.38,,***,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5934",semi_elasticity,18.0,5.325443786982249,100*b/1 (per unit count),|b/t|,0.25592521771509946,0.0757175200340531,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.38,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c4,14,4,20,No_parking,parking,A_structural,level,count,0.25,,4.65,,***,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.571",semi_elasticity,25.0,5.376344086021505,100*b/1 (per unit count),|b/t|,0.3422241386894086,0.0735965889654642,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.65,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c5,14,5,20,No_parking,parking,A_structural,level,count,0.23,,3.59,,***,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5546",semi_elasticity,23.0,6.406685236768802,100*b/1 (per unit count),|b/t|,0.27069249797073924,0.07540181001970454,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.59,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c6,14,6,20,No_parking,parking,A_structural,level,count,0.22,,3.01,,**,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5453",semi_elasticity,22.0,7.308970099667775,100*b/1 (per unit count),|b/t|,0.22947026126280803,0.0762359671969462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.01,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c7,14,7,20,No_parking,parking,A_structural,level,count,0.29,,3.2,,**,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5363",semi_elasticity,28.999999999999996,9.062499999999998,100*b/1 (per unit count),|b/t|,0.24312291308276734,0.07597591033836479,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c8,14,8,20,No_parking,parking,A_structural,level,count,0.27,,2.56,,*,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5186",semi_elasticity,27.0,10.546875,100*b/1 (per unit count),|b/t|,0.19660133280507944,0.07679739562698415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.56,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c9,14,9,20,No_parking,parking,A_structural,level,count,0.12,,1.0,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5181",semi_elasticity,12.0,12.0,100*b/1 (per unit count),|b/t|,0.07808688094430304,0.07808688094430304,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c1,14,1,20,Structure,roof_materials,A_structural,binary,binary,-0.04,,-0.33,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5844",pct_premium,-4.624283996290812,11.645932595785736,100*(exp(b - se^2/2) - 1),|b/t|,-0.025838964808374536,0.07829989335871071,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.33,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c2,14,2,20,Structure,roof_materials,A_structural,binary,binary,-0.01,,-0.21,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.6082",pct_premium,-1.1072035630721344,4.714523017853182,100*(exp(b - se^2/2) - 1),|b/t|,-0.016446244816782134,0.07831545150848634,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.21,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c3,14,3,20,Structure,roof_materials,A_structural,binary,binary,0.02,,0.29,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5934",pct_premium,1.7778060074763014,7.035871310529352,100*(exp(b - se^2/2) - 1),|b/t|,0.02270869551892764,0.07830584661699187,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.29,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c4,14,4,20,Structure,roof_materials,A_structural,binary,binary,0.04,,0.6,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.571",pct_premium,3.850042936142084,6.938738494615921,100*(exp(b - se^2/2) - 1),|b/t|,0.04694381579433043,0.07823969299055072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c5,14,5,20,Structure,roof_materials,A_structural,binary,binary,0.09,,1.19,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5546",pct_premium,9.104945138591813,8.275267691888144,100*(exp(b - se^2/2) - 1),|b/t|,0.09280572978466087,0.0779880082224041,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.19,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c6,14,6,20,Structure,roof_materials,A_structural,binary,binary,0.06,,0.81,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5453",pct_premium,5.892740714413414,7.865455900335997,100*(exp(b - se^2/2) - 1),|b/t|,0.06331679451827393,0.07816888212132585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.81,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c7,14,7,20,Structure,roof_materials,A_structural,binary,binary,0.06,,0.58,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5363",pct_premium,5.617007386293293,10.984515998745099,100*(exp(b - se^2/2) - 1),|b/t|,0.045382300157365094,0.07824534509890534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.58,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c8,14,8,20,Structure,roof_materials,A_structural,binary,binary,-0.1,,-0.86,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5186",pct_premium,-10.125902438083422,10.521365325999529,100*(exp(b - se^2/2) - 1),|b/t|,-0.06720809547985139,0.07814894823238534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.86,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T14-c9,14,9,20,Structure,roof_materials,A_structural,binary,binary,-0.07,,-0.55,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with useful surface + square, Duration control; pseudo-R2 = 0.5181",pct_premium,-7.512730091716035,11.866830435166616,100*(exp(b - se^2/2) - 1),|b/t|,-0.04303940638866546,0.07825346616120993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.55,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c1,15,1,21,S_constructed,living_area,A_structural,level,m2,0.01,,6.74,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4729",semi_elasticity,1.0,0.1483679525222552,100*b/1 (X per m2->m2),|b/t|,0.4668552883253223,0.06926636325301518,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.74,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c2,15,2,21,S_constructed,living_area,A_structural,level,m2,0.01,,6.59,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4941",semi_elasticity,1.0,0.15174506828528073,100*b/1 (X per m2->m2),|b/t|,0.45867070927872133,0.06960101809995772,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.59,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c3,15,3,21,S_constructed,living_area,A_structural,level,m2,0.01,,8.25,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.496",semi_elasticity,1.0,0.12121212121212122,100*b/1 (X per m2->m2),|b/t|,0.5427367311306341,0.06578627044007686,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.25,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c4,15,4,21,S_constructed,living_area,A_structural,level,m2,0.01,,9.41,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4844",semi_elasticity,1.0,0.10626992561105207,100*b/1 (X per m2->m2),|b/t|,0.5933064951550262,0.06305063710467866,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.41,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c5,15,5,21,S_constructed,living_area,A_structural,level,m2,0.01,,9.9,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4753",semi_elasticity,1.0,0.10101010101010101,100*b/1 (X per m2->m2),|b/t|,0.6127828769611389,0.06189726029910493,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.9,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c6,15,6,21,S_constructed,living_area,A_structural,level,m2,0.01,,8.45,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4788",semi_elasticity,1.0,0.11834319526627221,100*b/1 (X per m2->m2),|b/t|,0.5519193103906693,0.06531589472078926,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.45,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c7,15,7,21,S_constructed,living_area,A_structural,level,m2,0.01,,7.48,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4792",semi_elasticity,1.0,0.1336898395721925,100*b/1 (X per m2->m2),|b/t|,0.5055088071173947,0.0675813913258549,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.48,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c8,15,8,21,S_constructed,living_area,A_structural,level,m2,0.01,,6.12,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4667",semi_elasticity,1.0,0.16339869281045752,100*b/1 (X per m2->m2),|b/t|,0.43225858293354363,0.07063048740744177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.12,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c9,15,9,21,S_constructed,living_area,A_structural,level,m2,0.01,,3.84,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4491",semi_elasticity,1.0,0.2604166666666667,100*b/1 (X per m2->m2),|b/t|,0.28802606753872173,0.07500678842154213,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.84,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c1,15,1,21,Comfort,condition,A_structural,binary,binary,0.14,,1.42,,,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4729",pct_premium,14.469686268086491,11.340727594367031,100*(exp(b - se^2/2) - 1),|b/t|,0.11054135663698533,0.0778460258006939,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.42,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c2,15,2,21,Comfort,condition,A_structural,binary,binary,0.16,,1.81,,†,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4941",pct_premium,16.89348100389678,10.373576760148598,100*(exp(b - se^2/2) - 1),|b/t|,0.14036656109869525,0.07755058624237307,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.81,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c3,15,3,21,Comfort,condition,A_structural,binary,binary,0.2,,2.8,,**,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.496",pct_premium,21.82909056846871,8.724305415429786,100*(exp(b - se^2/2) - 1),|b/t|,0.2142215956964861,0.07650771274874506,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c4,15,4,21,Comfort,condition,A_structural,binary,binary,0.2,,3.21,,**,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4844",pct_premium,21.903434525923938,7.609986032150592,100*(exp(b - se^2/2) - 1),|b/t|,0.24383756556406858,0.075961858431174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.21,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c5,15,5,21,Comfort,condition,A_structural,binary,binary,0.21,,3.25,,**,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4753",pct_premium,23.110535205154115,7.971458233566648,100*(exp(b - se^2/2) - 1),|b/t|,0.24669219681861024,0.07590529132880315,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.25,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c6,15,6,21,Comfort,condition,A_structural,binary,binary,0.25,,3.65,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4788",pct_premium,28.101706462213706,8.794694634847543,100*(exp(b - se^2/2) - 1),|b/t|,0.2748773764109295,0.07530887024956973,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.65,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c7,15,7,21,Comfort,condition,A_structural,binary,binary,0.25,,3.38,,***,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4792",pct_premium,28.051792703746937,9.497229413370869,100*(exp(b - se^2/2) - 1),|b/t|,0.25592521771509946,0.0757175200340531,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.38,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c8,15,8,21,Comfort,condition,A_structural,binary,binary,0.3,,3.23,,**,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4667",pct_premium,34.404902962690564,12.537388305659473,100*(exp(b - se^2/2) - 1),|b/t|,0.24526567865625545,0.07593364664280354,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.23,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c9,15,9,21,Comfort,condition,A_structural,binary,binary,0.31,,2.08,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4491",pct_premium,34.836637686966185,20.32027814331611,100*(exp(b - se^2/2) - 1),|b/t|,0.160798169784715,0.0773068123964976,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.08,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c3,15,3,21,Floor,floor_level,A_structural,level,count,-0.01,,-1.41,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.496",semi_elasticity,-1.0,0.7092198581560284,100*b/1 (per unit count),|b/t|,-0.10977230965416428,0.07785270188238601,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.41,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c7,15,7,21,Floor,floor_level,A_structural,level,count,-0.01,,-1.08,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4792",semi_elasticity,-1.0,0.9259259259259258,100*b/1 (per unit count),|b/t|,-0.08429107995739295,0.07804729625684532,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.08,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c8,15,8,21,Floor,floor_level,A_structural,level,count,-0.01,,-1.4,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4667",semi_elasticity,-1.0,0.7142857142857143,100*b/1 (per unit count),|b/t|,-0.10900306547625242,0.07785933248303746,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c9,15,9,21,Floor,floor_level,A_structural,level,count,-0.02,,-1.24,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4491",semi_elasticity,-2.0,1.6129032258064515,100*b/1 (per unit count),|b/t|,-0.09666941847029474,0.07795920844378608,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.24,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c1,15,1,21,No_bathrooms,bathrooms,A_structural,level,count,0.02,,0.23,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4729",semi_elasticity,2.0,8.695652173913043,100*b/1 (per unit count),|b/t|,0.018012067769695272,0.07831333812910987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.23,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c2,15,2,21,No_bathrooms,bathrooms,A_structural,level,count,0.05,,0.79,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4941",semi_elasticity,5.0,6.329113924050633,100*b/1 (per unit count),|b/t|,0.06175945514506461,0.07817652550008178,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.79,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c3,15,3,21,No_bathrooms,bathrooms,A_structural,level,count,0.1,,1.78,,†,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.496",semi_elasticity,10.0,5.617977528089888,100*b/1 (per unit count),|b/t|,0.13808477074149605,0.07757571389971687,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.78,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c4,15,4,21,No_bathrooms,bathrooms,A_structural,level,count,0.06,,1.33,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4844",semi_elasticity,6.0,4.511278195488721,100*b/1 (per unit count),|b/t|,0.10361294545812871,0.0779044702692697,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.33,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c5,15,5,21,No_bathrooms,bathrooms,A_structural,level,count,0.06,,1.12,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4753",semi_elasticity,6.0,5.357142857142856,100*b/1 (per unit count),|b/t|,0.0873895527330593,0.07802638636880294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.12,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c6,15,6,21,No_bathrooms,bathrooms,A_structural,level,count,0.12,,2.25,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4788",semi_elasticity,12.0,5.333333333333333,100*b/1 (per unit count),|b/t|,0.17355898767151737,0.07713732785400773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.25,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c7,15,7,21,No_bathrooms,bathrooms,A_structural,level,count,0.17,,2.84,,**,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4792",semi_elasticity,17.0,5.985915492957748,100*b/1 (per unit count),|b/t|,0.21713858208422665,0.07645724721275586,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.84,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c8,15,8,21,No_bathrooms,bathrooms,A_structural,level,count,0.11,,1.44,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4667",semi_elasticity,11.0,7.638888888888889,100*b/1 (per unit count),|b/t|,0.11207885376546127,0.07783253733712589,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.44,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c9,15,9,21,No_bathrooms,bathrooms,A_structural,level,count,0.11,,0.92,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4491",semi_elasticity,11.0,11.956521739130434,100*b/1 (per unit count),|b/t|,0.07187359623253212,0.07812347416579578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.92,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c1,15,1,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.12,,-1.67,,†,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4729",semi_elasticity,-12.0,7.18562874251497,100*b/1 (per unit count),|b/t|,-0.129699632680199,0.077664450706706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.67,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c2,15,2,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.02,,-0.37,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4941",semi_elasticity,-2.0,5.405405405405405,100*b/1 (per unit count),|b/t|,-0.028968474220789676,0.07829317356970182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.37,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c3,15,3,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.06,,-1.08,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.496",semi_elasticity,-6.0,5.555555555555555,100*b/1 (per unit count),|b/t|,-0.08429107995739295,0.07804729625684532,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.08,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c4,15,4,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.07,,-1.44,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4844",semi_elasticity,-7.000000000000001,4.861111111111112,100*b/1 (per unit count),|b/t|,-0.11207885376546127,0.07783253733712589,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.44,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c5,15,5,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.1,,-2.1,,*,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4753",semi_elasticity,-10.0,4.761904761904762,100*b/1 (per unit count),|b/t|,-0.16230376580572478,0.0772875075265356,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c6,15,6,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.08,,-1.67,,†,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4788",semi_elasticity,-8.0,4.790419161676647,100*b/1 (per unit count),|b/t|,-0.129699632680199,0.077664450706706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.67,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c7,15,7,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.07,,-1.29,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4792",semi_elasticity,-7.000000000000001,5.426356589147288,100*b/1 (per unit count),|b/t|,-0.1005287420017387,0.07792925736568891,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.29,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c8,15,8,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.03,,-0.39,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4667",semi_elasticity,-3.0,7.692307692307692,100*b/1 (per unit count),|b/t|,-0.030532915299387793,0.07828952640868665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.39,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c9,15,9,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.01,,-0.08,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4491",semi_elasticity,-1.0,12.5,100*b/1 (per unit count),|b/t|,-0.006265960588387915,0.07832450735484893,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.08,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c1,15,1,21,No_parking,parking,A_structural,level,count,-0.26,,-2.14,,*,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4729",semi_elasticity,-26.0,12.149532710280374,100*b/1 (per unit count),|b/t|,-0.16531155025463876,0.07724838796945735,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.14,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,True
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c2,15,2,21,No_parking,parking,A_structural,level,count,-0.01,,-0.12,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4941",semi_elasticity,-1.0,8.333333333333334,100*b/1 (per unit count),|b/t|,-0.009398710251270781,0.07832258542725651,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.12,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c3,15,3,21,No_parking,parking,A_structural,level,count,-0.09,,-1.11,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.496",semi_elasticity,-9.0,8.108108108108107,100*b/1 (per unit count),|b/t|,-0.08661516872350343,0.07803168353468777,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.11,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c4,15,4,21,No_parking,parking,A_structural,level,count,0.03,,0.38,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4844",semi_elasticity,3.0,7.894736842105263,100*b/1 (per unit count),|b/t|,0.029750722089589628,0.07829137391997269,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.38,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c5,15,5,21,No_parking,parking,A_structural,level,count,0.13,,1.76,,†,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4753",semi_elasticity,13.0,7.386363636363637,100*b/1 (per unit count),|b/t|,0.1365623523826234,0.07759224567194511,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.76,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c6,15,6,21,No_parking,parking,A_structural,level,count,0.07,,0.9,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4788",semi_elasticity,7.000000000000001,7.777777777777778,100*b/1 (per unit count),|b/t|,0.07031893818579951,0.07813215353977723,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c7,15,7,21,No_parking,parking,A_structural,level,count,0.04,,0.43,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4792",semi_elasticity,4.0,9.30232558139535,100*b/1 (per unit count),|b/t|,0.03366111292083537,0.0782816579554311,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.43,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c8,15,8,21,No_parking,parking,A_structural,level,count,0.05,,0.42,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4667",semi_elasticity,5.0,11.904761904761905,100*b/1 (per unit count),|b/t|,0.032879152659595456,0.07828369680856062,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.42,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c9,15,9,21,No_parking,parking,A_structural,level,count,0.06,,0.34,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4491",semi_elasticity,6.0,17.64705882352941,100*b/1 (per unit count),|b/t|,0.02662141698558542,0.0782982852517218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.34,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c1,15,1,21,Structure,roof_materials,A_structural,binary,binary,0.84,,6.52,,***,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4729",pct_premium,129.72226605451928,29.84276473153554,100*(exp(b - se^2/2) - 1),|b/t|,0.4548107209358334,0.06975624554230575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.52,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c2,15,2,21,Structure,roof_materials,A_structural,binary,binary,0.46,,4.17,,***,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4941",pct_premium,57.44651996533576,17.474197436389968,100*(exp(b - se^2/2) - 1),|b/t|,0.31047822711185186,0.07445521033857358,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.17,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c3,15,3,21,Structure,roof_materials,A_structural,binary,binary,0.25,,2.79,,**,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.496",pct_premium,27.888090960737966,11.505604092184063,100*(exp(b - se^2/2) - 1),|b/t|,0.21349144934754488,0.07652023274105552,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.79,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c4,15,4,21,Structure,roof_materials,A_structural,binary,binary,0.25,,3.17,,**,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4844",pct_premium,28.00385656456601,10.126383412363891,100*(exp(b - se^2/2) - 1),|b/t|,0.2409765823537718,0.07601784932295641,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.17,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c5,15,5,21,Structure,roof_materials,A_structural,binary,binary,0.27,,3.3,,**,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4753",pct_premium,30.558718864649027,10.717890960544754,100*(exp(b - se^2/2) - 1),|b/t|,0.2502514693627675,0.07583377859477804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c6,15,6,21,Structure,roof_materials,A_structural,binary,binary,0.13,,1.52,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4788",pct_premium,13.467086790340987,9.739979594223739,100*(exp(b - se^2/2) - 1),|b/t|,0.11822069266068613,0.0777767714872935,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.52,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c7,15,7,21,Structure,roof_materials,A_structural,binary,binary,0.09,,0.99,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4792",pct_premium,8.966223121049467,9.94703894277464,100*(exp(b - se^2/2) - 1),|b/t|,0.07731070277406268,0.07809161896369968,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.99,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c8,15,8,21,Structure,roof_materials,A_structural,binary,binary,0.05,,0.43,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4667",pct_premium,4.418804081737182,12.224082516000282,100*(exp(b - se^2/2) - 1),|b/t|,0.03366111292083537,0.0782816579554311,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.43,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T15-c9,15,9,21,Structure,roof_materials,A_structural,binary,binary,0.07,,0.37,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface (linear), Duration control; pseudo-R2 = 0.4491",pct_premium,5.34850099445483,20.29069532102572,100*(exp(b - se^2/2) - 1),|b/t|,0.028968474220789676,0.07829317356970182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.37,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c1,16,1,21,S_constructed,living_area,A_structural,level,m2,0.03,,7.03,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5574",semi_elasticity,3.0,0.42674253200568985,100*b/1 (X per m2->m2),|b/t|,0.4823438024700204,0.06861220518776963,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.03,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c2,16,2,21,S_constructed,living_area,A_structural,level,m2,0.02,,8.59,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5769",semi_elasticity,2.0,0.23282887077997672,100*b/1 (X per m2->m2),|b/t|,0.5582300708718622,0.06498603851826103,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.59,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c3,16,3,21,S_constructed,living_area,A_structural,level,m2,0.02,,7.78,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5539",semi_elasticity,2.0,0.2570694087403599,100*b/1 (X per m2->m2),|b/t|,0.5203711877421267,0.06688575677919364,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.78,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c4,16,4,21,S_constructed,living_area,A_structural,level,m2,0.02,,8.25,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5284",semi_elasticity,2.0,0.24242424242424243,100*b/1 (X per m2->m2),|b/t|,0.5427367311306341,0.06578627044007686,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.25,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c5,16,5,21,S_constructed,living_area,A_structural,level,m2,0.03,,7.54,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5185",semi_elasticity,3.0,0.3978779840848806,100*b/1 (X per m2->m2),|b/t|,0.5085182345615921,0.06744273667925624,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.54,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c6,16,6,21,S_constructed,living_area,A_structural,level,m2,0.03,,8.96,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5133",semi_elasticity,3.0,0.3348214285714285,100*b/1 (X per m2->m2),|b/t|,0.5744515134501954,0.06411289212613787,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.96,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c7,16,7,21,S_constructed,living_area,A_structural,level,m2,0.02,,6.11,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5152",semi_elasticity,2.0,0.3273322422258592,100*b/1 (X per m2->m2),|b/t|,0.4316839863350638,0.07065204359002679,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.11,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c8,16,8,21,S_constructed,living_area,A_structural,level,m2,0.03,,7.48,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5028",semi_elasticity,3.0,0.4010695187165775,100*b/1 (X per m2->m2),|b/t|,0.5055088071173947,0.0675813913258549,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.48,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c9,16,9,21,S_constructed,living_area,A_structural,level,m2,0.03,,6.27,,***,,,high,Constructed (gross built) surface in square metres,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5006",semi_elasticity,3.0,0.4784688995215311,100*b/1 (X per m2->m2),|b/t|,0.4408143797372346,0.07030532372204698,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.27,163.0,m2,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c1,16,1,21,Comfort,condition,A_structural,binary,binary,0.04,,0.47,,,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5574",pct_premium,3.7048244996988,8.8579640356799,100*(exp(b - se^2/2) - 1),|b/t|,0.03678832155190899,0.07827302457852976,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.47,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c2,16,2,21,Comfort,condition,A_structural,binary,binary,0.09,,1.59,,,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5769",pct_premium,9.24228268001006,6.193439341727605,100*(exp(b - se^2/2) - 1),|b/t|,0.12358371871647124,0.07772560925564229,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.59,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c3,16,3,21,Comfort,condition,A_structural,binary,binary,0.14,,2.31,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5539",pct_premium,14.816320532357551,6.971356356710469,100*(exp(b - se^2/2) - 1),|b/t|,0.1780423628397666,0.07707461594795091,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.31,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c4,16,4,21,Comfort,condition,A_structural,binary,binary,0.14,,2.45,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5284",pct_premium,14.839733304392254,6.572993136327013,100*(exp(b - se^2/2) - 1),|b/t|,0.18846014453071327,0.07692250797171969,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.45,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c5,16,5,21,Comfort,condition,A_structural,binary,binary,0.15,,2.04,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5185",pct_premium,15.869771247573228,8.542898843590317,100*(exp(b - se^2/2) - 1),|b/t|,0.1577836170801829,0.07734491033342297,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.04,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c6,16,6,21,Comfort,condition,A_structural,binary,binary,0.17,,2.78,,**,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5133",pct_premium,18.309072510347214,7.248267076419502,100*(exp(b - se^2/2) - 1),|b/t|,0.21276094507182663,0.0765327140546139,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.78,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c7,16,7,21,Comfort,condition,A_structural,binary,binary,0.21,,2.42,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5152",pct_premium,22.904185767942643,10.705470768219673,100*(exp(b - se^2/2) - 1),|b/t|,0.18623298443757855,0.07695577869321428,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.42,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c8,16,8,21,Comfort,condition,A_structural,binary,binary,0.19,,2.19,,*,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5028",pct_premium,20.47071706603416,10.491206555017252,100*(exp(b - se^2/2) - 1),|b/t|,0.16906479552348647,0.07719853676871528,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.19,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c9,16,9,21,Comfort,condition,A_structural,binary,binary,0.13,,1.08,,,,,high,"Romanian apartment comfort class: 1 = Comfort 1 (higher standard), 0 = Comfort 2",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5006",pct_premium,13.060793877251564,13.708119428907482,100*(exp(b - se^2/2) - 1),|b/t|,0.08429107995739295,0.07804729625684532,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.08,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c2,16,2,21,Floor,floor_level,A_structural,level,count,-0.01,,-1.72,,†,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5769",semi_elasticity,-1.0,0.5813953488372093,100*b/1 (per unit count),|b/t|,-0.1335146210126104,0.07762477965849443,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.72,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c3,16,3,21,Floor,floor_level,A_structural,level,count,-0.01,,-2.09,,*,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5539",semi_elasticity,-1.0,0.47846889952153115,100*b/1 (per unit count),|b/t|,-0.1615511088030177,0.07729718124546302,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.09,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c4,16,4,21,Floor,floor_level,A_structural,level,count,-0.01,,-1.12,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5284",semi_elasticity,-1.0,0.8928571428571428,100*b/1 (per unit count),|b/t|,-0.0873895527330593,0.07802638636880294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.12,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c7,16,7,21,Floor,floor_level,A_structural,level,count,-0.01,,-1.45,,,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5152",semi_elasticity,-1.0,0.6896551724137931,100*b/1 (per unit count),|b/t|,-0.11284730128956229,0.07782572502728434,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.45,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c8,16,8,21,Floor,floor_level,A_structural,level,count,-0.02,,-2.18,,*,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5028",semi_elasticity,-2.0,0.9174311926605503,100*b/1 (per unit count),|b/t|,-0.1683147291176314,0.07720859133836303,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.18,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c9,16,9,21,Floor,floor_level,A_structural,level,count,-0.02,,-2.32,,*,,,high,"Floor level of the apartment (0 = ground, up to 10)",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5006",semi_elasticity,-2.0,0.8620689655172415,100*b/1 (per unit count),|b/t|,-0.17878852324638245,0.07706401864068209,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.32,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c1,16,1,21,No_bathrooms,bathrooms,A_structural,level,count,0.07,,1.13,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5574",semi_elasticity,7.000000000000001,6.194690265486727,100*b/1 (per unit count),|b/t|,0.08816377835032914,0.07802104278790191,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.13,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c2,16,2,21,No_bathrooms,bathrooms,A_structural,level,count,0.1,,2.45,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5769",semi_elasticity,10.0,4.081632653061225,100*b/1 (per unit count),|b/t|,0.18846014453071327,0.07692250797171969,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.45,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c3,16,3,21,No_bathrooms,bathrooms,A_structural,level,count,0.09,,1.97,,†,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5539",semi_elasticity,9.0,4.568527918781726,100*b/1 (per unit count),|b/t|,0.15249756513080967,0.07740993153848208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.97,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c4,16,4,21,No_bathrooms,bathrooms,A_structural,level,count,0.1,,2.21,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5284",semi_elasticity,10.0,4.524886877828055,100*b/1 (per unit count),|b/t|,0.17056404630215613,0.0771783014941883,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.21,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c5,16,5,21,No_bathrooms,bathrooms,A_structural,level,count,0.13,,2.37,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5185",semi_elasticity,13.0,5.485232067510548,100*b/1 (per unit count),|b/t|,0.18251467764361257,0.0770104125078534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.37,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c6,16,6,21,No_bathrooms,bathrooms,A_structural,level,count,0.15,,3.27,,**,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5133",semi_elasticity,15.0,4.587155963302751,100*b/1 (per unit count),|b/t|,0.24811711316950952,0.07587679301819863,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.27,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c7,16,7,21,No_bathrooms,bathrooms,A_structural,level,count,0.14,,2.09,,*,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5152",semi_elasticity,14.000000000000002,6.6985645933014375,100*b/1 (per unit count),|b/t|,0.1615511088030177,0.07729718124546302,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.09,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c8,16,8,21,No_bathrooms,bathrooms,A_structural,level,count,0.07,,1.08,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5028",semi_elasticity,7.000000000000001,6.481481481481481,100*b/1 (per unit count),|b/t|,0.08429107995739295,0.07804729625684532,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.08,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c9,16,9,21,No_bathrooms,bathrooms,A_structural,level,count,0.11,,1.2,,,,,high,Number of bathrooms,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5006",semi_elasticity,11.0,9.166666666666668,100*b/1 (per unit count),|b/t|,0.09357880867084666,0.07798234055903888,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c1,16,1,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.12,,-2.09,,*,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5574",semi_elasticity,-12.0,5.741626794258373,100*b/1 (per unit count),|b/t|,-0.1615511088030177,0.07729718124546302,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.09,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c2,16,2,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.03,,-0.86,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5769",semi_elasticity,-3.0,3.488372093023256,100*b/1 (per unit count),|b/t|,-0.06720809547985139,0.07814894823238534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.86,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c3,16,3,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.05,,-1.22,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5539",semi_elasticity,-5.0,4.0983606557377055,100*b/1 (per unit count),|b/t|,-0.09512445741279114,0.07797086673179603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.22,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c4,16,4,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.03,,-0.71,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5284",semi_elasticity,-3.0,4.225352112676056,100*b/1 (per unit count),|b/t|,-0.05552569778801017,0.07820520815212702,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.71,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c5,16,5,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.08,,-1.6,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5185",semi_elasticity,-8.0,5.0,100*b/1 (per unit count),|b/t|,-0.12434899333339904,0.0777181208333744,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c6,16,6,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.02,,-0.55,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5133",semi_elasticity,-2.0,3.6363636363636362,100*b/1 (per unit count),|b/t|,-0.04303940638866546,0.07825346616120993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.55,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c7,16,7,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.01,,-0.09,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5152",semi_elasticity,-1.0,11.111111111111112,100*b/1 (per unit count),|b/t|,-0.007049168904005755,0.07832409893339728,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.09,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c8,16,8,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.04,,-0.69,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5028",semi_elasticity,-4.0,5.797101449275363,100*b/1 (per unit count),|b/t|,-0.053966214667216864,0.07821190531480704,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.69,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c9,16,9,21,No_balconies,terrace_balcony,C_exterior,level,count,-0.06,,-0.68,,,,,high,Number of balconies,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5006",semi_elasticity,-6.0,8.823529411764705,100*b/1 (per unit count),|b/t|,-0.05318632428208009,0.07821518276776482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.68,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c1,16,1,21,No_parking,parking,A_structural,level,count,0.15,,1.58,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5574",semi_elasticity,15.0,9.493670886075948,100*b/1 (per unit count),|b/t|,0.12281822353975222,0.0777330528732609,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.58,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c2,16,2,21,No_parking,parking,A_structural,level,count,0.1,,1.49,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5769",semi_elasticity,10.0,6.7114093959731544,100*b/1 (per unit count),|b/t|,0.11591905394981178,0.07779802278510858,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.49,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c3,16,3,21,No_parking,parking,A_structural,level,count,0.06,,0.84,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5539",semi_elasticity,6.0,7.142857142857142,100*b/1 (per unit count),|b/t|,0.06565193307519313,0.07815706318475373,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.84,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c4,16,4,21,No_parking,parking,A_structural,level,count,0.23,,3.48,,***,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5284",semi_elasticity,23.0,6.609195402298851,100*b/1 (per unit count),|b/t|,0.2629803347816215,0.07556906171885676,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.48,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c5,16,5,21,No_parking,parking,A_structural,level,count,0.22,,2.73,,**,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5185",semi_elasticity,22.0,8.058608058608058,100*b/1 (per unit count),|b/t|,0.20910308960733248,0.0765945383177042,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.73,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c6,16,6,21,No_parking,parking,A_structural,level,count,0.21,,2.99,,**,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5133",semi_elasticity,21.0,7.023411371237458,100*b/1 (per unit count),|b/t|,0.22802507163322808,0.07626256576362142,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.99,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c7,16,7,21,No_parking,parking,A_structural,level,count,0.26,,2.68,,**,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5152",semi_elasticity,26.0,9.701492537313433,100*b/1 (per unit count),|b/t|,0.20543643595198066,0.07665538654924652,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.68,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c8,16,8,21,No_parking,parking,A_structural,level,count,0.17,,1.73,,†,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5028",semi_elasticity,17.0,9.826589595375722,100*b/1 (per unit count),|b/t|,0.13427691256247734,0.07761671246385972,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.73,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c9,16,9,21,No_parking,parking,A_structural,level,count,0.06,,0.42,,,,,high,Number of parking spaces related to the apartment,ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5006",semi_elasticity,6.0,14.285714285714285,100*b/1 (per unit count),|b/t|,0.032879152659595456,0.07828369680856062,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.42,163.0,count,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c1,16,1,21,Structure,roof_materials,A_structural,binary,binary,0.11,,1.1,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.1; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5574",pct_premium,11.071061035570517,11.16278070458871,100*(exp(b - se^2/2) - 1),|b/t|,0.08584062768258548,0.07803693425689588,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c2,16,2,21,Structure,roof_materials,A_structural,binary,binary,0.21,,2.92,,**,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.2; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5769",pct_premium,23.04917846944616,8.872342212017672,100*(exp(b - se^2/2) - 1),|b/t|,0.2229550763794247,0.07635447821213175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.92,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c3,16,3,21,Structure,roof_materials,A_structural,binary,binary,0.23,,3.17,,**,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.3; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5539",pct_premium,25.529156851494417,9.131798179299052,100*(exp(b - se^2/2) - 1),|b/t|,0.2409765823537718,0.07601784932295641,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.17,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c4,16,4,21,Structure,roof_materials,A_structural,binary,binary,0.17,,2.44,,*,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.4; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5284",pct_premium,18.243148283466624,8.258271505100907,100*(exp(b - se^2/2) - 1),|b/t|,0.18771807904379892,0.0769336389523766,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.44,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c5,16,5,21,Structure,roof_materials,A_structural,binary,binary,0.05,,0.56,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.5; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5185",pct_premium,4.708910215505191,9.38634907478593,100*(exp(b - se^2/2) - 1),|b/t|,0.04382045179337803,0.07825080677388933,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.56,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c6,16,6,21,Structure,roof_materials,A_structural,binary,binary,0.06,,0.83,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.6; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5133",pct_premium,5.906573660360759,7.675926842496575,100*(exp(b - se^2/2) - 1),|b/t|,0.06487367148697346,0.07816104998430536,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.83,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c7,16,7,21,Structure,roof_materials,A_structural,binary,binary,0.04,,0.37,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.7; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5152",pct_premium,3.474634406287591,11.252008369647442,100*(exp(b - se^2/2) - 1),|b/t|,0.028968474220789676,0.07829317356970182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.37,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c8,16,8,21,Structure,roof_materials,A_structural,binary,binary,0.03,,0.31,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.8; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5028",pct_premium,2.5640584356238394,9.972140651163068,100*(exp(b - se^2/2) - 1),|b/t|,0.024273919409963114,0.07830296583859069,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.31,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819,2799534456858542797f23b6cf17bd1f12439819:T16-c9,16,9,21,Structure,roof_materials,A_structural,binary,binary,0.04,,0.24,,,,,high,"1 = concrete structure, 0 = brick",ln(Price): log sale price of the apartment,log,quantile,173.0,,t,"Quantile regression at tau = 0.9; all structural attributes with constructed surface + square, Duration control; pseudo-R2 = 0.5006",pct_premium,2.6454992692278356,17.346846236539808,100*(exp(b - se^2/2) - 1),|b/t|,0.018794930270996775,0.07831220946248657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.24,163.0,binary,,2019.0,Romania,Europe,High income,2014.0,2018.0,condo_apartment,transaction,journal,False,False,unknown,,2016.0,quantile,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c1,4,Full Model,9,LnLANDSIZE,lot_size,A_structural,log,m2,0.553,,7.84,,***,,,medium,"Plot area; Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.766,t,All variables,elasticity,0.553,0.0705357142857143,b (log-log),|b/t|,0.4515409907243725,0.05759451412300669,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.84,240.0,m2,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c2,4,Fit Model,9,LnLANDSIZE,lot_size,A_structural,log,m2,0.528,,7.658,,***,,,medium,"Plot area; Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.763,t,Insignificant variables dropped,elasticity,0.528,0.06894750587620789,b (log-log),|b/t|,0.4431367458515154,0.057865858690456434,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.658,240.0,m2,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c1,4,Full Model,9,LnBUILDSIZE,living_area,A_structural,log,m2,0.113,,1.38,,,,,medium,"Building area; Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.766,t,All variables,elasticity,0.113,0.0818840579710145,b (log-log),|b/t|,0.08872728702514433,0.06429513552546691,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.38,240.0,m2,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c2,4,Fit Model,9,LnBUILDSIZE,living_area,A_structural,log,m2,0.164,,2.093,,**,,,medium,"Building area; Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.763,t,Insignificant variables dropped,elasticity,0.164,0.07835642618251315,b (log-log),|b/t|,0.13388620184149586,0.06396856275274526,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.093,240.0,m2,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c1,4,Full Model,9,LnNUMROOM,bedrooms,A_structural,log,count,0.094,,1.179,,,,,medium,"Number of rooms (all rooms); Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.766,t,All variables,elasticity,0.094,0.07972858354537743,b (log-log),|b/t|,0.07588468415273403,0.06436359979027483,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.179,240.0,count,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c1,4,Full Model,9,WSTRUCTDUM,roof_materials,A_structural,binary,binary,-0.067,,-1.088,,,,,medium,"Wall structure dummy; Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.766,t,All variables,pct_premium,-6.657634460870154,5.759014567055517,100*(exp(b - se^2/2) - 1),|b/t|,-0.07005753929300708,0.06439112067371973,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.088,240.0,binary,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c1,4,Full Model,9,LnDISSCHOOL,school_distance,D_location,log,m,-0.071,,-1.809,,*,,,medium,"Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.766,t,All variables,elasticity,-0.071,0.0392482034273079,b (log-log),|b/t|,-0.11598239557868535,0.0641140937416724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.809,240.0,m,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c2,4,Fit Model,9,LnDISSCHOOL,school_distance,D_location,log,m,-0.068,,-1.91,,**,,,medium,"Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.763,t,Insignificant variables dropped,elasticity,-0.068,0.0356020942408377,b (log-log),|b/t|,-0.1223634892875675,0.06406465407726047,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.91,240.0,m,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c1,4,Full Model,9,LnDISHPITAL,hospital_distance,D_location,log,m,-0.085,,-1.98,,**,,,medium,"Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.766,t,All variables,elasticity,-0.085,0.042929292929292935,b (log-log),|b/t|,-0.12677719205089263,0.0640288848741882,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.98,240.0,m,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c2,4,Fit Model,9,LnDISHPITAL,hospital_distance,D_location,log,m,-0.075,,-1.885,,*,,,medium,"Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.763,t,Insignificant variables dropped,elasticity,-0.075,0.03978779840848806,b (log-log),|b/t|,-0.12078539175196361,0.06407713090289847,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.885,240.0,m,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c1,4,Full Model,9,LnDISSPMARKET,commercial_distance,D_location,log,m,0.023,,0.56,,,,,medium,"Distance from supermarket; Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.766,t,All variables,elasticity,0.023,0.041071428571428564,b (log-log),|b/t|,0.036124251091907554,0.0645075912355492,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.56,240.0,m,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c1,4,Full Model,9,LnDISREST,neighbourhood_amenities,F_neighbourhood,log,m,-0.023,,-0.652,,,,,medium,"Distance from restaurant; Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.766,t,All variables,elasticity,-0.023,0.0352760736196319,b (log-log),|b/t|,-0.04204919533573716,0.06449263088303245,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.652,240.0,m,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c1,4,Full Model,9,LnDISCITY,cbd_distance,D_location,log,m,0.054,,1.274,,,,,medium,"Distance from city; Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.766,t,All variables,elasticity,0.054,0.0423861852433281,b (log-log),|b/t|,0.08195967424153908,0.0643325543497167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.274,240.0,m,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c2,4,Fit Model,9,LnDISCITY,cbd_distance,D_location,log,m,0.064,,1.538,,,,,medium,"Distance from city; Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.763,t,Insignificant variables dropped,elasticity,0.064,0.04161248374512354,b (log-log),|b/t|,0.09879181991336715,0.06423395312962754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.538,240.0,m,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c1,4,Full Model,9,LnDISMSTREET,highway_distance,D_location,log,m,0.024,,1.03,,,,,medium,"Distance from main street; Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.766,t,All variables,elasticity,0.024,0.02330097087378641,b (log-log),|b/t|,0.06633975111753143,0.06440752535682664,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.03,240.0,m,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c1,4,Full Model,9,GARDENDUM,garden,C_exterior,binary,binary,0.129,,1.673,,*,,,medium,"Dummy for close to garden; Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.766,t,All variables,pct_premium,13.431308445239454,8.77238649237175,100*(exp(b - se^2/2) - 1),|b/t|,0.10736742996573884,0.06417658694903695,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.673,240.0,binary,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c1,4,Full Model,9,LnCO,air_pollution,E_environment,log,ug/m3,-1.305,,-13.115,,***,,,medium,"Carbon monoxide concentration (2010 ambient monitoring); Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.766,t,All variables,elasticity,-1.305,0.0995043842927945,b (log-log),|b/t|,-0.6461271453261794,0.049266271088538274,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.115,240.0,ug/m3,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1,281b355bd08bd1b8b228829d9c97b819d0d2a4d1:T4-c2,4,Fit Model,9,LnCO,air_pollution,E_environment,log,ug/m3,-1.375,,-15.066,,***,,,medium,"Carbon monoxide concentration (2010 ambient monitoring); Parentheses contain t-statistics (not stated explicitly; inferred from magnitudes); star legend not printed, conventional ***1% **5% *10% assumed","ln PPRICE (house sales price, Rupiah)",log,OLS,250.0,0.763,t,Insignificant variables dropped,elasticity,-1.375,0.0912651002256737,b (log-log),|b/t|,-0.6971830133824944,0.046275256430538585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.066,240.0,ug/m3,,2013.0,Indonesia,Asia,Upper middle income,,,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
28afe169f4e2851e590b8152147dbd5bb4ee90f0,28afe169f4e2851e590b8152147dbd5bb4ee90f0,28afe169f4e2851e590b8152147dbd5bb4ee90f0:T2-c1,2,1,27,Coastal city,waterfront,C_exterior,binary,binary,0.178,0.04,,,***,,,high,city-level coastal location dummy (not property frontage); city-level amenity; SE clustered by city; stars * 10% ** 5% *** 1%,"ln(housing price), self-reported purchase cost of owner-occupied unit (CNY)",log,OLS,421660.0,0.734,se,owner-occupied units; housing attributes and 432 attribute-group FE included (not reported); SE clustered by city,pct_premium,19.38698432199777,4.779301284939203,100*(exp(b - se^2/2) - 1),reported,0.00685288999963231,0.0015399752808162497,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.449999999999999,421650.0,binary,,2021.0,China,Asia,Upper middle income,2005.0,2005.0,mixed,transaction,working_paper,False,False,clustered,,2005.0,ols,other,True,True,False
28afe169f4e2851e590b8152147dbd5bb4ee90f0,28afe169f4e2851e590b8152147dbd5bb4ee90f0,28afe169f4e2851e590b8152147dbd5bb4ee90f0:T2-c2,2,2,27,Coastal city,waterfront,C_exterior,binary,binary,0.019,0.05,,,,,,high,city-level coastal location dummy (not property frontage); city-level amenity; SE clustered by city; stars * 10% ** 5% *** 1%,ln(monthly housing rent) (CNY),log,OLS,227594.0,0.542,se,rental units; housing attributes and group FE included (not reported); SE clustered by city,pct_premium,1.7908467460638011,5.095908243087041,100*(exp(b - se^2/2) - 1),reported,0.0007965491814987221,0.0020961820565755847,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.37999999999999995,227584.0,binary,,2021.0,China,Asia,Upper middle income,2005.0,2005.0,mixed,transaction,working_paper,False,False,clustered,,2005.0,ols,other,True,True,True
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c1,4,1 (Benchmark),16,Age,age,A_structural,level,years,-0.012,0.0004,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.64,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,-1.2,0.04,100*b/1 (per year),reported,-0.17643396214858012,0.005881132071619336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.0,28012.0,years,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c1,4,1 (Benchmark),16,SQFT,living_area,A_structural,level,sqft,0.001,1e-05,,,***,,,high,Living area in square feet; SQFT printed as 0.001 (rounded),"ln(Price/100), sale price USD",log,OLS,28022.0,0.64,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,1.0763910416709723,0.010763910416709722,100*b/0.092903 (X per sqft->m2),reported,0.5129081969303817,0.0051290819693038175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),100.0,28012.0,sqft,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c1,4,1 (Benchmark),16,Beds,bedrooms,A_structural,level,count,-0.043,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.64,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,-4.3,0.5,100*b/1 (per unit count),reported,-0.05131612032022764,0.005966990734910192,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.6,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c1,4,1 (Benchmark),16,Baths,bathrooms,A_structural,level,count,0.069,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.64,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,6.9,0.5,100*b/1 (per unit count),reported,0.08217424913693558,0.005954655734560548,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.8,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c1,4,1 (Benchmark),16,Dist to CBD (km),cbd_distance,D_location,level,km,-0.0007,0.0004,,,*,,,high,Distance to nearest CBD (downtown Oklahoma City or Tulsa),"ln(Price/100), sale price USD",log,OLS,28022.0,0.64,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,-0.06999999999999999,0.04,100*b/1 (X per km->km),reported,-0.010455438476888016,0.0059745362725074375,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.75,28012.0,km,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c2,4,2 (No counts),16,Age,age,A_structural,level,years,-0.012,0.0004,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,-1.2,0.04,100*b/1 (per year),reported,-0.17643396214858012,0.005881132071619336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.0,28012.0,years,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c2,4,2 (No counts),16,SQFT,living_area,A_structural,level,sqft,0.001,1e-05,,,***,,,high,Living area in square feet; SQFT printed as 0.001 (rounded),"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,1.0763910416709723,0.010763910416709722,100*b/0.092903 (X per sqft->m2),reported,0.5129081969303817,0.0051290819693038175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),100.0,28012.0,sqft,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c2,4,2 (No counts),16,Beds,bedrooms,A_structural,level,count,-0.043,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,-4.3,0.5,100*b/1 (per unit count),reported,-0.05131612032022764,0.005966990734910192,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.6,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c2,4,2 (No counts),16,Baths,bathrooms,A_structural,level,count,0.069,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,6.9,0.5,100*b/1 (per unit count),reported,0.08217424913693558,0.005954655734560548,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.8,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c2,4,2 (No counts),16,Dist to CBD (km),cbd_distance,D_location,level,km,-0.001,0.0004,,,***,,,high,Distance to nearest CBD (downtown Oklahoma City or Tulsa),"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,-0.1,0.04,100*b/1 (X per km->km),reported,-0.014935491039694328,0.005974196415877732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5,28012.0,km,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c3,4,3 (No counts & minDist2),16,Age,age,A_structural,level,years,-0.012,0.0004,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,-1.2,0.04,100*b/1 (per year),reported,-0.17643396214858012,0.005881132071619336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.0,28012.0,years,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c3,4,3 (No counts & minDist2),16,SQFT,living_area,A_structural,level,sqft,0.001,1e-05,,,***,,,high,Living area in square feet; SQFT printed as 0.001 (rounded),"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,1.0763910416709723,0.010763910416709722,100*b/0.092903 (X per sqft->m2),reported,0.5129081969303817,0.0051290819693038175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),100.0,28012.0,sqft,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c3,4,3 (No counts & minDist2),16,Beds,bedrooms,A_structural,level,count,-0.043,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,-4.3,0.5,100*b/1 (per unit count),reported,-0.05131612032022764,0.005966990734910192,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.6,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c3,4,3 (No counts & minDist2),16,Baths,bathrooms,A_structural,level,count,0.069,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,6.9,0.5,100*b/1 (per unit count),reported,0.08217424913693558,0.005954655734560548,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.8,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c3,4,3 (No counts & minDist2),16,Dist to CBD (km),cbd_distance,D_location,level,km,-0.001,0.0004,,,***,,,high,Distance to nearest CBD (downtown Oklahoma City or Tulsa),"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,-0.1,0.04,100*b/1 (X per km->km),reported,-0.014935491039694328,0.005974196415877732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5,28012.0,km,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c4,4,4 (No counts & Interaction),16,Age,age,A_structural,level,years,-0.012,0.0004,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.64,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,-1.2,0.04,100*b/1 (per year),reported,-0.17643396214858012,0.005881132071619336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.0,28012.0,years,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c4,4,4 (No counts & Interaction),16,SQFT,living_area,A_structural,level,sqft,0.001,1e-05,,,***,,,high,Living area in square feet; SQFT printed as 0.001 (rounded),"ln(Price/100), sale price USD",log,OLS,28022.0,0.64,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,1.0763910416709723,0.010763910416709722,100*b/0.092903 (X per sqft->m2),reported,0.5129081969303817,0.0051290819693038175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),100.0,28012.0,sqft,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c4,4,4 (No counts & Interaction),16,Beds,bedrooms,A_structural,level,count,-0.043,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.64,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,-4.3,0.5,100*b/1 (per unit count),reported,-0.05131612032022764,0.005966990734910192,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.6,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c4,4,4 (No counts & Interaction),16,Baths,bathrooms,A_structural,level,count,0.068,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.64,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,6.800000000000001,0.5,100*b/1 (per unit count),reported,0.08099118704793636,0.005955234341760025,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.600000000000001,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T4-c4,4,4 (No counts & Interaction),16,Dist to CBD (km),cbd_distance,D_location,level,km,-0.001,0.0004,,,***,,,high,Distance to nearest CBD (downtown Oklahoma City or Tulsa),"ln(Price/100), sale price USD",log,OLS,28022.0,0.64,se,"Pooled 4-county benchmark sample (Comanche, Oklahoma, Wagoner, Washington), sales after July 2020-2023; year and county dummies not extracted",semi_elasticity,-0.1,0.04,100*b/1 (X per km->km),reported,-0.014935491039694328,0.005974196415877732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5,28012.0,km,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c1,5,1 (All),19,Age,age,A_structural,level,years,-0.013,0.0004,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,-1.3,0.04,100*b/1 (per year),reported,-0.1906223931913883,0.00586530440588887,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-32.5,28012.0,years,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c1,5,1 (All),19,SQFT,living_area,A_structural,level,sqft,0.0006,1e-05,,,***,,,high,Living area in square feet,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,0.6458346250025833,0.010763910416709722,100*b/0.092903 (X per sqft->m2),reported,0.337462301239245,0.00562437168732075,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),59.99999999999999,28012.0,sqft,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c1,5,1 (All),19,Beds,bedrooms,A_structural,level,count,-0.043,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,-4.3,0.5,100*b/1 (per unit count),reported,-0.05131612032022764,0.005966990734910192,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.6,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c1,5,1 (All),19,Baths,bathrooms,A_structural,level,count,0.07,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,7.000000000000001,0.5,100*b/1 (per unit count),reported,0.08335696394016968,0.005954068852869262,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.000000000000002,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c1,5,1 (All),19,Dist to CBD (km),cbd_distance,D_location,level,km,-0.0002,0.0004,,,,,,high,Distance to nearest CBD (downtown Oklahoma City or Tulsa),"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,-0.02,0.04,100*b/1 (X per km->km),reported,-0.002987418097087927,0.005974836194175853,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5,28012.0,km,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c2,5,2 (Count500),19,Age,age,A_structural,level,years,-0.012,0.0004,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,-1.2,0.04,100*b/1 (per year),reported,-0.17643396214858012,0.005881132071619336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.0,28012.0,years,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c2,5,2 (Count500),19,SQFT,living_area,A_structural,level,sqft,0.0006,1e-05,,,***,,,high,Living area in square feet,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,0.6458346250025833,0.010763910416709722,100*b/0.092903 (X per sqft->m2),reported,0.337462301239245,0.00562437168732075,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),59.99999999999999,28012.0,sqft,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c2,5,2 (Count500),19,Beds,bedrooms,A_structural,level,count,-0.043,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,-4.3,0.5,100*b/1 (per unit count),reported,-0.05131612032022764,0.005966990734910192,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.6,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c2,5,2 (Count500),19,Baths,bathrooms,A_structural,level,count,0.07,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,7.000000000000001,0.5,100*b/1 (per unit count),reported,0.08335696394016968,0.005954068852869262,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.000000000000002,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c2,5,2 (Count500),19,Dist to CBD (km),cbd_distance,D_location,level,km,-0.001,0.0004,,,*,,,high,Distance to nearest CBD (downtown Oklahoma City or Tulsa),"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,-0.1,0.04,100*b/1 (X per km->km),reported,-0.014935491039694328,0.005974196415877732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5,28012.0,km,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c3,5,3 (Count1000),19,Age,age,A_structural,level,years,-0.012,0.0004,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,-1.2,0.04,100*b/1 (per year),reported,-0.17643396214858012,0.005881132071619336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.0,28012.0,years,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c3,5,3 (Count1000),19,SQFT,living_area,A_structural,level,sqft,0.0006,1e-05,,,***,,,high,Living area in square feet,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,0.6458346250025833,0.010763910416709722,100*b/0.092903 (X per sqft->m2),reported,0.337462301239245,0.00562437168732075,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),59.99999999999999,28012.0,sqft,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c3,5,3 (Count1000),19,Beds,bedrooms,A_structural,level,count,-0.043,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,-4.3,0.5,100*b/1 (per unit count),reported,-0.05131612032022764,0.005966990734910192,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.6,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c3,5,3 (Count1000),19,Baths,bathrooms,A_structural,level,count,0.07,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,7.000000000000001,0.5,100*b/1 (per unit count),reported,0.08335696394016968,0.005954068852869262,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.000000000000002,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c3,5,3 (Count1000),19,Dist to CBD (km),cbd_distance,D_location,level,km,-0.001,0.0004,,,*,,,high,Distance to nearest CBD (downtown Oklahoma City or Tulsa),"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,-0.1,0.04,100*b/1 (X per km->km),reported,-0.014935491039694328,0.005974196415877732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5,28012.0,km,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c4,5,4 (Count2000),19,Age,age,A_structural,level,years,-0.013,0.0004,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,-1.3,0.04,100*b/1 (per year),reported,-0.1906223931913883,0.00586530440588887,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-32.5,28012.0,years,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c4,5,4 (Count2000),19,SQFT,living_area,A_structural,level,sqft,0.0006,1e-05,,,***,,,high,Living area in square feet,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,0.6458346250025833,0.010763910416709722,100*b/0.092903 (X per sqft->m2),reported,0.337462301239245,0.00562437168732075,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),59.99999999999999,28012.0,sqft,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c4,5,4 (Count2000),19,Beds,bedrooms,A_structural,level,count,-0.043,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,-4.3,0.5,100*b/1 (per unit count),reported,-0.05131612032022764,0.005966990734910192,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.6,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c4,5,4 (Count2000),19,Baths,bathrooms,A_structural,level,count,0.07,0.005,,,***,,,high,,"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,7.000000000000001,0.5,100*b/1 (per unit count),reported,0.08335696394016968,0.005954068852869262,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.000000000000002,28012.0,count,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c,28fd8140cfc928298ce0dcc59bc4a1264ace9c6c:T5-c4,5,4 (Count2000),19,Dist to CBD (km),cbd_distance,D_location,level,km,-0.0002,0.0004,,,,,,high,Distance to nearest CBD (downtown Oklahoma City or Tulsa),"ln(Price/100), sale price USD",log,OLS,28022.0,0.639,se,Pooled 4-county sample without minDist; count variables jointly (col 1) or one at a time (cols 2-4); SQFT2 printed as -0.0000000*** (0.00000) and not extracted,semi_elasticity,-0.02,0.04,100*b/1 (X per km->km),reported,-0.002987418097087927,0.005974836194175853,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5,28012.0,km,,2026.0,United States,North America,High income,2020.0,2023.0,single_family,transaction,journal,True,True,unknown,cross-validation selection of minDist threshold (Fitzpatrick and Parmeter 2021) for county models,2021.5,ols,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ci,4,i,12,SIZE,living_area,A_structural,log,m2,0.787,,68.211,,***,,,high,"Living area m2, logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.449,t,"Base: station distance + passengers; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.787,0.011537728518860596,b (log-log),|b/t|,0.4505961415028659,0.006605916076627902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),68.211,18263.0,m2,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cii,4,ii,12,SIZE,living_area,A_structural,log,m2,0.787,,67.918,,***,,,high,"Living area m2, logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.479,t,"+ CLOSENESS (gravity); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.787,0.011587502576636531,b (log-log),|b/t|,0.44905157473693247,0.00661167252770889,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),67.918,18263.0,m2,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ciii,4,iii,12,SIZE,living_area,A_structural,log,m2,0.789,,68.015,,***,,,high,"Living area m2, logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.509,t,"+ DEGREE; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.789,0.011600382268617216,b (log-log),|b/t|,0.44956336286735926,0.006609767887485986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),68.015,18263.0,m2,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-civ,4,iv,12,SIZE,living_area,A_structural,log,m2,0.789,,68.157,,***,,,high,"Living area m2, logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.51,t,"+ BETWEENNESS (Oresund trains); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.789,0.011576213741802018,b (log-log),|b/t|,0.45031178069910316,0.006606977723478193,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),68.157,18263.0,m2,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cv,4,v,12,SIZE,living_area,A_structural,log,m2,0.789,,68.033,,***,,,high,"Living area m2, logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"+ BETWEENNESS (Pagatag trains), without Oresund; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.789,0.011597313068657857,b (log-log),|b/t|,0.4496582852007423,0.006609414331291319,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),68.033,18263.0,m2,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cvi,4,vi,12,SIZE,living_area,A_structural,log,m2,0.789,,68.16,,***,,,high,"Living area m2, logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"All network measures; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.789,0.011575704225352115,b (log-log),|b/t|,0.45032758211801543,0.006606918751731447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),68.16,18263.0,m2,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ci,4,i,12,AGE,age,A_structural,log,years,-0.021,,-5.367,,***,,,high,"Age of building (years), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.449,t,"Base: station distance + passengers; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,-0.021,0.003912800447177194,b (log-log),|b/t|,-0.03968289222583491,0.0073938684974538685,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.367,18263.0,years,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cii,4,ii,12,AGE,age,A_structural,log,years,-0.021,,-5.353,,***,,,high,"Age of building (years), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.479,t,"+ CLOSENESS (gravity); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,-0.021,0.003923033812815244,b (log-log),|b/t|,-0.039579540437662125,0.0073938988301255615,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.353,18263.0,years,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ciii,4,iii,12,AGE,age,A_structural,log,years,-0.021,,-5.484,,***,,,high,"Age of building (years), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.509,t,"+ DEGREE; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,-0.021,0.003829321663019694,b (log-log),|b/t|,-0.04054656777025603,0.0073936119201779785,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.484,18263.0,years,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-civ,4,iv,12,AGE,age,A_structural,log,years,-0.021,,-5.467,,***,,,high,"Age of building (years), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.51,t,"+ BETWEENNESS (Oresund trains); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,-0.021,0.0038412291933418697,b (log-log),|b/t|,-0.04042108204902615,0.007393649542532678,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.467,18263.0,years,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cv,4,v,12,AGE,age,A_structural,log,years,-0.021,,-5.497,,***,,,high,"Age of building (years), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"+ BETWEENNESS (Pagatag trains), without Oresund; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,-0.021,0.0038202655994178645,b (log-log),|b/t|,-0.04064252614522423,0.00739358307171625,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.497,18263.0,years,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cvi,4,vi,12,AGE,age,A_structural,log,years,-0.021,,-5.488,,***,,,high,"Age of building (years), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"All network measures; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,-0.021,0.003826530612244898,b (log-log),|b/t|,-0.040576093543708995,0.007393603050967382,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.488,18263.0,years,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ci,4,i,12,BEACH,waterfront,C_exterior,binary,binary,0.413,,13.019,,***,,,high,"Beach-side property: within 150 m of waterfront. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.449,t,"Base: station distance + passengers; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",pct_premium,51.058475354699496,4.794419661346796,100*(exp(b - se^2/2) - 1),|b/t|,0.09589270555183466,0.00736559686241913,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.019,18263.0,binary,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cii,4,ii,12,BEACH,waterfront,C_exterior,binary,binary,0.413,,13.015,,***,,,high,"Beach-side property: within 150 m of waterfront. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.479,t,"+ CLOSENESS (gravity); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",pct_premium,51.05842862721195,4.7958931671973835,100*(exp(b - se^2/2) - 1),|b/t|,0.09586351395944923,0.007365617668801324,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.015,18263.0,binary,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ciii,4,iii,12,BEACH,waterfront,C_exterior,binary,binary,0.415,,12.998,,***,,,high,"Beach-side property: within 150 m of waterfront. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.509,t,"+ DEGREE; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",pct_premium,51.359906527091994,4.8350812231666405,100*(exp(b - se^2/2) - 1),|b/t|,0.09573944693324346,0.007365706026561277,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.998,18263.0,binary,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-civ,4,iv,12,BEACH,waterfront,C_exterior,binary,binary,0.415,,12.986,,***,,,high,"Beach-side property: within 150 m of waterfront. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.51,t,"+ BETWEENNESS (Oresund trains); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",pct_premium,51.35976388088266,4.839549186718004,100*(exp(b - se^2/2) - 1),|b/t|,0.0956518675220082,0.007365768329124302,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.986,18263.0,binary,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cv,4,v,12,BEACH,waterfront,C_exterior,binary,binary,0.415,,13.0,,***,,,high,"Beach-side property: within 150 m of waterfront. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"+ BETWEENNESS (Pagatag trains), without Oresund; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",pct_premium,51.35993026307639,4.834337364516923,100*(exp(b - se^2/2) - 1),|b/t|,0.09575404328567833,0.00736569563735987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,18263.0,binary,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cvi,4,vi,12,BEACH,waterfront,C_exterior,binary,binary,0.415,,12.988,,***,,,high,"Beach-side property: within 150 m of waterfront. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"All network measures; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",pct_premium,51.359787682701665,4.838803952781029,100*(exp(b - se^2/2) - 1),|b/t|,0.09566646424486233,0.007365757949250257,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.988,18263.0,binary,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ci,4,i,12,INC,income,F_neighbourhood,log,currency,0.532,,15.052,,***,,,high,"Average income in local small area (SEK 1,000), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.449,t,"Base: station distance + passengers; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.532,0.035344140313579596,b (log-log),|b/t|,0.11069573538134113,0.007354221059084582,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.052,18263.0,currency,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cii,4,ii,12,INC,income,F_neighbourhood,log,currency,0.512,,14.107,,***,,,high,"Average income in local small area (SEK 1,000), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.479,t,"+ CLOSENESS (gravity); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.512,0.03629403842064224,b (log-log),|b/t|,0.10382339005468508,0.007359707241418096,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.107,18263.0,currency,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ciii,4,iii,12,INC,income,F_neighbourhood,log,currency,0.525,,14.443,,***,,,high,"Average income in local small area (SEK 1,000), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.509,t,"+ DEGREE; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.525,0.03634978882503635,b (log-log),|b/t|,0.10626864684873813,0.007357795946045706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.443,18263.0,currency,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-civ,4,iv,12,INC,income,F_neighbourhood,log,currency,0.523,,14.466,,***,,,high,"Average income in local small area (SEK 1,000), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.51,t,"+ BETWEENNESS (Oresund trains); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.523,0.036153739803677594,b (log-log),|b/t|,0.1064359605288757,0.00735766352335654,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.466,18263.0,currency,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cv,4,v,12,INC,income,F_neighbourhood,log,currency,0.528,,14.482,,***,,,high,"Average income in local small area (SEK 1,000), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"+ BETWEENNESS (Pagatag trains), without Oresund; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.528,0.03645905261704185,b (log-log),|b/t|,0.1065523473229278,0.007357571283174134,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.482,18263.0,currency,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cvi,4,vi,12,INC,income,F_neighbourhood,log,currency,0.526,,4.534,,***,,,high,"Average income in local small area (SEK 1,000), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"All network measures; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.526,0.11601235112483459,b (log-log),|b/t|,0.03353136004331495,0.007395535960148864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.534,18263.0,currency,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ci,4,i,12,POP,density,F_neighbourhood,log,count,0.043,,5.114,,***,,,high,"Population of local small area (1,000 inh), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.449,t,"Base: station distance + passengers; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.043,0.008408290965975753,b (log-log),|b/t|,0.03781498454219757,0.007394404486155175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.114,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cii,4,ii,12,POP,density,F_neighbourhood,log,count,0.041,,4.783,,***,,,high,"Population of local small area (1,000 inh), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.479,t,"+ CLOSENESS (gravity); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.041,0.008572025925151577,b (log-log),|b/t|,0.03537060454592268,0.007395066808681303,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.783,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ciii,4,iii,12,POP,density,F_neighbourhood,log,count,0.042,,4.932,,***,,,high,"Population of local small area (1,000 inh), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.509,t,"+ DEGREE; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.042,0.00851581508515815,b (log-log),|b/t|,0.036471025980874185,0.007394774124264839,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.932,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-civ,4,iv,12,POP,density,F_neighbourhood,log,count,0.042,,4.938,,***,,,high,"Population of local small area (1,000 inh), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.51,t,"+ BETWEENNESS (Oresund trains); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.042,0.008505467800729041,b (log-log),|b/t|,0.03651533550170574,0.007394762151013719,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.938,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cv,4,v,12,POP,density,F_neighbourhood,log,count,0.043,,4.955,,***,,,high,"Population of local small area (1,000 inh), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"+ BETWEENNESS (Pagatag trains), without Oresund; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.043,0.008678102926337033,b (log-log),|b/t|,0.03664087797366679,0.00739472814806595,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.955,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cvi,4,vi,12,POP,density,F_neighbourhood,log,count,0.042,,4.973,,***,,,high,"Population of local small area (1,000 inh), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"All network measures; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.042,0.008445606273878947,b (log-log),|b/t|,0.036773803405936493,0.007394692018084958,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.973,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ci,4,i,12,LOC_LABOR,employment_access,D_location,log,count,0.062,,5.739,,***,,,high,"Number of jobs in home municipality (1,000), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.449,t,"Base: station distance + passengers; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.062,0.010803275832026485,b (log-log),|b/t|,0.042428620061168085,0.007393033640210504,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.739,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cii,4,ii,12,LOC_LABOR,employment_access,D_location,log,count,0.055,,5.187,,***,,,high,"Number of jobs in home municipality (1,000), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.479,t,"+ CLOSENESS (gravity); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.055,0.010603431656063235,b (log-log),|b/t|,0.03835398760051412,0.00739425247744633,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.187,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ciii,4,iii,12,LOC_LABOR,employment_access,D_location,log,count,0.06,,5.687,,***,,,high,"Number of jobs in home municipality (1,000), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.509,t,"+ DEGREE; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.06,0.010550378055213644,b (log-log),|b/t|,0.04204486501111937,0.007393153685795563,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.687,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-civ,4,iv,12,LOC_LABOR,employment_access,D_location,log,count,0.061,,5.686,,***,,,high,"Number of jobs in home municipality (1,000), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.51,t,"+ BETWEENNESS (Oresund trains); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.061,0.010728104115371086,b (log-log),|b/t|,0.04203748492339296,0.0073931559837131485,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.686,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cv,4,v,12,LOC_LABOR,employment_access,D_location,log,count,0.061,,5.758,,***,,,high,"Number of jobs in home municipality (1,000), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"+ BETWEENNESS (Pagatag trains), without Oresund; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.061,0.010593956234803751,b (log-log),|b/t|,0.0425688335773428,0.007392989506311706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.758,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cvi,4,vi,12,LOC_LABOR,employment_access,D_location,log,count,0.062,,5.732,,***,,,high,"Number of jobs in home municipality (1,000), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"All network measures; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.062,0.010816468946266573,b (log-log),|b/t|,0.04237696181755689,0.007393049863495618,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.732,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ci,4,i,12,STATION_DIST,transit_distance,D_location,log,km,-0.016,,-2.431,,**,,,high,"Road-network travel distance to closest train station (km), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.449,t,"Base: station distance + passengers; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,-0.016,0.00658165364047717,b (log-log),|b/t|,-0.01798575377139862,0.007398500111640731,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.431,18263.0,km,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cii,4,ii,12,STATION_DIST,transit_distance,D_location,log,km,-0.013,,-2.118,,**,,,high,"Road-network travel distance to closest train station (km), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.479,t,"+ CLOSENESS (gravity); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,-0.013,0.006137865911237016,b (log-log),|b/t|,-0.01567063391501869,0.007398788439574451,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.118,18263.0,km,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ciii,4,iii,12,STATION_DIST,transit_distance,D_location,log,km,-0.013,,-2.124,,**,,,high,"Road-network travel distance to closest train station (km), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.509,t,"+ DEGREE; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,-0.013,0.006120527306967985,b (log-log),|b/t|,-0.015715015697832176,0.00739878328523172,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.124,18263.0,km,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-civ,4,iv,12,STATION_DIST,transit_distance,D_location,log,km,-0.013,,-2.076,,**,,,high,"Road-network travel distance to closest train station (km), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.51,t,"+ BETWEENNESS (Oresund trains); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,-0.013,0.006262042389210019,b (log-log),|b/t|,-0.015359958856520431,0.00739882411200406,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.076,18263.0,km,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cv,4,v,12,STATION_DIST,transit_distance,D_location,log,km,-0.013,,-2.121,,**,,,high,"Road-network travel distance to closest train station (km), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"+ BETWEENNESS (Pagatag trains), without Oresund; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,-0.013,0.006129184347006129,b (log-log),|b/t|,-0.015692824818019847,0.00739878586422435,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.121,18263.0,km,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cvi,4,vi,12,STATION_DIST,transit_distance,D_location,log,km,-0.013,,-2.082,,**,,,high,"Road-network travel distance to closest train station (km), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"All network measures; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,-0.013,0.006243996157540827,b (log-log),|b/t|,-0.015404341282200334,0.00739881905965434,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.082,18263.0,km,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cii,4,ii,12,CLOSENESS (Gravity),employment_access,D_location,log,count,0.187,,2.991,,***,,,high,"Gravity-form closeness centrality of closest station: rail-network accessibility to employment in other nodes (1,000 inh), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.479,t,"+ CLOSENESS (gravity); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.187,0.06252089602139753,b (log-log),|b/t|,0.022127075133898527,0.007397885367401713,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.991,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-ciii,4,iii,12,CLOSENESS (Gravity),employment_access,D_location,log,count,0.172,,2.733,,***,,,high,"Gravity-form closeness centrality of closest station: rail-network accessibility to employment in other nodes (1,000 inh), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.509,t,"+ DEGREE; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.172,0.06293450420783021,b (log-log),|b/t|,0.020219237814519488,0.00739818434486626,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.733,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-civ,4,iv,12,CLOSENESS (Gravity),employment_access,D_location,log,count,0.175,,2.855,,***,,,high,"Gravity-form closeness centrality of closest station: rail-network accessibility to employment in other nodes (1,000 inh), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.51,t,"+ BETWEENNESS (Oresund trains); spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.175,0.06129597197898423,b (log-log),|b/t|,0.021121422250686493,0.007398046322482134,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.855,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cv,4,v,12,CLOSENESS (Gravity),employment_access,D_location,log,count,0.184,,2.937,,***,,,high,"Gravity-form closeness centrality of closest station: rail-network accessibility to employment in other nodes (1,000 inh), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"+ BETWEENNESS (Pagatag trains), without Oresund; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.184,0.06264896152536602,b (log-log),|b/t|,0.02172777965281289,0.0073979501711994855,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.937,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65,290a4bf33ce230c96c2113bb929c287ce4514c65:T4-cvi,4,vi,12,CLOSENESS (Gravity),employment_access,D_location,log,count,0.181,,2.864,,***,,,high,"Gravity-form closeness centrality of closest station: rail-network accessibility to employment in other nodes (1,000 inh), logged. Z values in parentheses (recorded as t); *** p<0.01, ** p<0.05, * p<0.1; all continuous variables in natural logs; N=18,273.","ln PRICE (single-family house sale price, SEK)",log,spatial_error,18273.0,0.512,t,"All network measures; spatial error model, GMM (Kelejian-Prucha), pseudo R2 reported",elasticity,0.181,0.06319832402234637,b (log-log),|b/t|,0.02118797482367033,0.00739803590211953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.864,18263.0,count,,2021.0,Sweden,Europe,High income,2016.0,2016.0,single_family,transaction,journal,False,False,robust,,2016.0,spatial,journal,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,24,Ln(Urban distance),cbd_distance,D_location,log,"km (log Euclidean distance to centroid of nearest major urban centre; unit not printed, km implied by descriptives)",-0.0053,0.002,,,*,,,medium,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0053,0.002,b (log-log),reported,-0.021743218753978184,0.00820498820904837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.65,14847.0,km,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,24,Ln(Urban distance),cbd_distance,D_location,log,"km (log Euclidean distance to centroid of nearest major urban centre; unit not printed, km implied by descriptives)",-0.0055,0.002,,,*,,,medium,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0055,0.002,b (log-log),reported,-0.022563307447751178,0.00820483907190952,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.75,14847.0,km,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,24,Ln(Urban distance),cbd_distance,D_location,log,"km (log Euclidean distance to centroid of nearest major urban centre; unit not printed, km implied by descriptives)",-0.0058,0.002,,,*,,,medium,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0058,0.002,b (log-log),reported,-0.023793354574970293,0.008204605025851826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.9,14847.0,km,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,24,Ln(Urban distance),cbd_distance,D_location,log,"km (log Euclidean distance to centroid of nearest major urban centre; unit not printed, km implied by descriptives)",-0.0058,0.002,,,*,,,medium,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0058,0.002,b (log-log),reported,-0.023793354574970293,0.008204605025851826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.9,14847.0,km,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,24,Ln(Urban distance),cbd_distance,D_location,log,"km (log Euclidean distance to centroid of nearest major urban centre; unit not printed, km implied by descriptives)",-0.0119,0.003,,,***,,,medium,SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,-0.0119,0.003,b (log-log),reported,-0.03253691311209422,0.008202583137502745,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.966666666666667,14847.0,km,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,24,Ln(Urban distance),cbd_distance,D_location,log,"km (log Euclidean distance to centroid of nearest major urban centre; unit not printed, km implied by descriptives)",-0.0116,0.003,,,***,,,medium,SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,-0.0116,0.003,b (log-log),reported,-0.031717490636968826,0.008202799302664352,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.8666666666666663,14847.0,km,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,24,Ln(Density),density,F_neighbourhood,log,per km2 (municipal population per square kilometre),0.1008,0.005,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.1008,0.005,b (log-log),reported,0.1632325757669029,0.008096853956691612,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.16,14847.0,per km2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,24,Ln(Density),density,F_neighbourhood,log,per km2 (municipal population per square kilometre),0.1006,0.005,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.1006,0.005,b (log-log),reported,0.16291730621007686,0.008097281620779169,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.119999999999997,14847.0,per km2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,24,Ln(Density),density,F_neighbourhood,log,per km2 (municipal population per square kilometre),0.1003,0.005,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.1003,0.005,b (log-log),reported,0.16244430831693044,0.008097921650893842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.06,14847.0,per km2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,24,Ln(Density),density,F_neighbourhood,log,per km2 (municipal population per square kilometre),0.1003,0.005,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.1003,0.005,b (log-log),reported,0.16244430831693044,0.008097921650893842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.06,14847.0,per km2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,24,Ln(Density),density,F_neighbourhood,log,per km2 (municipal population per square kilometre),0.0859,0.007,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,0.0859,0.007,b (log-log),reported,0.10020385156660398,0.008165622362819881,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.271428571428572,14847.0,per km2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,24,Ln(Density),density,F_neighbourhood,log,per km2 (municipal population per square kilometre),0.0859,0.007,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,0.0859,0.007,b (log-log),reported,0.10020385156660398,0.008165622362819881,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.271428571428572,14847.0,per km2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,24,Ln(Foreign),demographics,F_neighbourhood,log,"share (log of 1 + percentage of population with a non-western background, municipality)",-0.1536,0.009,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.1536,0.009,b (log-log),reported,-0.13871089275093337,0.008127591372125003,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.066666666666666,14847.0,share,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,24,Ln(Foreign),demographics,F_neighbourhood,log,"share (log of 1 + percentage of population with a non-western background, municipality)",-0.1535,0.009,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.1535,0.009,b (log-log),reported,-0.13862232207896777,0.008127693151209836,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.055555555555557,14847.0,share,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,24,Ln(Foreign),demographics,F_neighbourhood,log,"share (log of 1 + percentage of population with a non-western background, municipality)",-0.1531,0.009,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.1531,0.009,b (log-log),reported,-0.13826800614648044,0.008128099642836863,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.011111111111113,14847.0,share,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,24,Ln(Foreign),demographics,F_neighbourhood,log,"share (log of 1 + percentage of population with a non-western background, municipality)",-0.1531,0.009,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.1531,0.009,b (log-log),reported,-0.13826800614648044,0.008128099642836863,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.011111111111113,14847.0,share,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,24,Ln(Foreign),demographics,F_neighbourhood,log,"share (log of 1 + percentage of population with a non-western background, municipality)",-0.1164,0.013,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,-0.1164,0.013,b (log-log),reported,-0.07328597477678585,0.00818485972592969,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.953846153846154,14847.0,share,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,24,Ln(Foreign),demographics,F_neighbourhood,log,"share (log of 1 + percentage of population with a non-western background, municipality)",-0.1159,0.013,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,-0.1159,0.013,b (log-log),reported,-0.07297285241014245,0.008185048156443933,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.915384615384616,14847.0,share,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,24,Burglary,crime,F_neighbourhood,log,"rate (log of 1 + burglaries per 10,000 inhabitants, municipality, 2012)",-0.0185,0.005,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0185,0.005,b (log-log),reported,-0.030351645191858387,0.008203147349150916,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.6999999999999997,14847.0,rate,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,24,Burglary,crime,F_neighbourhood,log,"rate (log of 1 + burglaries per 10,000 inhabitants, municipality, 2012)",-0.0182,0.005,,,***,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0182,0.005,b (log-log),reported,-0.029859898806705937,0.00820326890294119,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.64,14847.0,rate,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,24,Burglary,crime,F_neighbourhood,log,"rate (log of 1 + burglaries per 10,000 inhabitants, municipality, 2012)",-0.0171,0.005,,,**,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0171,0.005,b (log-log),reported,-0.02805664593302658,0.008203697641235843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.42,14847.0,rate,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,24,Burglary,crime,F_neighbourhood,log,"rate (log of 1 + burglaries per 10,000 inhabitants, municipality, 2012)",-0.0172,0.005,,,**,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0172,0.005,b (log-log),reported,-0.02822058959663041,0.008203659766462328,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.44,14847.0,rate,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,24,Burglary,crime,F_neighbourhood,log,"rate (log of 1 + burglaries per 10,000 inhabitants, municipality, 2012)",-0.0118,0.008,,,,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,-0.0118,0.008,b (log-log),reported,-0.012104332594370807,0.008206327182624276,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4749999999999999,14847.0,rate,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,24,Burglary,crime,F_neighbourhood,log,"rate (log of 1 + burglaries per 10,000 inhabitants, municipality, 2012)",-0.012,0.008,,,,,,high,Municipal/neighbourhood variable; SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,-0.012,0.008,b (log-log),reported,-0.012309459946806333,0.008206306631204223,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5,14847.0,rate,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,24,Ln(Water distance),water_proximity,E_environment,log,distance to water (log; unit not printed),-0.0087,0.002,,,***,,,medium,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0087,0.002,b (log-log),reported,-0.03567741045221419,0.008201703552233148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.35,14847.0,distance to water,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,24,Ln(Water distance),water_proximity,E_environment,log,distance to water (log; unit not printed),-0.0087,0.002,,,***,,,medium,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0087,0.002,b (log-log),reported,-0.03567741045221419,0.008201703552233148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.35,14847.0,distance to water,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,24,Ln(Water distance),water_proximity,E_environment,log,distance to water (log; unit not printed),-0.0088,0.002,,,***,,,medium,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0088,0.002,b (log-log),reported,-0.03608696461902369,0.00820158286795993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.4,14847.0,distance to water,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,24,Ln(Water distance),water_proximity,E_environment,log,distance to water (log; unit not printed),-0.0088,0.002,,,***,,,medium,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0088,0.002,b (log-log),reported,-0.03608696461902369,0.00820158286795993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.4,14847.0,distance to water,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,24,Ln(Water distance),water_proximity,E_environment,log,distance to water (log; unit not printed),-0.0116,0.002,,,***,,,medium,SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,-0.0116,0.002,b (log-log),reported,-0.04754635060316749,0.008197646655718533,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.8,14847.0,distance to water,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,24,Ln(Water distance),water_proximity,E_environment,log,distance to water (log; unit not printed),-0.0115,0.002,,,***,,,medium,SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,-0.0115,0.002,b (log-log),reported,-0.0471373829522357,0.0081978057308236,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.75,14847.0,distance to water,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,24,Ln(Forest distance),green_space,E_environment,log,distance to forest (log; unit not printed),-0.0045,0.002,,,*,,,medium,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0045,0.002,b (log-log),reported,-0.018462441577416236,0.008205529589962771,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.25,14847.0,distance to forest,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,24,Ln(Forest distance),green_space,E_environment,log,distance to forest (log; unit not printed),-0.0043,0.002,,,*,,,medium,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0043,0.002,b (log-log),reported,-0.01764214994924424,0.008205651139183368,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.15,14847.0,distance to forest,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,24,Ln(Forest distance),green_space,E_environment,log,distance to forest (log; unit not printed),-0.0038,0.002,,,*,,,medium,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0038,0.002,b (log-log),reported,-0.015591268635961223,0.008205930861032223,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9,14847.0,distance to forest,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,24,Ln(Forest distance),green_space,E_environment,log,distance to forest (log; unit not printed),-0.0039,0.002,,,*,,,medium,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0039,0.002,b (log-log),reported,-0.016001461470432812,0.008205877677145031,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.95,14847.0,distance to forest,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,24,Ln(Forest distance),green_space,E_environment,log,distance to forest (log; unit not printed),-0.0039,0.002,,,,,,medium,SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,-0.0039,0.002,b (log-log),reported,-0.016001461470432812,0.008205877677145031,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.95,14847.0,distance to forest,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,24,Ln(Forest distance),green_space,E_environment,log,distance to forest (log; unit not printed),-0.004,0.002,,,†,,,medium,SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,-0.004,0.002,b (log-log),reported,-0.01641164622586575,0.008205823112932876,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,14847.0,distance to forest,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,24,Ln(Nature distance),green_space,E_environment,log,distance to nature area (log; unit not printed),-0.0553,0.003,,,***,,,medium,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0553,0.003,b (log-log),reported,-0.14957909956586185,0.00811459852979359,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-18.433333333333334,14847.0,distance to nature area,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,24,Ln(Nature distance),green_space,E_environment,log,distance to nature area (log; unit not printed),-0.0549,0.003,,,***,,,medium,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0549,0.003,b (log-log),reported,-0.14852110424384518,0.008115907335729247,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-18.299999999999997,14847.0,distance to nature area,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,24,Ln(Nature distance),green_space,E_environment,log,distance to nature area (log; unit not printed),-0.0546,0.003,,,***,,,medium,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0546,0.003,b (log-log),reported,-0.1477272727272727,0.008116883116883116,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-18.2,14847.0,distance to nature area,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,24,Ln(Nature distance),green_space,E_environment,log,distance to nature area (log; unit not printed),-0.0547,0.003,,,***,,,medium,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,-0.0547,0.003,b (log-log),reported,-0.1479919150365674,0.008116558411511925,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-18.23333333333333,14847.0,distance to nature area,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,24,Ln(Nature distance),green_space,E_environment,log,distance to nature area (log; unit not printed),-0.0357,0.004,,,***,,,medium,SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,-0.0357,0.004,b (log-log),reported,-0.0730511350285056,0.008185001123642083,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.925,14847.0,distance to nature area,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,24,Ln(Nature distance),green_space,E_environment,log,distance to nature area (log; unit not printed),-0.0359,0.004,,,***,,,medium,SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,-0.0359,0.004,b (log-log),reported,-0.07345818284696569,0.008184755748965537,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.975,14847.0,distance to nature area,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c1,7,1,24,Ln(Floor Area),living_area,A_structural,log,"m2 (net floorspace, NVM definition)",0.6616,0.009,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7035,se,Structure characteristics only; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.6616,0.009,b (log-log),reported,0.5165721638386598,0.007027130402883823,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),73.51111111111112,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,24,Ln(Floor Area),living_area,A_structural,log,"m2 (net floorspace, NVM definition)",0.6508,0.009,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.6508,0.009,b (log-log),reported,0.5103493402401468,0.0070576890936713595,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),72.31111111111112,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,24,Ln(Floor Area),living_area,A_structural,log,"m2 (net floorspace, NVM definition)",0.6485,0.009,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.6485,0.009,b (log-log),reported,0.5090136337295211,0.007064183043277855,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),72.05555555555556,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,24,Ln(Floor Area),living_area,A_structural,log,"m2 (net floorspace, NVM definition)",0.6471,0.009,,,***,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.6471,0.009,b (log-log),reported,0.5081987899224374,0.007068133378615264,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),71.9,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,24,Ln(Floor Area),living_area,A_structural,log,"m2 (net floorspace, NVM definition)",0.6471,0.009,,,***,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.6471,0.009,b (log-log),reported,0.5081987899224374,0.007068133378615264,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),71.9,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,24,Ln(Floor Area),living_area,A_structural,log,"m2 (net floorspace, NVM definition)",0.5932,0.008,,,***,,,high,SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,0.5932,0.008,b (log-log),reported,0.5198522565594356,0.007010819373694346,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),74.14999999999999,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,24,Ln(Floor Area),living_area,A_structural,log,"m2 (net floorspace, NVM definition)",0.5931,0.008,,,***,,,high,SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,0.5931,0.008,b (log-log),reported,0.5197883000529032,0.0070111387631482495,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),74.13749999999999,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c1,7,1,24,Ln(Lotsize),lot_size,A_structural,log,m2 (log of 1 + lot size; flats = 0),0.0461,0.001,,,***,,,high,Log(1+lot size); apartments recorded with zero land; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7035,se,Structure characteristics only; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.0461,0.001,b (log-log),reported,0.35386020683712865,0.0076759263955993185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),46.1,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,24,Ln(Lotsize),lot_size,A_structural,log,m2 (log of 1 + lot size; flats = 0),0.0514,0.001,,,***,,,high,Log(1+lot size); apartments recorded with zero land; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.0514,0.001,b (log-log),reported,0.38867009524788926,0.007561675004822748,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),51.4,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,24,Ln(Lotsize),lot_size,A_structural,log,m2 (log of 1 + lot size; flats = 0),0.0514,0.001,,,***,,,high,Log(1+lot size); apartments recorded with zero land; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.0514,0.001,b (log-log),reported,0.38867009524788926,0.007561675004822748,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),51.4,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,24,Ln(Lotsize),lot_size,A_structural,log,m2 (log of 1 + lot size; flats = 0),0.0514,0.001,,,***,,,high,Log(1+lot size); apartments recorded with zero land; SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.0514,0.001,b (log-log),reported,0.38867009524788926,0.007561675004822748,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),51.4,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,24,Ln(Lotsize),lot_size,A_structural,log,m2 (log of 1 + lot size; flats = 0),0.0514,0.001,,,***,,,high,Log(1+lot size); apartments recorded with zero land; SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.0514,0.001,b (log-log),reported,0.38867009524788926,0.007561675004822748,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),51.4,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,24,Ln(Lotsize),lot_size,A_structural,log,m2 (log of 1 + lot size; flats = 0),0.0553,0.001,,,***,,,high,Log(1+lot size); apartments recorded with zero land; SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,0.0553,0.001,b (log-log),reported,0.41327285184219953,0.007473288460075941,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),55.300000000000004,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,24,Ln(Lotsize),lot_size,A_structural,log,m2 (log of 1 + lot size; flats = 0),0.0552,0.001,,,***,,,high,Log(1+lot size); apartments recorded with zero land; SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,0.0552,0.001,b (log-log),reported,0.4126528755536585,0.00747559557162425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),55.199999999999996,14847.0,m2,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c1,7,1,25,Rooms,bedrooms,A_structural,log,count (natural log of number of rooms per Table 1),0.0309,0.009,,,***,,,high,Printed as 'Rooms' in Table 7 but defined as Ln(rooms) in Tables 1 and 3; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7035,se,Structure characteristics only; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.0309,0.009,b (log-log),reported,0.02816594196114244,0.00820367241586673,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4333333333333336,14847.0,count,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,25,Rooms,bedrooms,A_structural,log,count (natural log of number of rooms per Table 1),0.0327,0.009,,,***,,,high,Printed as 'Rooms' in Table 7 but defined as Ln(rooms) in Tables 1 and 3; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.0327,0.009,b (log-log),reported,0.029805258974566824,0.008203282286578024,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6333333333333337,14847.0,count,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,25,Rooms,bedrooms,A_structural,log,count (natural log of number of rooms per Table 1),0.0326,0.009,,,***,,,high,Printed as 'Rooms' in Table 7 but defined as Ln(rooms) in Tables 1 and 3; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.0326,0.009,b (log-log),reported,0.02971419199415272,0.00820330453826302,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6222222222222222,14847.0,count,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,25,Rooms,bedrooms,A_structural,log,count (natural log of number of rooms per Table 1),0.0323,0.009,,,***,,,high,Printed as 'Rooms' in Table 7 but defined as Ln(rooms) in Tables 1 and 3; SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.0323,0.009,b (log-log),reported,0.02944098662233312,0.008203370885479816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5888888888888895,14847.0,count,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,25,Rooms,bedrooms,A_structural,log,count (natural log of number of rooms per Table 1),0.0323,0.009,,,***,,,high,Printed as 'Rooms' in Table 7 but defined as Ln(rooms) in Tables 1 and 3; SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),elasticity,0.0323,0.009,b (log-log),reported,0.02944098662233312,0.008203370885479816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5888888888888895,14847.0,count,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,25,Rooms,bedrooms,A_structural,log,count (natural log of number of rooms per Table 1),0.0498,0.008,,,***,,,high,Printed as 'Rooms' in Table 7 but defined as Ln(rooms) in Tables 1 and 3; SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,0.0498,0.008,b (log-log),reported,0.051021589725736706,0.00819623931337136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.225,14847.0,count,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,25,Rooms,bedrooms,A_structural,log,count (natural log of number of rooms per Table 1),0.05,0.008,,,***,,,high,Printed as 'Rooms' in Table 7 but defined as Ln(rooms) in Tables 1 and 3; SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",elasticity,0.05,0.008,b (log-log),reported,0.05122595908758647,0.008196153454013835,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.25,14847.0,count,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c1,7,1,25,Two Bathrooms,bathrooms,A_structural,dummy,binary (two bathrooms vs one),0.1438,0.008,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7035,se,Structure characteristics only; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,15.461620648957354,0.9237225238394808,100*(exp(b - se^2/2) - 1),reported,0.14594010967580615,0.008119060343577532,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.975,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,25,Two Bathrooms,bathrooms,A_structural,dummy,binary (two bathrooms vs one),0.1395,0.008,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,14.96620159449189,0.91975904457445,100*(exp(b - se^2/2) - 1),reported,0.14166501755606656,0.008124158712892704,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.4375,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,25,Two Bathrooms,bathrooms,A_structural,dummy,binary (two bathrooms vs one),0.1386,0.008,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,14.862778560403257,0.9189316338250204,100*(exp(b - se^2/2) - 1),reported,0.14076921849291268,0.008125207416618336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.325,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,25,Two Bathrooms,bathrooms,A_structural,dummy,binary (two bathrooms vs one),0.1374,0.008,,,***,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,14.725025894260767,0.9178295772306339,100*(exp(b - se^2/2) - 1),reported,0.1395742820754585,0.008126595754029606,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.175,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,25,Two Bathrooms,bathrooms,A_structural,dummy,binary (two bathrooms vs one),0.1375,0.008,,,***,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,14.736498970494448,0.9179213647776578,100*(exp(b - se^2/2) - 1),reported,0.13967388347796864,0.00812648049326363,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.1875,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,25,Two Bathrooms,bathrooms,A_structural,dummy,binary (two bathrooms vs one),0.1164,0.007,,,***,,,high,SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,12.341763626450074,0.7864116122336304,100*(exp(b - se^2/2) - 1),reported,0.13521617616475085,0.008131556985852714,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.62857142857143,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,25,Two Bathrooms,bathrooms,A_structural,dummy,binary (two bathrooms vs one),0.116,0.007,,,***,,,high,SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,12.29683590714239,0.7860971104932782,100*(exp(b - se^2/2) - 1),reported,0.13475996839791785,0.00813206705849504,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.571428571428573,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c1,7,1,25,Three Bathrooms,bathrooms,A_structural,dummy,binary (three bathrooms vs one),0.2432,0.063,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7035,se,Structure characteristics only; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,27.279529314155827,8.034539079082041,100*(exp(b - se^2/2) - 1),reported,0.03166546163641855,0.008202812841670924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8603174603174604,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,25,Three Bathrooms,bathrooms,A_structural,dummy,binary (three bathrooms vs one),0.2489,0.061,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,28.022968085193757,7.823943968208005,100*(exp(b - se^2/2) - 1),reported,0.03346819879622231,0.008202330761629411,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.080327868852459,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,25,Three Bathrooms,bathrooms,A_structural,dummy,binary (three bathrooms vs one),0.2487,0.061,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,27.997366051865402,7.82237933588281,100*(exp(b - se^2/2) - 1),reported,0.03344133599549222,0.00820233814123452,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.077049180327869,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,25,Three Bathrooms,bathrooms,A_structural,dummy,binary (three bathrooms vs one),0.2542,0.061,,,***,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,28.703291079458083,7.8655209529242605,100*(exp(b - se^2/2) - 1),reported,0.03418003640649839,0.00820213304797955,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.167213114754098,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,25,Three Bathrooms,bathrooms,A_structural,dummy,binary (three bathrooms vs one),0.254,0.061,,,***,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,28.677552995136434,7.863948006033605,100*(exp(b - se^2/2) - 1),reported,0.034153175547499776,0.008202140584242073,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.163934426229508,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,25,Three Bathrooms,bathrooms,A_structural,dummy,binary (three bathrooms vs one),0.1801,0.053,,,***,,,high,SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,19.565661129332824,6.345886581475366,100*(exp(b - se^2/2) - 1),reported,0.027877233291980413,0.008203738836618334,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.39811320754717,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,25,Three Bathrooms,bathrooms,A_structural,dummy,binary (three bathrooms vs one),0.1806,0.053,,,***,,,high,SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,19.625458908096395,6.349060318134148,100*(exp(b - se^2/2) - 1),reported,0.02795456665828642,0.00820372111234319,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.407547169811321,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c1,7,1,25,Balcony,terrace_balcony,C_exterior,binary,binary,0.1196,0.006,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7035,se,Structure characteristics only; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,12.702565638207242,0.67622756581588,100*(exp(b - se^2/2) - 1),reported,0.16144538972416456,0.008099267043018289,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.933333333333334,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,25,Balcony,terrace_balcony,C_exterior,binary,binary,0.1158,0.006,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,12.275108571581871,0.673662777250349,100*(exp(b - se^2/2) - 1),reported,0.15644340477362445,0.008105875895006448,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.3,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,25,Balcony,terrace_balcony,C_exterior,binary,binary,0.1153,0.006,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,12.218985049345864,0.673326030055538,100*(exp(b - se^2/2) - 1),reported,0.1557843430917401,0.008106730776673381,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.216666666666665,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,25,Balcony,terrace_balcony,C_exterior,binary,binary,0.1153,0.006,,,***,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,12.218985049345864,0.673326030055538,100*(exp(b - se^2/2) - 1),reported,0.1557843430917401,0.008106730776673381,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.216666666666665,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,25,Balcony,terrace_balcony,C_exterior,binary,binary,0.1153,0.006,,,***,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,12.218985049345864,0.673326030055538,100*(exp(b - se^2/2) - 1),reported,0.1557843430917401,0.008106730776673381,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.216666666666665,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,25,Balcony,terrace_balcony,C_exterior,binary,binary,0.087,0.005,,,***,,,high,SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,9.088304359500722,0.5454483398591389,100*(exp(b - se^2/2) - 1),reported,0.14136645642295834,0.008124508989825193,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.4,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,25,Balcony,terrace_balcony,C_exterior,binary,binary,0.0871,0.005,,,***,,,high,SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,9.099213735396372,0.5455028874204574,100*(exp(b - se^2/2) - 1),reported,0.14152569383305474,0.0081243222636656,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.419999999999998,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c1,7,1,25,Parking,parking,A_structural,binary,binary (private parking),0.1244,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7035,se,Structure characteristics only; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,13.245970820701602,0.45298750716836816,100*(exp(b - se^2/2) - 1),reported,0.24730713042511457,0.00795199776286542,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),31.099999999999998,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,25,Parking,parking,A_structural,binary,binary (private parking),0.1342,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,14.36123721423841,0.45744860843118273,100*(exp(b - se^2/2) - 1),reported,0.26546341843908533,0.007912471488497327,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.550000000000004,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,25,Parking,parking,A_structural,binary,binary (private parking),0.1338,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,14.315501867031944,0.45726566557882004,100*(exp(b - se^2/2) - 1),reported,0.26472769954952086,0.007914131526144121,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.45,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,25,Parking,parking,A_structural,binary,binary (private parking),0.1327,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,14.189823950504831,0.45676294989100213,100*(exp(b - se^2/2) - 1),reported,0.26270209021542923,0.007918676419455288,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.175000000000004,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,25,Parking,parking,A_structural,binary,binary (private parking),0.1327,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,14.189823950504831,0.45676294989100213,100*(exp(b - se^2/2) - 1),reported,0.26270209021542923,0.007918676419455288,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.175000000000004,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,25,Parking,parking,A_structural,binary,binary (private parking),0.1203,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,12.78261287321616,0.4511340605509128,100*(exp(b - se^2/2) - 1),reported,0.23963188261182908,0.007967809895655164,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.075,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,25,Parking,parking,A_structural,binary,binary (private parking),0.1205,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,12.805171651593428,0.45122429638630573,100*(exp(b - se^2/2) - 1),reported,0.24000734235927335,0.007967048709021523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.125,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c1,7,1,25,Basement,basement,A_structural,binary,binary,-0.0192,0.008,,,*,,,high,Negative because floorspace measure already includes basement area; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7035,se,Structure characteristics only; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-1.9048244965777283,0.7847865167941092,100*(exp(b - se^2/2) - 1),reported,-0.019692808602938178,0.008205336917890908,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,25,Basement,basement,A_structural,binary,binary,-0.0228,0.008,,,**,,,high,Negative because floorspace measure already includes basement area; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-2.2573322337548496,0.7819663646532675,100*(exp(b - se^2/2) - 1),reported,-0.023383350596322596,0.008204684419762314,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.85,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,25,Basement,basement,A_structural,binary,binary,-0.0227,0.008,,,**,,,high,Negative because floorspace measure already includes basement area; SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-2.2475574782485963,0.7820445651996951,100*(exp(b - se^2/2) - 1),reported,-0.02328084774996487,0.008204704052851057,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.8375,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,25,Basement,basement,A_structural,binary,binary,-0.0223,0.008,,,**,,,high,Negative because floorspace measure already includes basement area; SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-2.2084486800016956,0.7823574455976827,100*(exp(b - se^2/2) - 1),reported,-0.022870829054520515,0.008204781723594803,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.7875,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,25,Basement,basement,A_structural,binary,binary,-0.0223,0.008,,,**,,,high,Negative because floorspace measure already includes basement area; SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-2.2084486800016956,0.7823574455976827,100*(exp(b - se^2/2) - 1),reported,-0.022870829054520515,0.008204781723594803,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.7875,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,25,Basement,basement,A_structural,binary,binary,-0.032,0.007,,,***,,,high,Negative because floorspace measure already includes basement area; SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,-3.1517146041392663,0.6779546074554383,100*(exp(b - se^2/2) - 1),reported,-0.037491011037961444,0.008201158664554066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.571428571428571,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,True
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,25,Basement,basement,A_structural,binary,binary,-0.0319,0.007,,,***,,,high,Negative because floorspace measure already includes basement area; SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,-3.142029291342119,0.6780224063060698,100*(exp(b - se^2/2) - 1),reported,-0.03737401553487276,0.00820119463147678,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.557142857142857,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c1,7,1,25,Attic,storage,B_interior,binary,binary (attic/loft),-0.0392,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7035,se,Structure characteristics only; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-3.8449314197986806,0.3846233512953078,100*(exp(b - se^2/2) - 1),reported,-0.08016902396149082,0.008180512649131716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.799999999999999,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,True
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,25,Attic,storage,B_interior,binary,binary (attic/loft),-0.0371,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-3.642793605360739,0.3854319090214955,100*(exp(b - se^2/2) - 1),reported,-0.07589969192609944,0.008183255194188619,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.275,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,25,Attic,storage,B_interior,binary,binary (attic/loft),-0.0373,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-3.662063119624004,0.3853548303478154,100*(exp(b - se^2/2) - 1),reported,-0.07630647861273315,0.008183000387424467,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.325,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,25,Attic,storage,B_interior,binary,binary (attic/loft),-0.0389,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-3.816080571813796,0.38473875561047804,100*(exp(b - se^2/2) - 1),reported,-0.07955938390387053,0.008180913511966122,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.725,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,25,Attic,storage,B_interior,binary,binary (attic/loft),-0.0389,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-3.816080571813796,0.38473875561047804,100*(exp(b - se^2/2) - 1),reported,-0.07955938390387053,0.008180913511966122,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.725,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,25,Attic,storage,B_interior,binary,binary (attic/loft),-0.0316,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,-3.1113688918605553,0.3875576248811551,100*(exp(b - se^2/2) - 1),reported,-0.06469889485833985,0.008189733526372133,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.9,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,25,Attic,storage,B_interior,binary,binary (attic/loft),-0.032,0.004,,,***,,,high,SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,-3.150116594246688,0.3874026328316791,100*(exp(b - se^2/2) - 1),reported,-0.06551437494467446,0.008189296868084308,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.0,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c1,7,1,25,Under roof,storage,B_interior,binary,binary (under-roof storage area),-0.0064,0.006,,,,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7035,se,Structure characteristics only; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-0.6397448627740276,0.5961722618274894,100*(exp(b - se^2/2) - 1),reported,-0.008753721576912033,0.00820661397835503,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0666666666666667,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,25,Under roof,storage,B_interior,binary,binary (under-roof storage area),-0.0051,0.006,,,,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-0.5104925352858003,0.5969477897517957,100*(exp(b - se^2/2) - 1),reported,-0.0069757194319330995,0.008206728743450704,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8500000000000001,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,25,Under roof,storage,B_interior,binary,binary (under-roof storage area),-0.0054,0.005,,,,,,high,SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-0.5397878812827273,0.49730727689569565,100*(exp(b - se^2/2) - 1),reported,-0.008863134554054382,0.008206606068568871,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.08,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,25,Under roof,storage,B_interior,binary,binary (under-roof storage area),-0.0073,0.006,,,,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-0.729128863563755,0.5956359481691921,100*(exp(b - se^2/2) - 1),reported,-0.009984598517632823,0.008206519329561226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2166666666666666,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,25,Under roof,storage,B_interior,binary,binary (under-roof storage area),-0.0073,0.006,,,,,,high,SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,-0.729128863563755,0.5956359481691921,100*(exp(b - se^2/2) - 1),reported,-0.009984598517632823,0.008206519329561226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2166666666666666,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,25,Under roof,storage,B_interior,binary,binary (under-roof storage area),-0.0106,0.005,,,*,,,high,SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,-1.0556386100222137,0.4947279910111261,100*(exp(b - se^2/2) - 1),reported,-0.017396055438504966,0.008205686527596682,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.12,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,25,Under roof,storage,B_interior,binary,binary (under-roof storage area),-0.0112,0.005,,,*,,,high,SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,-1.1149874204326116,0.49443124324975024,100*(exp(b - se^2/2) - 1),reported,-0.018380414064904104,0.008205541993260762,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.2399999999999998,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c1,7,1,25,Monument,architectural_style,H_ai_derived,binary,binary (monumental appearance assessed by realtor),0.1416,0.024,,,***,,,high,Monumental appearance (not listed status); SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7035,se,Structure characteristics only; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,15.178394852288468,2.7650777041714303,100*(exp(b - se^2/2) - 1),reported,0.04836421397221881,0.008197324402070983,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c2,7,2,25,Monument,architectural_style,H_ai_derived,binary,binary (monumental appearance assessed by realtor),0.1425,0.023,,,***,,,high,Monumental appearance (not listed status); SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7223,se,Structure + neighbourhood characteristics; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,15.284811230133899,2.65225208620195,100*(exp(b - se^2/2) - 1),reported,0.05078166968904669,0.008196339669109291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.195652173913043,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c3,7,3,25,Monument,architectural_style,H_ai_derived,binary,binary (monumental appearance assessed by realtor),0.14,0.023,,,***,,,high,Monumental appearance (not listed status); SE printed on sigma row,log transaction price,log,OLS,14857.0,0.7235,se,Structure + neighbourhood + subjective well-being and positive affect; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,14.996959167060343,2.645629737371623,100*(exp(b - se^2/2) - 1),reported,0.04989300069816131,0.008196707257555072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.086956521739131,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,ols,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c4,7,4,25,Monument,architectural_style,H_ai_derived,binary,binary (monumental appearance assessed by realtor),0.1418,0.023,,,***,,,high,Monumental appearance (not listed status); SE printed on sigma row,log transaction price,log,IV,14857.0,0.7191,se,Well-being instrumented by Ln(Health+1); Wu-Hausman 28.05***; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,15.204140100462272,2.650396159391776,100*(exp(b - se^2/2) - 1),reported,0.0505328544389004,0.008196443244673548,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.165217391304348,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c5,7,5,25,Monument,architectural_style,H_ai_derived,binary,binary (monumental appearance assessed by realtor),0.1418,0.023,,,***,,,high,Monumental appearance (not listed status); SE printed on sigma row,log transaction price,log,IV,14857.0,0.7195,se,Well-being instrumented by Ln(Health+1) and Ln(Pain+1); Sargan 0.332; N inferred from Table 2 / Table 6 (not printed in Table 7),pct_premium,15.204140100462272,2.650396159391776,100*(exp(b - se^2/2) - 1),reported,0.0505328544389004,0.008196443244673548,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.165217391304348,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,iv,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c6,7,6,25,Monument,architectural_style,H_ai_derived,binary,binary (monumental appearance assessed by realtor),0.1648,0.02,,,***,,,high,Monumental appearance (not listed status); SE printed on sigma row,log transaction price,log,other,14857.0,0.7574,se,"General nesting spatial model (rho 0.4282***, lambda 0.2409***, spatial lag of well-being); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,17.892145580277653,2.3583145273478765,100*(exp(b - se^2/2) - 1),reported,0.06747098861730998,0.008188226773945387,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.24,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,other,other,True,True,False
291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5,291ca9688b933cfaf7d01e6f6552e428bb2432b5:T7-c7,7,7,25,Monument,architectural_style,H_ai_derived,binary,binary (monumental appearance assessed by realtor),0.1648,0.02,,,***,,,high,Monumental appearance (not listed status); SE printed on sigma row,log transaction price,log,SAC,14857.0,0.7568,se,"Spatial lag and spatial error model (rho 0.4238***, lambda 0.2445***); N inferred from Table 2 / Table 6 (not printed in Table 7)",pct_premium,17.892145580277653,2.3583145273478765,100*(exp(b - se^2/2) - 1),reported,0.06747098861730998,0.008188226773945387,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.24,14847.0,binary,,2020.0,Netherlands,Europe,High income,2000.0,2012.0,mixed,transaction,working_paper,True,False,unknown,,2006.0,spatial,other,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T3-c1,3,Local Market,36,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.012,,,0.34,,,,high,distance to transitional (estuarine) waters; robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.8,p,spatial FE level: Local Market (50 absorbed units); robust p-values clustered at SFE level; controls included but not reported,elasticity,-0.012,0.01257643784494571,b (log-log),|b/z(p)| (two-sided normal),-0.003017020044668816,0.0031619470890610576,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9541652531461942,100020.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T3-c2,3,Micro market,36,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.012,,,0.1,,,,high,distance to transitional (estuarine) waters; robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.841,p,spatial FE level: Micro market (261 absorbed units); robust p-values clustered at SFE level; controls included but not reported,elasticity,-0.012,0.007295481982941227,b (log-log),|b/z(p)| (two-sided normal),-0.005200893466704698,0.003161918715128405,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6448536269514729,100020.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T3-c4,3,Small Area,36,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.014,,,0.01,,,,high,distance to transitional (estuarine) waters; robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.882,p,spatial FE level: Small Area (5571 absorbed units); robust p-values clustered at SFE level; controls included but not reported,elasticity,-0.014,0.0054351427638125,b (log-log),|b/z(p)| (two-sided normal),-0.008144402908585707,0.003161856609583792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,100020.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T3-c5,3,ED x Year,36,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.018,,,0.01,,,,high,distance to transitional (estuarine) waters; robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.868,p,spatial FE level: ED x Year (4509 absorbed units); robust p-values clustered at SFE level; controls included but not reported,elasticity,-0.018,0.006988040696330356,b (log-log),|b/z(p)| (two-sided normal),-0.008144402908585707,0.003161856609583792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,100020.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T3-c6,3,Small Area + Micro-Market x Year,36,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.014,,,0.01,,,,high,distance to transitional (estuarine) waters; robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.89,p,spatial FE level: Small Area + Micro-Market x Year (5571 absorbed units); robust p-values clustered at SFE level; controls included but not reported,elasticity,-0.014,0.0054351427638125,b (log-log),|b/z(p)| (two-sided normal),-0.008144402908585707,0.003161856609583792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,100020.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T3-c1,3,Local Market,36,Seaview breadth,view,E_environment,log,"index (ln of visible near-shore sea area score, x NLP sea-view indicator)",0.01,,,0.08,,,,high,GIS 3D viewshed breadth restricted to NLP-flagged listings; AI/NLP-assisted; robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.8,p,spatial FE level: Local Market (50 absorbed units); robust p-values clustered at SFE level; controls included but not reported,elasticity,0.01,0.005712046359543804,b (log-log),|b/z(p)| (two-sided normal),0.005535517109104458,0.003161913035125256,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7506860712521697,100020.0,index,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T3-c2,3,Micro market,36,Seaview breadth,view,E_environment,log,"index (ln of visible near-shore sea area score, x NLP sea-view indicator)",0.011,,,0.01,,,,high,GIS 3D viewshed breadth restricted to NLP-flagged listings; AI/NLP-assisted; robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.841,p,spatial FE level: Micro market (261 absorbed units); robust p-values clustered at SFE level; controls included but not reported,elasticity,0.011,0.004270469314424107,b (log-log),|b/z(p)| (two-sided normal),0.008144402908585707,0.003161856609583792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,100020.0,index,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T4-c1,4,Baseline,37,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.014,,,0.01,,,,high,robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.89,p,"Baseline; spatial FE Small Area + Micro-Market x Year (5,571 units); controls not reported",elasticity,-0.014,0.0054351427638125,b (log-log),|b/z(p)| (two-sided normal),-0.008144402908585707,0.003161856609583792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,100020.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T4-c2,4,Spec 1: GIS-only breadth and depth,37,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.015,,,0.01,,,,high,robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.89,p,"Spec 1: GIS-only breadth and depth; spatial FE Small Area + Micro-Market x Year (5,571 units); controls not reported",elasticity,-0.015,0.005823367246941964,b (log-log),|b/z(p)| (two-sided normal),-0.008144402908585707,0.003161856609583792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,100020.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T4-c3,4,Spec 2: GIS-only breadth,37,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.014,,,0.01,,,,high,robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.89,p,"Spec 2: GIS-only breadth; spatial FE Small Area + Micro-Market x Year (5,571 units); controls not reported",elasticity,-0.014,0.0054351427638125,b (log-log),|b/z(p)| (two-sided normal),-0.008144402908585707,0.003161856609583792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,100020.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T4-c4,4,Spec 3: GIS-only depth,37,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.015,,,0.01,,,,high,robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.89,p,"Spec 3: GIS-only depth; spatial FE Small Area + Micro-Market x Year (5,571 units); controls not reported",elasticity,-0.015,0.005823367246941964,b (log-log),|b/z(p)| (two-sided normal),-0.008144402908585707,0.003161856609583792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,100020.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T4-c5,4,Spec 4: NLP sea-view dummy only,37,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.012,,,0.02,,,,high,robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.89,p,"Spec 4: NLP sea-view dummy only; spatial FE Small Area + Micro-Market x Year (5,571 units); controls not reported",elasticity,-0.012,0.0051582998974079195,b (log-log),|b/z(p)| (two-sided normal),-0.007355623369604289,0.0031618759394000918,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3263478740408408,100020.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T4-c6,4,Spec 5: NLP sea-view dummy set to 0 when GIS measure is 0,37,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.013,,,0.01,,,,high,robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.89,p,"Spec 5: NLP sea-view dummy set to 0 when GIS measure is 0; spatial FE Small Area + Micro-Market x Year (5,571 units); controls not reported",elasticity,-0.013,0.005046918280683036,b (log-log),|b/z(p)| (two-sided normal),-0.008144402908585707,0.003161856609583792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,100020.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T4-c2,4,Spec 1: GIS-only breadth and depth,37,Seaview breadth (GIS only),view,E_environment,log,"index (ln of visible near-shore sea area score, all listings)",0.003,,,0.14,,,,high,GIS measure without NLP restriction; robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,100030.0,0.89,p,"Spec 1: GIS-only breadth and depth; spatial FE Small Area + Micro-Market x Year (5,571 units); controls not reported",elasticity,0.003,0.002032808129821332,b (log-log),|b/z(p)| (two-sided normal),0.004666343578288186,0.0031619270541612637,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4757910281791702,100020.0,index,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T5-c1,5 (printed 'Table 1' p.38),Baseline,38,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.015,,,0.01,,,,high,robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,99447.0,0.89,p,"Baseline; spatial FE Small Area + Micro-Market x Year (5,566 units); controls not reported",elasticity,-0.015,0.005823367246941964,b (log-log),|b/z(p)| (two-sided normal),-0.008168241779845766,0.0031711114430571182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,99437.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8,2b0979784a826ff5181dbb43492b0239ca3062e8:T5-c3,5 (printed 'Table 1' p.38),Adding slope,38,Distance To Transitional (log),water_proximity,E_environment,log,"m (Euclidean distance to transitional water body/estuary), log",-0.015,,,0.01,,,,high,robust clustered p-value printed below coefficient; no SE,natural log of listed sale price (EUR),log,OLS,99447.0,0.89,p,"Adding slope; spatial FE Small Area + Micro-Market x Year (5,566 units); controls not reported",elasticity,-0.015,0.005823367246941964,b (log-log),|b/z(p)| (two-sided normal),-0.008168241779845766,0.0031711114430571182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,99437.0,m log,,2023.0,Ireland,Europe,High income,2014.0,2019.0,mixed,listing,journal,True,True,clustered,NLP keyword classification of listing text to identify sea-view properties (combined with GIS viewshed),2016.5,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c1,2,1,8,HIGH,energy_efficiency,A_structural,dummy,binary,0.001,0.007,,,,,,high,"=1 if building energy performance <= 75 kWh/m2; reference: >75 kWh/m2 (c1,c2,c4) or medium efficiency 75-140 (c3,c5)",log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.812,se,Full sample; 2-digit postcode FE; robust SE,pct_premium,0.09759759548770841,0.7007003501166958,100*(exp(b - se^2/2) - 1),reported,0.0009700900025774411,0.0067906300180420875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.14285714285714285,21686.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c2,2,2,8,HIGH,energy_efficiency,A_structural,dummy,binary,0.011,0.005,,,**,,,high,"=1 if building energy performance <= 75 kWh/m2; reference: >75 kWh/m2 (c1,c2,c4) or medium efficiency 75-140 (c3,c5)",log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.933,se,Full sample; 4-digit postcode FE; robust SE,pct_premium,1.1048084264677849,0.5055303612223597,100*(exp(b - se^2/2) - 1),reported,0.014937726220546576,0.006789875554793898,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1999999999999997,21686.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c3,2,3,8,HIGH,energy_efficiency,A_structural,dummy,binary,0.011,0.005,,,**,,,high,"=1 if building energy performance <= 75 kWh/m2; reference: >75 kWh/m2 (c1,c2,c4) or medium efficiency 75-140 (c3,c5)",log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.933,se,Full sample; 4-digit postcode FE; HIGH and LOW dummies; robust SE,pct_premium,1.1048084264677849,0.5055303612223597,100*(exp(b - se^2/2) - 1),reported,0.014937726220546576,0.006789875554793898,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1999999999999997,21686.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c4,2,4,8,HIGH,energy_efficiency,A_structural,dummy,binary,0.007,0.004,,,*,,,high,"=1 if building energy performance <= 75 kWh/m2; reference: >75 kWh/m2 (c1,c2,c4) or medium efficiency 75-140 (c3,c5)",log sales price (SEK) of tenant-owned apartment,log,other,21695.0,0.943,se,Full sample; 4-digit postcode FE; robust regression (outlier-robust),pct_premium,0.7016501102615091,0.40280982290673945,100*(exp(b - se^2/2) - 1),reported,0.011883043053773672,0.006790310316442099,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.75,21685.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c5,2,5,8,HIGH,energy_efficiency,A_structural,dummy,binary,0.007,0.004,,,*,,,high,"=1 if building energy performance <= 75 kWh/m2; reference: >75 kWh/m2 (c1,c2,c4) or medium efficiency 75-140 (c3,c5)",log sales price (SEK) of tenant-owned apartment,log,other,21696.0,0.943,se,Full sample; 4-digit postcode FE; HIGH and LOW; robust regression,pct_premium,0.7016501102615091,0.40280982290673945,100*(exp(b - se^2/2) - 1),reported,0.01188276910970561,0.006790153776974635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.75,21686.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c3,2,3,8,LOW,energy_efficiency,A_structural,dummy,binary,-0.001,0.002,,,,,,high,=1 if building energy performance > 140 kWh/m2; reference medium efficiency,log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.933,se,Full sample; 4-digit postcode FE; HIGH and LOW dummies; robust SE,pct_premium,-0.10014981656266686,0.199800099966675,100*(exp(b - se^2/2) - 1),reported,-0.0033952970359119893,0.0067905940718239795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5,21686.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c5,2,5,8,LOW,energy_efficiency,A_structural,dummy,binary,-0.001,0.002,,,,,,high,=1 if building energy performance > 140 kWh/m2; reference medium efficiency,log sales price (SEK) of tenant-owned apartment,log,other,21696.0,0.943,se,Full sample; 4-digit postcode FE; HIGH and LOW; robust regression,pct_premium,-0.10014981656266686,0.199800099966675,100*(exp(b - se^2/2) - 1),reported,-0.0033952970359119893,0.0067905940718239795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5,21686.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c1,2,1,8,Area,living_area,A_structural,log,m2,0.862,0.019,,,***,,,high,,log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.812,se,Full sample; 2-digit postcode FE; robust SE,elasticity,0.862,0.019,b (log-log),reported,0.2944245620682365,0.006489636518905444,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),45.36842105263158,21686.0,m2,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c1,2,1,8,Room,bedrooms,A_structural,level,count,0.049,0.004,,,***,,,high,"Total number of rooms, not bedrooms; mapped to bedrooms as closest leaf",log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.812,se,Full sample; 2-digit postcode FE; robust SE,semi_elasticity,4.9,0.4,100*b/1 (per unit count),reported,0.08289892987235534,0.006767259581416762,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.25,21686.0,count,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c2,2,2,8,Area,living_area,A_structural,log,m2,0.746,0.012,,,***,,,high,,log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.933,se,Full sample; 4-digit postcode FE; robust SE,elasticity,0.746,0.012,b (log-log),reported,0.38891637330459794,0.006256027452620878,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),62.166666666666664,21686.0,m2,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c2,2,2,8,Room,bedrooms,A_structural,level,count,0.06,0.002,,,***,,,high,"Total number of rooms, not bedrooms; mapped to bedrooms as closest leaf",log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.933,se,Full sample; 4-digit postcode FE; robust SE,semi_elasticity,6.0,0.2,100*b/1 (per unit count),reported,0.19961887000309445,0.006653962333436481,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.0,21686.0,count,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c3,2,3,8,Area,living_area,A_structural,log,m2,0.746,0.012,,,***,,,high,,log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.933,se,Full sample; 4-digit postcode FE; HIGH and LOW dummies; robust SE,elasticity,0.746,0.012,b (log-log),reported,0.38891637330459794,0.006256027452620878,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),62.166666666666664,21686.0,m2,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c3,2,3,8,Room,bedrooms,A_structural,level,count,0.06,0.002,,,***,,,high,"Total number of rooms, not bedrooms; mapped to bedrooms as closest leaf",log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.933,se,Full sample; 4-digit postcode FE; HIGH and LOW dummies; robust SE,semi_elasticity,6.0,0.2,100*b/1 (per unit count),reported,0.19961887000309445,0.006653962333436481,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.0,21686.0,count,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c4,2,4,8,Area,living_area,A_structural,log,m2,0.751,0.006,,,***,,,high,,log sales price (SEK) of tenant-owned apartment,log,other,21695.0,0.943,se,Full sample; 4-digit postcode FE; robust regression (outlier-robust),elasticity,0.751,0.006,b (log-log),reported,0.6476398037701645,0.005174219470866827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),125.16666666666666,21685.0,m2,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c4,2,4,8,Room,bedrooms,A_structural,level,count,0.058,0.002,,,***,,,high,"Total number of rooms, not bedrooms; mapped to bedrooms as closest leaf",log sales price (SEK) of tenant-owned apartment,log,other,21695.0,0.943,se,Full sample; 4-digit postcode FE; robust regression (outlier-robust),semi_elasticity,5.800000000000001,0.2,100*b/1 (per unit count),reported,0.19322172634637602,0.006662818149875035,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.0,21685.0,count,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c5,2,5,8,Area,living_area,A_structural,log,m2,0.751,0.006,,,***,,,high,,log sales price (SEK) of tenant-owned apartment,log,other,21696.0,0.943,se,Full sample; 4-digit postcode FE; HIGH and LOW; robust regression,elasticity,0.751,0.006,b (log-log),reported,0.647631134460653,0.005174150208740237,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),125.16666666666666,21686.0,m2,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T2-c5,2,5,8,Room,bedrooms,A_structural,level,count,0.058,0.002,,,***,,,high,"Total number of rooms, not bedrooms; mapped to bedrooms as closest leaf",log sales price (SEK) of tenant-owned apartment,log,other,21696.0,0.943,se,Full sample; 4-digit postcode FE; HIGH and LOW; robust regression,semi_elasticity,5.800000000000001,0.2,100*b/1 (per unit count),reported,0.19321743762904284,0.006662670263070442,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.0,21686.0,count,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T3-c1,3,1,9,HIGH,energy_efficiency,A_structural,dummy,binary,0.004,0.006,,,,,,high,<= 75 kWh/m2 dummy,log sales price (SEK) of tenant-owned apartment,log,OLS,11468.0,0.913,se,Regional subsample: Stockholm; 4-digit postcode FE; robust SE; dwelling controls included but not reported,pct_premium,0.3989938695798001,0.6024048064064051,100*(exp(b - se^2/2) - 1),reported,0.006227961357189108,0.009341942035783663,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6666666666666666,11458.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T3-c2,3,2,9,HIGH,energy_efficiency,A_structural,dummy,binary,0.015,0.017,,,,,,high,<= 75 kWh/m2 dummy,log sales price (SEK) of tenant-owned apartment,log,OLS,4142.0,0.885,se,Regional subsample: South; 4-digit postcode FE; robust SE; dwelling controls included but not reported,pct_premium,1.4966391375278887,1.7256922098467222,100*(exp(b - se^2/2) - 1),reported,0.013725281817756866,0.015555319393457783,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8823529411764705,4132.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T3-c3,3,3,9,HIGH,energy_efficiency,A_structural,dummy,binary,0.002,0.008,,,,,,high,<= 75 kWh/m2 dummy,log sales price (SEK) of tenant-owned apartment,log,OLS,5285.0,0.912,se,Regional subsample: Mid; 4-digit postcode FE; robust SE; dwelling controls included but not reported,pct_premium,0.19699377829771603,0.8016016010672002,100*(exp(b - se^2/2) - 1),reported,0.0034421215624525553,0.013768486249810221,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.25,5275.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c1,4,1,10,AB,energy_efficiency,A_structural,dummy,binary,0.015,0.009,,,*,,,high,EPC grade A or B; reference C-G,log sales price (SEK) of tenant-owned apartment,log,OLS,6555.0,0.936,se,Graded sample (buildings with EPC grade); AB vs C-G; robust SE,pct_premium,1.507195336911038,0.9136017581541469,100*(exp(b - se^2/2) - 1),reported,0.02059689636394069,0.012358137818364414,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6666666666666667,6545.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c4,4,4,10,AB,energy_efficiency,A_structural,dummy,binary,0.01,0.008,,,,,,high,EPC grade A or B; reference C-G,log sales price (SEK) of tenant-owned apartment,log,other,6555.0,0.945,se,Graded sample; AB vs C-G; robust regression,pct_premium,1.001784599596145,0.8080401336673343,100*(exp(b - se^2/2) - 1),reported,0.015449106028584252,0.012359284822867403,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.25,6545.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c2,4,2,10,ABC,energy_efficiency,A_structural,dummy,binary,0.001,0.005,,,,,,high,EPC grade A-C; reference D-G,log sales price (SEK) of tenant-owned apartment,log,OLS,6555.0,0.936,se,Graded sample; ABC vs D-G; robust SE,pct_premium,0.09879877386591573,0.5005002500833542,100*(exp(b - se^2/2) - 1),reported,0.0024721444481789587,0.012360722240894791,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2,6545.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c3,4,3,10,ABC,energy_efficiency,A_structural,dummy,binary,0.002,0.006,,,,,,high,EPC grade A-C; reference D,log sales price (SEK) of tenant-owned apartment,log,OLS,6555.0,0.936,se,Graded sample; ABC and EFG vs D; robust SE,pct_premium,0.19839654602995527,0.6012012008004002,100*(exp(b - se^2/2) - 1),reported,0.004120218364175057,0.012360655092525171,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3333333333333333,6545.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c5,4,5,10,ABC,energy_efficiency,A_structural,dummy,binary,-0.001,0.006,,,,,,high,EPC grade A-C; reference D,log sales price (SEK) of tenant-owned apartment,log,other,6553.0,0.945,se,Graded sample; ABC and EFG vs D; robust regression,pct_premium,-0.10174820137849316,0.599400299900025,100*(exp(b - se^2/2) - 1),reported,-0.0020604371306068726,0.012362622783641235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.16666666666666666,6543.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c3,4,3,10,EFG,energy_efficiency,A_structural,dummy,binary,0.002,0.005,,,,,,high,EPC grade E-G; reference D,log sales price (SEK) of tenant-owned apartment,log,OLS,6555.0,0.936,se,Graded sample; ABC and EFG vs D; robust SE,pct_premium,0.19894763872647658,0.5010010006670002,100*(exp(b - se^2/2) - 1),reported,0.00494424357146234,0.012360608928655849,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4,6545.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c5,4,5,10,EFG,energy_efficiency,A_structural,dummy,binary,-0.002,0.005,,,,,,high,EPC grade E-G; reference D,log sales price (SEK) of tenant-owned apartment,log,other,6553.0,0.945,se,Graded sample; ABC and EFG vs D; robust regression,pct_premium,-0.201047627968165,0.49900099933366654,100*(exp(b - se^2/2) - 1),reported,-0.004944999149166611,0.012362497872916526,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4,6543.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c1,4,1,10,Area,living_area,A_structural,log,m2,0.749,0.023,,,***,,,high,,log sales price (SEK) of tenant-owned apartment,log,OLS,6555.0,0.936,se,Graded sample (buildings with EPC grade); AB vs C-G; robust SE,elasticity,0.749,0.023,b (log-log),reported,0.37341373243039067,0.011466643318957257,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.56521739130435,6545.0,m2,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c1,4,1,10,Room,bedrooms,A_structural,level,count,0.065,0.004,,,***,,,high,"Total number of rooms, not bedrooms; mapped to bedrooms as closest leaf",log sales price (SEK) of tenant-owned apartment,log,OLS,6555.0,0.936,se,Graded sample (buildings with EPC grade); AB vs C-G; robust SE,semi_elasticity,6.5,0.4,100*b/1 (per unit count),reported,0.1969290133594376,0.012118708514426929,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.25,6545.0,count,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c2,4,2,10,Area,living_area,A_structural,log,m2,0.75,0.023,,,***,,,high,,log sales price (SEK) of tenant-owned apartment,log,OLS,6555.0,0.936,se,Graded sample; ABC vs D-G; robust SE,elasticity,0.75,0.023,b (log-log),reported,0.3738426456347446,0.011464507799465501,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.608695652173914,6545.0,m2,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c2,4,2,10,Room,bedrooms,A_structural,level,count,0.065,0.004,,,***,,,high,"Total number of rooms, not bedrooms; mapped to bedrooms as closest leaf",log sales price (SEK) of tenant-owned apartment,log,OLS,6555.0,0.936,se,Graded sample; ABC vs D-G; robust SE,semi_elasticity,6.5,0.4,100*b/1 (per unit count),reported,0.1969290133594376,0.012118708514426929,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.25,6545.0,count,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c3,4,3,10,Area,living_area,A_structural,log,m2,0.75,0.023,,,***,,,high,,log sales price (SEK) of tenant-owned apartment,log,OLS,6555.0,0.936,se,Graded sample; ABC and EFG vs D; robust SE,elasticity,0.75,0.023,b (log-log),reported,0.3738426456347446,0.011464507799465501,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.608695652173914,6545.0,m2,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c3,4,3,10,Room,bedrooms,A_structural,level,count,0.065,0.004,,,***,,,high,"Total number of rooms, not bedrooms; mapped to bedrooms as closest leaf",log sales price (SEK) of tenant-owned apartment,log,OLS,6555.0,0.936,se,Graded sample; ABC and EFG vs D; robust SE,semi_elasticity,6.5,0.4,100*b/1 (per unit count),reported,0.1969290133594376,0.012118708514426929,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.25,6545.0,count,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c4,4,4,10,Area,living_area,A_structural,log,m2,0.75,0.012,,,***,,,high,,log sales price (SEK) of tenant-owned apartment,log,other,6555.0,0.945,se,Graded sample; AB vs C-G; robust regression,elasticity,0.75,0.012,b (log-log),reported,0.6113584216501162,0.009781734746401857,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),62.5,6545.0,m2,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c4,4,4,10,Room,bedrooms,A_structural,level,count,0.059,0.003,,,***,,,high,"Total number of rooms, not bedrooms; mapped to bedrooms as closest leaf",log sales price (SEK) of tenant-owned apartment,log,other,6555.0,0.945,se,Graded sample; AB vs C-G; robust regression,semi_elasticity,5.8999999999999995,0.3,100*b/1 (per unit count),reported,0.23621552688563624,0.012010958994184896,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.666666666666664,6545.0,count,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c5,4,5,10,Area,living_area,A_structural,log,m2,0.75,0.012,,,***,,,high,,log sales price (SEK) of tenant-owned apartment,log,other,6553.0,0.945,se,Graded sample; ABC and EFG vs D; robust regression,elasticity,0.75,0.012,b (log-log),reported,0.6114169262481257,0.00978267081997001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),62.5,6543.0,m2,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T4-c5,4,5,10,Room,bedrooms,A_structural,level,count,0.059,0.003,,,***,,,high,"Total number of rooms, not bedrooms; mapped to bedrooms as closest leaf",log sales price (SEK) of tenant-owned apartment,log,other,6553.0,0.945,se,Graded sample; ABC and EFG vs D; robust regression,semi_elasticity,5.8999999999999995,0.3,100*b/1 (per unit count),reported,0.2362496114542047,0.012012692107840919,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.666666666666664,6543.0,count,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T5-c1,5,1,11,HIGH,energy_efficiency,A_structural,dummy,binary,0.008,0.005,,,*,,,high,<= 75 kWh/m2 dummy,log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.935,se,Full sample; income-category dummies; 4-digit postcode FE,pct_premium,0.8019485181956831,0.5040160427521367,100*(exp(b - se^2/2) - 1),reported,0.01086437189872603,0.006790232436703768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6,21686.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T5-c2,5,2,11,HIGH,energy_efficiency,A_structural,dummy,binary,0.006,0.004,,,,,,high,<= 75 kWh/m2 dummy,log sales price (SEK) of tenant-owned apartment,log,other,21691.0,0.944,se,Full sample; income-category dummies; robust regression; 4-digit postcode FE,pct_premium,0.6009987941968831,0.40240721442162597,100*(exp(b - se^2/2) - 1),reported,0.010186595721122791,0.006791063814081862,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5,21681.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T5-c3,5,3,11,HIGH,energy_efficiency,A_structural,dummy,binary,-0.003,0.005,,,,,,high,<= 75 kWh/m2 dummy,log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.924,se,Full sample; neighbourhood controls (unreported); 3-digit postcode FE,pct_premium,-0.30079669749301097,0.4985022477516865,100*(exp(b - se^2/2) - 1),reported,-0.004074346109876248,0.006790576849793746,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6,21686.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T5-c4,5,4,11,HIGH,energy_efficiency,A_structural,dummy,binary,0.003,0.005,,,,,,high,<= 75 kWh/m2 dummy,log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.938,se,Full sample; neighbourhood controls (unreported); 4-digit postcode FE,pct_premium,0.2991967025430142,0.5015022522516885,100*(exp(b - se^2/2) - 1),reported,0.004074346109876248,0.006790576849793746,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6,21686.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T5-c5,5,5,11,HIGH,energy_efficiency,A_structural,dummy,binary,0.0,0.004,,,,,,high,<= 75 kWh/m2 dummy,log sales price (SEK) of tenant-owned apartment,log,other,21696.0,0.946,se,Full sample; neighbourhood controls (unreported); robust regression; 4-digit postcode FE,pct_premium,-0.0007999968000049762,0.4,100*(exp(b - se^2/2) - 1),reported,0.0,0.006790633213289102,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0,21686.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,other,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T6-c1,6,1,11,HIGH (≤ 50 kWh/m2),energy_efficiency,A_structural,dummy,binary,0.01,0.012,,,,,,high,Narrow boundary,log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.938,se,Full sample; HIGH defined as <= 50 kWh/m2; neighbourhood + dwelling controls; 4-digit postcode FE,pct_premium,0.9977446090125186,1.2120602005010015,100*(exp(b - se^2/2) - 1),reported,0.005658770407223558,0.006790524488668269,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8333333333333334,21686.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T6-c2,6,2,11,HIGH (≤ 100 kWh/m2),energy_efficiency,A_structural,dummy,binary,0.005,0.003,,,,,,high,Wide boundary,log sales price (SEK) of tenant-owned apartment,log,OLS,21696.0,0.938,se,Full sample; HIGH defined as <= 100 kWh/m2; neighbourhood + dwelling controls,pct_premium,0.5007998313232953,0.3015037562578203,100*(exp(b - se^2/2) - 1),reported,0.011316997243562096,0.006790198346137258,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6666666666666667,21686.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T8-c1,8,1,12,HIGH,energy_efficiency,A_structural,dummy,binary,0.009,0.005,,,*,,,high,<= 75 kWh/m2,log sales price (SEK) of tenant-owned apartment,log,OLS,16511.0,0.927,se,Full sample; propensity score (probit) included as covariate,pct_premium,0.9028008844926605,0.5045203108869339,100*(exp(b - se^2/2) - 1),reported,0.014011180886090095,0.007783989381161165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7999999999999998,16501.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T8-c2,8,2,12,HIGH,energy_efficiency,A_structural,dummy,binary,0.012,0.005,,,**,,,high,<= 75 kWh/m2,log sales price (SEK) of tenant-owned apartment,log,WLS,2754.0,0.911,se,"Full sample; nearest-neighbour PS-matched sample, weighted",pct_premium,1.205963804153476,0.5060361444330389,100*(exp(b - se^2/2) - 1),reported,0.04576820148524767,0.019070083952186533,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4,2744.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T8-c3,8,3,12,AB,energy_efficiency,A_structural,dummy,binary,0.011,0.009,,,,,,high,EPC grade A or B,log sales price (SEK) of tenant-owned apartment,log,OLS,3638.0,0.929,se,Graded sample; propensity score as covariate,pct_premium,1.1019775314645486,0.9099546502002475,100*(exp(b - se^2/2) - 1),reported,0.0202874351533894,0.016598810580045874,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2222222222222223,3628.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T8-c4,8,4,12,AB,energy_efficiency,A_structural,dummy,binary,0.014,0.009,,,,,,high,EPC grade A or B,log sales price (SEK) of tenant-owned apartment,log,WLS,788.0,0.939,se,"Graded sample; PS-matched sample, weighted",pct_premium,1.405738878258167,0.9126886130446429,100*(exp(b - se^2/2) - 1),reported,0.05568284283033449,0.035796113248072164,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5555555555555558,778.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T9-c1,9,1,13,HIGH,energy_efficiency,A_structural,dummy,binary,0.005,0.005,,,,,,high,<= 75 kWh/m2,log sales price (SEK) of tenant-owned apartment,log,WLS,17702.0,0.931,se,"Full sample after coarsened exact matching (CEM), weighted hedonic regression",pct_premium,0.4999958281406647,0.5025062604297005,100*(exp(b - se^2/2) - 1),reported,0.0075179470267321075,0.0075179470267321075,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,17692.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f,2bbd25e60ca8ea2625da98d69a5096e00200229f:T9-c2,9,2,13,AB,energy_efficiency,A_structural,dummy,binary,0.007,0.009,,,,,,high,EPC grade A or B,log sales price (SEK) of tenant-owned apartment,log,WLS,4373.0,0.933,se,"Graded sample after CEM, weighted hedonic regression",pct_premium,0.6983773598154164,0.9063221015401637,100*(exp(b - se^2/2) - 1),reported,0.011774238218514897,0.015138306280947722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7777777777777779,4363.0,binary,,2022.0,Sweden,Europe,High income,2019.0,2019.0,condo_apartment,transaction,journal,True,True,robust,,2019.0,ols,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Age,age,A_structural,log,years,0.0616,,15.2607,,,,,medium,Age of house (data section lists year built); positive coefficient as printed; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",elasticity,0.0616,0.004036512086601532,b (log-log),|b/t|,0.13617003682328652,0.008922922069320969,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.2607,12327.0,years,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Bathrooms,bathrooms,A_structural,log,count,0.0286,,1.9343,,,,,medium,Number of bathrooms; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",elasticity,0.0286,0.014785710592979373,b (log-log),|b/t|,0.017419241283239004,0.009005449663050717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9343,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Bedrooms,bedrooms,A_structural,log,count,0.086,,5.1746,,,,,medium,Number of bedrooms; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",elasticity,0.086,0.016619642097939938,b (log-log),|b/t|,0.04655613452786352,0.008997049922286462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.1746,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Dock,waterfront,C_exterior,dummy,binary,0.2154,,5.5903,,,,,high,Presence of a dock (water access),log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",pct_premium,23.94375400547686,4.779226525869481,100*(exp(b - se^2/2) - 1),|b/t|,0.05028710113380218,0.008995420842137664,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.5903,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Square feet,living_area,A_structural,log,sqft,0.7462,,41.7834,,,,,medium,House square footage; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",elasticity,0.7462,0.017858766878712597,b (log-log),|b/t|,0.35221894214068855,0.008429638137171425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),41.7834,12327.0,sqft,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Central air,air_conditioning,A_structural,dummy,binary,0.1035,,6.461,,,,,high,Presence of central air conditioning,log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",pct_premium,10.890350386959913,1.776601758447369,100*(exp(b - se^2/2) - 1),|b/t|,0.05809475592793831,0.00899160438445106,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.461,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Lot size,lot_size,A_structural,log,acres,0.0046,,1.5806,,,,,medium,"Lot size; unit (acres) inferred from the 0.10-acre price-change exercise, not stated in table; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",elasticity,0.0046,0.0029102872326964443,b (log-log),|b/t|,0.014234731348383177,0.009005903674796392,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5806,12327.0,acre,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Adjacent golf,green_space,E_environment,dummy,binary,0.0163,,0.6336,,,,,high,Parcel shares a border with a golf course (fixed open space type),log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",pct_premium,1.6097273494849018,2.6148780282190507,100*(exp(b - se^2/2) - 1),|b/t|,0.005706625844883544,0.009006669578414683,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6336,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Distance fixed,green_space,E_environment,log,miles,-0.0316,,-16.7966,,,,,medium,"Distance to nearest fixed open space (parks, large water bodies, golf courses); unit inferred (miles), not stated; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",elasticity,-0.0316,0.0018813331269423575,b (log-log),|b/t|,-0.14958184702665084,0.008905483670900707,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.7966,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Adjacent fixed,green_space,E_environment,dummy,binary,-0.1379,,-2.0083,,,,,high,"Parcel adjacent to fixed open space (golf course, resource protection area or park)",log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",pct_premium,-13.086554673834483,5.982000828728144,100*(exp(b - se^2/2) - 1),|b/t|,-0.018085430603751985,0.009005343127895226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0083,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Distance historic,neighbourhood_amenities,F_neighbourhood,log,miles,-0.0489,,-6.4415,,,,,medium,"Distance to nearest historic area (Jamestown, Yorktown, Colonial Williamsburg etc.); cultural amenity; unit inferred (miles); entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",elasticity,-0.0489,0.0075913995187456345,b (log-log),|b/t|,-0.057920008735210006,0.008991695837182335,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.4415,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Adjacent historic,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.5175,,-5.3227,,,,,high,Parcel adjacent to a historic area,log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",pct_premium,-40.680159605596025,5.794700185740714,100*(exp(b - se^2/2) - 1),|b/t|,-0.04788558465651213,0.008996483862797477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.3227,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,True
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Distance water,water_proximity,E_environment,log,miles,0.024,,4.2566,,,,,medium,Distance to nearest open water; unit inferred (miles); entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",elasticity,0.024,0.005638302870835879,b (log-log),|b/t|,0.03831026945897289,0.009000204261375953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.2566,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c1,1,1 Strict Contiguity,13,Adjacent water,waterfront,C_exterior,dummy,binary,0.274,,4.5128,,,,,high,Parcel adjacent to open water,log sale price (2004 dollars),log,spatial_error,12337.0,0.56,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Strict Contiguity",pct_premium,31.279279490248648,7.985482534422322,100*(exp(b - se^2/2) - 1),|b/t|,0.04061242637826273,0.00899938538784407,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5128,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Age,age,A_structural,log,years,0.0657,,16.5206,,,,,medium,Age of house (data section lists year built); positive coefficient as printed; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",elasticity,0.0657,0.003976853140927084,b (log-log),|b/t|,0.14717760995485718,0.008908732730945435,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.5206,12327.0,years,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Bathrooms,bathrooms,A_structural,log,count,0.0169,,1.1437,,,,,medium,Number of bathrooms; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",elasticity,0.0169,0.01477660225583632,b (log-log),|b/t|,0.010300549234374136,0.00900633840550331,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1437,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Bedrooms,bedrooms,A_structural,log,count,0.1049,,5.4593,,,,,medium,Number of bedrooms; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",elasticity,0.1049,0.019214917663436703,b (log-log),|b/t|,0.04911157725876088,0.008995947696364163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.4593,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Dock,waterfront,C_exterior,dummy,binary,0.1814,,4.8653,,,,,high,Presence of a dock (water access),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",pct_premium,19.80616212728674,4.470011878464146,100*(exp(b - se^2/2) - 1),|b/t|,0.043778849628308705,0.008998180919636755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.8653,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Square feet,living_area,A_structural,log,sqft,0.681,,39.3776,,,,,medium,House square footage; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",elasticity,0.681,0.017294096135874203,b (log-log),|b/t|,0.3342659447337591,0.008488733308626201,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),39.3776,12327.0,sqft,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Central air,air_conditioning,A_structural,dummy,binary,0.1171,,7.1324,,,,,high,Presence of central air conditioning,log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",pct_premium,12.408033804567054,1.8457678945863583,100*(exp(b - se^2/2) - 1),|b/t|,0.06410807154600548,0.008988288871348421,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.1324,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Lot size,lot_size,A_structural,log,acres,0.006,,1.7832,,,,,medium,"Lot size; unit (acres) inferred from the 0.10-acre price-change exercise, not stated in table; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",elasticity,0.006,0.0033647375504710637,b (log-log),|b/t|,0.016058883616282577,0.009005654787058422,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7832,12327.0,acre,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Adjacent golf,green_space,E_environment,dummy,binary,0.0703,,2.4266,,,,,high,Parcel shares a border with a golf course (fixed open space type),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",pct_premium,7.237986639388416,3.108050265100677,100*(exp(b - se^2/2) - 1),|b/t|,0.021850722050961613,0.009004665808522877,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4266,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Distance fixed,green_space,E_environment,log,miles,-0.0283,,-15.1693,,,,,medium,"Distance to nearest fixed open space (parks, large water bodies, golf courses); unit inferred (miles), not stated; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",elasticity,-0.0283,0.0018656101468096748,b (log-log),|b/t|,-0.13536947090039608,0.008923910193640847,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.1693,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Adjacent fixed,green_space,E_environment,dummy,binary,-0.0995,,-1.3958,,,,,high,"Parcel adjacent to fixed open space (golf course, resource protection area or park)",log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",pct_premium,-9.700728747190501,6.453385156320142,100*(exp(b - se^2/2) - 1),|b/t|,-0.01257072075242873,0.0090061045654311,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3958,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Distance historic,neighbourhood_amenities,F_neighbourhood,log,miles,-0.0444,,-5.1727,,,,,medium,"Distance to nearest historic area (Jamestown, Yorktown, Colonial Williamsburg etc.); cultural amenity; unit inferred (miles); entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",elasticity,-0.0444,0.008583525044947514,b (log-log),|b/t|,-0.04653907716430166,0.008997057081273156,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.1727,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Adjacent historic,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.4934,,-4.8451,,,,,high,Parcel adjacent to a historic area,log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",pct_premium,-39.261059375309124,6.217495830801905,100*(exp(b - se^2/2) - 1),|b/t|,-0.04359743257653115,0.008998252373848041,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.8451,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,True
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Distance water,water_proximity,E_environment,log,miles,0.0199,,3.229,,,,,medium,Distance to nearest open water; unit inferred (miles); entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",elasticity,0.0199,0.006162898730257046,b (log-log),|b/t|,0.029070717905305188,0.009003009571169151,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.229,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c2,1,2 200-meter Contiguity,13,Adjacent water,waterfront,C_exterior,dummy,binary,0.2564,,3.9774,,,,,high,Parcel adjacent to open water,log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 200-meter Contiguity",pct_premium,28.958721911545737,8.33051511297538,100*(exp(b - se^2/2) - 1),|b/t|,0.03580074602783284,0.009001042396498427,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9774,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Age,age,A_structural,log,years,0.053,,13.5754,,,,,medium,Age of house (data section lists year built); positive coefficient as printed; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",elasticity,0.053,0.003904120688893145,b (log-log),|b/t|,0.1213672645939632,0.008940234880295475,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.5754,12327.0,years,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Bathrooms,bathrooms,A_structural,log,count,0.0101,,0.6857,,,,,medium,Number of bathrooms; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",elasticity,0.0101,0.014729473530698556,b (log-log),|b/t|,0.006175856112172244,0.00900664446867762,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6857,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Bedrooms,bedrooms,A_structural,log,count,0.12,,6.3163,,,,,medium,Number of bedrooms; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",elasticity,0.12,0.01899846429080316,b (log-log),|b/t|,0.056797915997789536,0.008992276490633683,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.3163,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Dock,waterfront,C_exterior,dummy,binary,0.2231,,5.9027,,,,,high,Presence of a dock (water access),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",pct_premium,24.905307128548436,4.724327085769552,100*(exp(b - se^2/2) - 1),|b/t|,0.05308955917369604,0.008994114417757304,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9027,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Square feet,living_area,A_structural,log,sqft,0.7053,,38.7594,,,,,medium,House square footage; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",elasticity,0.7053,0.018196876112633324,b (log-log),|b/t|,0.32959232231746793,0.00850354552231118,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),38.7594,12327.0,sqft,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Central air,air_conditioning,A_structural,dummy,binary,0.0919,,5.6053,,,,,high,Presence of central air conditioning,log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",pct_premium,9.610786291418648,1.797332026123044,100*(exp(b - se^2/2) - 1),|b/t|,0.05042168986207548,0.008995359724203072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.6053,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Lot size,lot_size,A_structural,log,acres,0.012,,3.4345,,,,,medium,"Lot size; unit (acres) inferred from the 0.10-acre price-change exercise, not stated in table; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",elasticity,0.012,0.003493958363662833,b (log-log),|b/t|,0.03091912054027778,0.009002509984066905,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4345,12327.0,acre,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Adjacent golf,green_space,E_environment,dummy,binary,0.0395,,1.3148,,,,,high,Parcel shares a border with a golf course (fixed open space type),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",pct_premium,3.98211438872893,3.1253023049859934,100*(exp(b - se^2/2) - 1),|b/t|,0.01184133172056785,0.009006184758570011,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3148,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Distance fixed,green_space,E_environment,log,miles,-0.0289,,-16.0611,,,,,medium,"Distance to nearest fixed open space (parks, large water bodies, golf courses); unit inferred (miles), not stated; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",elasticity,-0.0289,0.0017993786228838622,b (log-log),|b/t|,-0.14316912963334263,0.0089140301494507,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.0611,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Adjacent fixed,green_space,E_environment,dummy,binary,-0.1498,,-2.3457,,,,,high,"Parcel adjacent to fixed open space (golf course, resource protection area or park)",log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",pct_premium,-14.087353795166791,5.497712591478039,100*(exp(b - se^2/2) - 1),|b/t|,-0.021122575209034572,0.009004806756633232,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3457,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Distance historic,neighbourhood_amenities,F_neighbourhood,log,miles,-0.0265,,-2.5745,,,,,medium,"Distance to nearest historic area (Jamestown, Yorktown, Colonial Williamsburg etc.); cultural amenity; unit inferred (miles); entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",elasticity,-0.0265,0.010293260827345115,b (log-log),|b/t|,-0.02318181697188166,0.009004395794088817,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5745,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Adjacent historic,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.2972,,-2.6345,,,,,high,Parcel adjacent to a historic area,log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",pct_premium,-26.181671831308872,8.38066116356929,100*(exp(b - se^2/2) - 1),|b/t|,-0.023721780160836016,0.009004281708421338,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6345,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Distance water,water_proximity,E_environment,log,miles,0.0185,,2.648,,,,,medium,Distance to nearest open water; unit inferred (miles); entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",elasticity,0.0185,0.006986404833836857,b (log-log),|b/t|,0.02384326903416647,0.009004255677555313,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.648,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c3,1,3 400-meter Contiguity,13,Adjacent water,waterfront,C_exterior,dummy,binary,0.265,,3.814,,,,,high,Parcel adjacent to open water,log sale price (2004 dollars),log,spatial_error,12337.0,0.57,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 400-meter Contiguity",pct_premium,30.02885547739107,9.056350513405027,100*(exp(b - se^2/2) - 1),|b/t|,0.034331746340227176,0.00900150664400293,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.814,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Age,age,A_structural,log,years,0.0478,,12.0331,,,,,medium,Age of house (data section lists year built); positive coefficient as printed; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",elasticity,0.0478,0.0039723761956603045,b (log-log),|b/t|,0.10774894719476605,0.008954379768701835,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0331,12327.0,years,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Bathrooms,bathrooms,A_structural,log,count,0.0134,,0.9073,,,,,medium,Number of bathrooms; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",elasticity,0.0134,0.014769095117381241,b (log-log),|b/t|,0.00817161152634583,0.009006515514544063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9073,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Bedrooms,bedrooms,A_structural,log,count,0.1305,,7.4568,,,,,medium,Number of bedrooms; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",elasticity,0.1305,0.01750080463469585,b (log-log),|b/t|,0.06701106268479361,0.008986571006972643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.4568,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Dock,waterfront,C_exterior,dummy,binary,0.2198,,5.6961,,,,,high,Presence of a dock (water access),log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",pct_premium,24.490035507086418,4.807375104499882,100*(exp(b - se^2/2) - 1),|b/t|,0.05123634139389025,0.008994986287791691,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.6961,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Square feet,living_area,A_structural,log,sqft,0.7546,,42.7783,,,,,medium,House square footage; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",elasticity,0.7546,0.017639784657174317,b (log-log),|b/t|,0.35953251049322327,0.008404553488409386,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.7783,12327.0,sqft,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Central air,air_conditioning,A_structural,dummy,binary,0.0926,,5.6566,,,,,high,Presence of central air conditioning,log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",pct_premium,9.687585518822072,1.795854662377801,100*(exp(b - se^2/2) - 1),|b/t|,0.05088196250643488,0.008995149472551513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.6566,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Lot size,lot_size,A_structural,log,acres,0.0121,,3.6175,,,,,medium,"Lot size; unit (acres) inferred from the 0.10-acre price-change exercise, not stated in table; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",elasticity,0.0121,0.003344851416724257,b (log-log),|b/t|,0.03256487692987019,0.009002039234241931,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6175,12327.0,acre,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Adjacent golf,green_space,E_environment,dummy,binary,-0.0061,,-0.2161,,,,,high,Parcel shares a border with a golf course (fixed open space type),log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",pct_premium,-0.6477331800559871,2.805600768203364,100*(exp(b - se^2/2) - 1),|b/t|,-0.0019463693017567308,0.00900679917518154,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2161,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Distance fixed,green_space,E_environment,log,miles,-0.0291,,-16.4908,,,,,medium,"Distance to nearest fixed open space (parks, large water bodies, golf courses); unit inferred (miles), not stated; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",elasticity,-0.0291,0.0017646202731219833,b (log-log),|b/t|,-0.14691786513856364,0.008909080526024429,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.4908,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Adjacent fixed,green_space,E_environment,dummy,binary,-0.1727,,-2.6857,,,,,high,"Parcel adjacent to fixed open space (golf course, resource protection area or park)",log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",pct_premium,-16.03477594506556,5.410434968948365,100*(exp(b - se^2/2) - 1),|b/t|,-0.0241825323509895,0.009004182280593326,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6857,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Distance historic,neighbourhood_amenities,F_neighbourhood,log,miles,-0.0095,,-0.913,,,,,medium,"Distance to nearest historic area (Jamestown, Yorktown, Colonial Williamsburg etc.); cultural amenity; unit inferred (miles); entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",elasticity,-0.0095,0.010405257393209199,b (log-log),|b/t|,-0.00822294520435934,0.009006511724380438,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.913,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Adjacent historic,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.1366,,-1.1847,,,,,high,Parcel adjacent to a historic area,log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",pct_premium,-13.346037685267543,10.058140193548011,100*(exp(b - se^2/2) - 1),|b/t|,-0.010669767798342826,0.009006303535361547,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1847,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Distance water,water_proximity,E_environment,log,miles,0.0274,,3.9995,,,,,medium,Distance to nearest open water; unit inferred (miles); entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",elasticity,0.0274,0.006850856357044631,b (log-log),|b/t|,0.03599941198029344,0.009000978117338026,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9995,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T1-c4,1,4 600-meter Contiguity,13,Adjacent water,waterfront,C_exterior,dummy,binary,0.3246,,4.7136,,,,,high,Parcel adjacent to open water,log sale price (2004 dollars),log,spatial_error,12337.0,0.55,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: 600-meter Contiguity",pct_premium,38.02005794602186,9.527254775161108,100*(exp(b - se^2/2) - 1),|b/t|,0.04241632090389059,0.008998710307172987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.7136,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c1,2,1 Strict Contiguity,14,Age,age,A_structural,level,years,0.0017,,4.5662,,,,,medium,Age of house (data section lists year built); positive coefficient as printed,log sale price (2004 dollars),log,spatial_error,12337.0,0.5236,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Strict Contiguity",semi_elasticity,0.16999999999999998,0.03723008190618019,100*b/1 (per year),|b/t|,0.041092186824701254,0.008999208712868741,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5662,12327.0,years,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c1,2,1 Strict Contiguity,14,Bathrooms,bathrooms,A_structural,level,count,0.0052,,0.7222,,,,,high,Number of bathrooms,log sale price (2004 dollars),log,spatial_error,12337.0,0.5236,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Strict Contiguity",semi_elasticity,0.52,0.7200221545278316,100*b/1 (per unit count),|b/t|,0.006504585077771182,0.009006625696166134,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7222,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c1,2,1 Strict Contiguity,14,Bedrooms,bedrooms,A_structural,level,count,0.0336,,13.0655,,,,,high,Number of bedrooms,log sale price (2004 dollars),log,spatial_error,12337.0,0.5236,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Strict Contiguity",semi_elasticity,3.36,0.25716581837664076,100*b/1 (per unit count),|b/t|,0.11687210328403942,0.00894509228763074,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0655,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c1,2,1 Strict Contiguity,14,Dock,waterfront,C_exterior,dummy,binary,0.27,,6.7807,,,,,high,Presence of a dock (water access),log sale price (2004 dollars),log,spatial_error,12337.0,0.5236,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Strict Contiguity",pct_premium,30.892635873037698,5.216134052501611,100*(exp(b - se^2/2) - 1),|b/t|,0.060958940727726195,0.008990066029720559,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.7807,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c1,2,1 Strict Contiguity,14,Square feet,living_area,A_structural,level,sqft,0.0002,,35.8411,,,,,high,House square footage,log sale price (2004 dollars),log,spatial_error,12337.0,0.5236,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Strict Contiguity",semi_elasticity,0.21527820833419445,0.006006462087776169,100*b/0.092903 (X per sqft->m2),|b/t|,0.3072040869746576,0.00857127953591429,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.8411,12327.0,sqft,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c1,2,1 Strict Contiguity,14,Central air,air_conditioning,A_structural,dummy,binary,0.1409,,7.9052,,,,,high,Presence of central air conditioning,log sale price (2004 dollars),log,spatial_error,12337.0,0.5236,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Strict Contiguity",pct_premium,15.112664910762753,2.0520607971830183,100*(exp(b - se^2/2) - 1),|b/t|,0.07102088975941993,0.008984072478801288,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.9052,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c1,2,1 Strict Contiguity,14,Lot size,lot_size,A_structural,level,acres,0.0164,,1.4767,,,,,medium,"Lot size; unit (acres) inferred from the 0.10-acre price-change exercise, not stated in table",log sale price (2004 dollars),log,spatial_error,12337.0,0.5236,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Strict Contiguity",semi_elasticity,0.0004052528256061512,0.0002744313845778772,100*b/4046.86 (X per acre->m2),|b/t|,0.013299189275823043,0.009006019689729155,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4767,12327.0,acre,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c1,2,1 Strict Contiguity,14,Adjacent golf,green_space,E_environment,dummy,binary,0.1628,,6.1477,,,,,high,Parcel shares a border with a golf course (fixed open space type),log sale price (2004 dollars),log,spatial_error,12337.0,0.5236,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Strict Contiguity",pct_premium,17.638875219813286,3.1163402996054153,100*(exp(b - se^2/2) - 1),|b/t|,0.055286515629554,0.00899304058909088,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.1477,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c1,2,1 Strict Contiguity,14,Adjacent fixed,green_space,E_environment,dummy,binary,-0.0374,,-0.5251,,,,,high,"Parcel adjacent to fixed open space (golf course, resource protection area or park)",log sale price (2004 dollars),log,spatial_error,12337.0,0.5236,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Strict Contiguity",pct_premium,-3.9149516824738106,6.860992906113953,100*(exp(b - se^2/2) - 1),|b/t|,-0.004729426311820209,0.009006715505275584,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5251,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c1,2,1 Strict Contiguity,14,Adjacent historic,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.017,,0.2389,,,,,high,Parcel adjacent to a historic area,log sale price (2004 dollars),log,spatial_error,12337.0,0.5236,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Strict Contiguity",pct_premium,1.4573334617687506,7.2379533191833785,100*(exp(b - se^2/2) - 1),|b/t|,0.0021517234175444664,0.009006795385284498,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2389,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c1,2,1 Strict Contiguity,14,Distance water,water_proximity,E_environment,level,miles,-0.0005,,-0.0355,,,,,medium,Distance to nearest open water; unit inferred (miles),log sale price (2004 dollars),log,spatial_error,12337.0,0.5236,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Strict Contiguity",semi_elasticity,-0.0310685596118667,0.8751706932920197,100*b/1.60934 (X per miles->km),|b/t|,-0.00031974196002293107,0.009006815775293832,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.0355,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c1,2,1 Strict Contiguity,14,Adjacent water,waterfront,C_exterior,dummy,binary,0.1557,,4.6742,,,,,high,Parcel adjacent to open water,log sale price (2004 dollars),log,spatial_error,12337.0,0.5236,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Strict Contiguity",pct_premium,16.782752302722482,3.892252195834757,100*(exp(b - se^2/2) - 1),|b/t|,0.04206240164143918,0.008998845073261558,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.6742,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c2,2,2 200-meter Contiguity,14,Age,age,A_structural,level,years,0.0015,,3.7826,,,,,medium,Age of house (data section lists year built); positive coefficient as printed,log sale price (2004 dollars),log,spatial_error,12337.0,0.5418,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 200-meter Contiguity",semi_elasticity,0.15,0.03965526357531857,100*b/1 (per year),|b/t|,0.03404942808111245,0.00900159363430245,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.7826,12327.0,years,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c2,2,2 200-meter Contiguity,14,Bathrooms,bathrooms,A_structural,level,count,0.0048,,0.6573,,,,,high,Number of bathrooms,log sale price (2004 dollars),log,spatial_error,12337.0,0.5418,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 200-meter Contiguity",semi_elasticity,0.48,0.7302601551802829,100*b/1 (per unit count),|b/t|,0.005920076567629075,0.009006658401991594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6573,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c2,2,2 200-meter Contiguity,14,Bedrooms,bedrooms,A_structural,level,count,0.0296,,11.4472,,,,,high,Number of bedrooms,log sale price (2004 dollars),log,spatial_error,12337.0,0.5418,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 200-meter Contiguity",semi_elasticity,2.96,0.25857851701726187,100*b/1 (per unit count),|b/t|,0.1025591560193025,0.00895932245608555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.4472,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c2,2,2 200-meter Contiguity,14,Dock,waterfront,C_exterior,dummy,binary,0.2326,,6.0702,,,,,high,Presence of a dock (water access),log sale price (2004 dollars),log,spatial_error,12337.0,0.5418,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 200-meter Contiguity",pct_premium,26.09505639028098,4.8353020263903534,100*(exp(b - se^2/2) - 1),|b/t|,0.054591645318832795,0.008993384949232776,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0702,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c2,2,2 200-meter Contiguity,14,Square feet,living_area,A_structural,level,sqft,0.0002,,29.6874,,,,,high,House square footage,log sale price (2004 dollars),log,spatial_error,12337.0,0.5418,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 200-meter Contiguity",semi_elasticity,0.21527820833419445,0.007251500917365429,100*b/0.092903 (X per sqft->m2),|b/t|,0.2583140424901331,0.00870113389822393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.6874,12327.0,sqft,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c2,2,2 200-meter Contiguity,14,Central air,air_conditioning,A_structural,dummy,binary,0.1412,,8.0795,,,,,high,Presence of central air conditioning,log sale price (2004 dollars),log,spatial_error,12337.0,0.5418,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 200-meter Contiguity",pct_premium,15.147909894940415,2.0126700882399273,100*(exp(b - se^2/2) - 1),|b/t|,0.07257865335369054,0.008983062485759087,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0795,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c2,2,2 200-meter Contiguity,14,Lot size,lot_size,A_structural,level,acres,0.0247,,2.2378,,,,,medium,"Lot size; unit (acres) inferred from the 0.10-acre price-change exercise, not stated in table",log sale price (2004 dollars),log,spatial_error,12337.0,0.5418,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 200-meter Contiguity",semi_elasticity,0.0006103502922238984,0.0002727456842541328,100*b/4046.86 (X per acre->m2),|b/t|,0.02015136062031847,0.009004987318043825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2378,12327.0,acre,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c2,2,2 200-meter Contiguity,14,Adjacent golf,green_space,E_environment,dummy,binary,0.2005,,6.5199,,,,,high,Parcel shares a border with a golf course (fixed open space type),log sale price (2004 dollars),log,spatial_error,12337.0,0.5418,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 200-meter Contiguity",pct_premium,22.14359283453977,3.757936920108112,100*(exp(b - se^2/2) - 1),|b/t|,0.05862254957520138,0.008991326488934092,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.5199,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c2,2,2 200-meter Contiguity,14,Adjacent fixed,green_space,E_environment,dummy,binary,0.0028,,0.0381,,,,,high,"Parcel adjacent to fixed open space (golf course, resource protection area or park)",log sale price (2004 dollars),log,spatial_error,12337.0,0.5418,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 200-meter Contiguity",pct_premium,0.009955510993697736,7.369687627956539,100*(exp(b - se^2/2) - 1),|b/t|,0.00034315967837515043,0.009006815705384525,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0381,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c2,2,2 200-meter Contiguity,14,Adjacent historic,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0202,,-0.2998,,,,,high,Parcel adjacent to a historic area,log sale price (2004 dollars),log,spatial_error,12337.0,0.5418,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 200-meter Contiguity",pct_premium,-2.2219346163425135,6.603086589102788,100*(exp(b - se^2/2) - 1),|b/t|,-0.002700233663353524,0.00900678340011182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2998,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c2,2,2 200-meter Contiguity,14,Distance water,water_proximity,E_environment,level,miles,0.0019,,0.1194,,,,,medium,Distance to nearest open water; unit inferred (miles),log sale price (2004 dollars),log,spatial_error,12337.0,0.5418,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 200-meter Contiguity",semi_elasticity,0.11806052652509345,0.9887816291883874,100*b/1.60934 (X per miles->km),|b/t|,0.0010754132366769384,0.009006811027445044,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.1194,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c2,2,2 200-meter Contiguity,14,Adjacent water,waterfront,C_exterior,dummy,binary,0.167,,5.1277,,,,,high,Parcel adjacent to open water,log sale price (2004 dollars),log,spatial_error,12337.0,0.5418,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 200-meter Contiguity",pct_premium,18.112769508725847,3.8487618680206794,100*(exp(b - se^2/2) - 1),|b/t|,0.04613507510719028,0.00899722587265056,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.1277,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c3,2,3 400-meter Contiguity,14,Age,age,A_structural,level,years,0.0005,,1.4055,,,,,medium,Age of house (data section lists year built); positive coefficient as printed,log sale price (2004 dollars),log,spatial_error,12337.0,0.5372,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 400-meter Contiguity",semi_elasticity,0.05,0.03557452863749556,100*b/1 (per year),|b/t|,0.012658066017733557,0.009006094640863434,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4055,12327.0,years,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c3,2,3 400-meter Contiguity,14,Bathrooms,bathrooms,A_structural,level,count,-0.0034,,-0.4631,,,,,high,Number of bathrooms,log sale price (2004 dollars),log,spatial_error,12337.0,0.5372,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 400-meter Contiguity",semi_elasticity,-0.33999999999999997,0.7341826819261498,100*b/1 (per unit count),|b/t|,-0.004171020315802711,0.009006737887719092,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4631,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c3,2,3 400-meter Contiguity,14,Bedrooms,bedrooms,A_structural,level,count,0.0354,,13.0245,,,,,high,Number of bedrooms,log sale price (2004 dollars),log,spatial_error,12337.0,0.5372,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 400-meter Contiguity",semi_elasticity,3.54,0.2717954623977888,100*b/1 (per unit count),|b/t|,0.11651034071933383,0.008945475121450637,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0245,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c3,2,3 400-meter Contiguity,14,Dock,waterfront,C_exterior,dummy,binary,0.2801,,7.1615,,,,,high,Presence of a dock (water access),log sale price (2004 dollars),log,spatial_error,12337.0,0.5372,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 400-meter Contiguity",pct_premium,32.22503939979819,5.175531985685468,100*(exp(b - se^2/2) - 1),|b/t|,0.06436854922396044,0.008988137851561887,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.1615,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c3,2,3 400-meter Contiguity,14,Square feet,living_area,A_structural,level,sqft,0.0002,,29.8074,,,,,high,House square footage,log sale price (2004 dollars),log,spatial_error,12337.0,0.5372,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 400-meter Contiguity",semi_elasticity,0.21527820833419445,0.007222307491904508,100*b/0.092903 (X per sqft->m2),|b/t|,0.2592881127885074,0.008698783281618236,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.8074,12327.0,sqft,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c3,2,3 400-meter Contiguity,14,Central air,air_conditioning,A_structural,dummy,binary,0.1097,,6.1635,,,,,high,Presence of central air conditioning,log sale price (2004 dollars),log,spatial_error,12337.0,0.5372,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 400-meter Contiguity",pct_premium,11.57664967283203,1.9861924738865104,100*(exp(b - se^2/2) - 1),|b/t|,0.05542816968800274,0.008992969852843796,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.1635,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c3,2,3 400-meter Contiguity,14,Lot size,lot_size,A_structural,level,acres,0.0164,,1.4318,,,,,medium,"Lot size; unit (acres) inferred from the 0.10-acre price-change exercise, not stated in table",log sale price (2004 dollars),log,spatial_error,12337.0,0.5372,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 400-meter Contiguity",semi_elasticity,0.0004052528256061512,0.0002830373135955798,100*b/4046.86 (X per acre->m2),|b/t|,0.012894887283764636,0.009006067386342112,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4318,12327.0,acre,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c3,2,3 400-meter Contiguity,14,Adjacent golf,green_space,E_environment,dummy,binary,0.1573,,5.0233,,,,,high,Parcel shares a border with a golf course (fixed open space type),log sale price (2004 dollars),log,spatial_error,12337.0,0.5372,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 400-meter Contiguity",pct_premium,16.977300165825504,3.6648324894447053,100*(exp(b - se^2/2) - 1),|b/t|,0.045197703478094785,0.00899761182451671,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0233,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c3,2,3 400-meter Contiguity,14,Adjacent fixed,green_space,E_environment,dummy,binary,-0.0427,,-0.6496,,,,,high,"Parcel adjacent to fixed open space (golf course, resource protection area or park)",log sale price (2004 dollars),log,spatial_error,12337.0,0.5372,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 400-meter Contiguity",pct_premium,-4.386904947810921,6.298505086450091,100*(exp(b - se^2/2) - 1),|b/t|,-0.005850727685967398,0.009006662078151784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6496,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c3,2,3 400-meter Contiguity,14,Adjacent historic,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0374,,0.574,,,,,high,Parcel adjacent to a historic area,log sale price (2004 dollars),log,spatial_error,12337.0,0.5372,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 400-meter Contiguity",pct_premium,3.590692189470679,6.763980134517483,100*(exp(b - se^2/2) - 1),|b/t|,0.005169843429977262,0.009006695871040526,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.574,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c3,2,3 400-meter Contiguity,14,Distance water,water_proximity,E_environment,level,miles,0.003,,0.1373,,,,,medium,Distance to nearest open water; unit inferred (miles),log sale price (2004 dollars),log,spatial_error,12337.0,0.5372,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 400-meter Contiguity",semi_elasticity,0.18641135767120018,1.3576937922155874,100*b/1.60934 (X per miles->km),|b/t|,0.0012366349235886148,0.009006809348788163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.1373,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T2-c3,2,3 400-meter Contiguity,14,Adjacent water,waterfront,C_exterior,dummy,binary,0.193,,5.9676,,,,,high,Parcel adjacent to open water,log sale price (2004 dollars),log,spatial_error,12337.0,0.5372,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: 400-meter Contiguity",pct_premium,21.22486457221524,3.9226218102619157,100*(exp(b - se^2/2) - 1),|b/t|,0.053671604834570986,0.008993834176984213,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9676,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Age,age,A_structural,log,years,0.0603,,14.9488,,,,,medium,Age of house (data section lists year built); positive coefficient as printed; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",elasticity,0.0603,0.004033768596810447,b (log-log),|b/t|,0.13343703859871045,0.008926270911291239,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.9488,12327.0,years,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Bathrooms,bathrooms,A_structural,log,count,0.0142,,0.9694,,,,,medium,Number of bathrooms; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",elasticity,0.0142,0.014648236022281824,b (log-log),|b/t|,0.008730874870527854,0.009006472942570513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9694,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Bedrooms,bedrooms,A_structural,log,count,0.1059,,5.3971,,,,,medium,Number of bedrooms; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",elasticity,0.1059,0.01962164866317096,b (log-log),|b/t|,0.048553355989217326,0.008996193509332295,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.3971,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Dock,waterfront,C_exterior,dummy,binary,0.2008,,5.3418,,,,,high,Presence of a dock (water access),log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",pct_premium,22.15169447704919,4.594967211071576,100*(exp(b - se^2/2) - 1),|b/t|,0.04805702136208362,0.008996409704984016,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.3418,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Square feet,living_area,A_structural,log,sqft,0.6713,,38.6585,,,,,medium,House square footage; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",elasticity,0.6713,0.01736487447779919,b (log-log),|b/t|,0.3288271966066714,0.008505948151290698,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),38.6585,12327.0,sqft,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Central air,air_conditioning,A_structural,dummy,binary,0.1066,,6.4215,,,,,high,Presence of central air conditioning,log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",pct_premium,11.233589268741762,1.8467857276449906,100*(exp(b - se^2/2) - 1),|b/t|,0.05774077531479171,0.008991789350586579,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.4215,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Lot size,lot_size,A_structural,log,acres,0.016,,3.8439,,,,,medium,"Lot size; unit (acres) inferred from the 0.10-acre price-change exercise, not stated in table; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",elasticity,0.016,0.004162439189364968,b (log-log),|b/t|,0.034600570420288364,0.009001423143236912,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8439,12327.0,acre,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Adjacent golf,green_space,E_environment,dummy,binary,0.033,,1.0085,,,,,high,Parcel shares a border with a golf course (fixed open space type),log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",pct_premium,3.299736550794452,3.3819700342055614,100*(exp(b - se^2/2) - 1),|b/t|,0.009082999472795686,0.009006444692905987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0085,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Distance fixed,green_space,E_environment,log,miles,-0.0294,,-15.9305,,,,,medium,"Distance to nearest fixed open space (parks, large water bodies, golf courses); unit inferred (miles), not stated; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",elasticity,-0.0294,0.0018455164621323874,b (log-log),|b/t|,-0.14202853540630175,0.008915510210370155,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.9305,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Adjacent fixed,green_space,E_environment,dummy,binary,-0.18,,-2.7616,,,,,high,"Parcel adjacent to fixed open space (golf course, resource protection area or park)",log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",pct_premium,-16.65021785407169,5.4442583304616505,100*(exp(b - se^2/2) - 1),|b/t|,-0.02486553303593655,0.009004031371645623,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.7616,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Distance historic,neighbourhood_amenities,F_neighbourhood,log,miles,-0.0076,,-0.6301,,,,,medium,"Distance to nearest historic area (Jamestown, Yorktown, Colonial Williamsburg etc.); cultural amenity; unit inferred (miles); entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",elasticity,-0.0076,0.012061577527376606,b (log-log),|b/t|,-0.005675103519444755,0.009006671194167204,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6301,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Adjacent historic,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.1041,,-0.83,,,,,high,Parcel adjacent to a historic area,log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",pct_premium,-10.592471840501528,11.302189418707636,100*(exp(b - se^2/2) - 1),|b/t|,-0.007475448594126978,0.009006564571237323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.83,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Distance water,water_proximity,E_environment,log,miles,0.0285,,3.6211,,,,,medium,Distance to nearest open water; unit inferred (miles); entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",elasticity,0.0285,0.007870536577283146,b (log-log),|b/t|,0.03259724985279739,0.009002029729308053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6211,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c1,3,"1 Log linear, 600 m 1/distance",15,Adjacent water,waterfront,C_exterior,dummy,binary,0.3598,,4.7185,,,,,high,Parcel adjacent to open water,log sale price (2004 dollars),log,spatial_error,12337.0,0.5682,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance",pct_premium,42.88825946115173,10.927387756441446,100*(exp(b - se^2/2) - 1),|b/t|,0.042460335129980806,0.008998693468259152,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.7185,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Age,age,A_structural,log,years,0.0679,,16.6913,,,,,medium,Age of house (data section lists year built); positive coefficient as printed; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",elasticity,0.0679,0.004067987514453638,b (log-log),|b/t|,0.14866488890683718,0.008906729188669379,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.6913,12327.0,years,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,True
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Bathrooms,bathrooms,A_structural,log,count,0.0213,,1.4479,,,,,medium,Number of bathrooms; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",elasticity,0.0213,0.01471096070170592,b (log-log),|b/t|,0.01303986045062796,0.009006050452813013,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4479,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Bedrooms,bedrooms,A_structural,log,count,0.0883,,4.619,,,,,medium,Number of bedrooms; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",elasticity,0.0883,0.019116691924659018,b (log-log),|b/t|,0.04156652876186445,0.008999031990011789,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.619,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Dock,waterfront,C_exterior,dummy,binary,0.1933,,5.1092,,,,,high,Presence of a dock (water access),log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",pct_premium,21.237870914160318,4.590162640173766,100*(exp(b - se^2/2) - 1),|b/t|,0.04596897879451747,0.008997294839606488,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.1092,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Square feet,living_area,A_structural,log,sqft,0.6849,,39.1968,,,,,medium,House square footage; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",elasticity,0.6849,0.017473365172667153,b (log-log),|b/t|,0.3329016181611144,0.008493081531173832,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),39.1968,12327.0,sqft,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Central air,air_conditioning,A_structural,dummy,binary,0.1141,,6.9647,,,,,high,Presence of central air conditioning,log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",pct_premium,12.071380137542986,1.8362686960017978,100*(exp(b - se^2/2) - 1),|b/t|,0.06260671450212615,0.008989147343335125,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.9647,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Lot size,lot_size,A_structural,log,acres,0.0082,,2.2801,,,,,medium,"Lot size; unit (acres) inferred from the 0.10-acre price-change exercise, not stated in table; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",elasticity,0.0082,0.0035963334941449938,b (log-log),|b/t|,0.020532112493041144,0.00900491754442399,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2801,12327.0,acre,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Adjacent golf,green_space,E_environment,dummy,binary,0.0278,,0.9556,,,,,high,Parcel shares a border with a golf course (fixed open space type),log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",pct_premium,2.775502629350046,2.991176508859367,100*(exp(b - se^2/2) - 1),|b/t|,0.008606594816934338,0.009006482646436102,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9556,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Distance fixed,green_space,E_environment,log,miles,-0.0312,,-16.2618,,,,,medium,"Distance to nearest fixed open space (parks, large water bodies, golf courses); unit inferred (miles), not stated; entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",elasticity,-0.0312,0.0019186067962956128,b (log-log),|b/t|,-0.14492082891219785,0.008911733566530019,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.2618,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Adjacent fixed,green_space,E_environment,dummy,binary,-0.165,,-2.4259,,,,,high,"Parcel adjacent to fixed open space (golf course, resource protection area or park)",log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",pct_premium,-15.406528190382108,5.767033314419643,100*(exp(b - se^2/2) - 1),|b/t|,-0.021844421793114098,0.00900466704856511,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4259,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Distance historic,neighbourhood_amenities,F_neighbourhood,log,miles,-0.0426,,-4.7608,,,,,medium,"Distance to nearest historic area (Jamestown, Yorktown, Colonial Williamsburg etc.); cultural amenity; unit inferred (miles); entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity)",log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",elasticity,-0.0426,0.00894807595362124,b (log-log),|b/t|,-0.04284028436810568,0.00899854738029442,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.7608,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Adjacent historic,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.441,,-4.1709,,,,,high,Parcel adjacent to a historic area,log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",pct_premium,-36.01936258428234,6.802756805453829,100*(exp(b - se^2/2) - 1),|b/t|,-0.03754005008823063,0.009000467546148465,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.1709,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,True
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Distance water,water_proximity,E_environment,log,miles,0.0291,,4.4791,,,,,medium,Distance to nearest open water; unit inferred (miles); entered in logarithm (inferred from 'log linear' model label; square-feet coefficient is an elasticity),log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",elasticity,0.0291,0.006496840883213146,b (log-log),|b/t|,0.0403096417300587,0.008999495820602065,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.4791,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c2,3,"2 Log linear, 600 m 1/distance^2",15,Adjacent water,waterfront,C_exterior,dummy,binary,0.3419,,5.0645,,,,,high,Parcel adjacent to open water,log sale price (2004 dollars),log,spatial_error,12337.0,0.584,t,"Log-linear functional form (continuous regressors in logs); spatial error model, weight matrix: Log linear, 600 m 1/distance^2",pct_premium,40.4415579408822,9.50271728308788,100*(exp(b - se^2/2) - 1),|b/t|,0.04556763848130472,0.008997460456373724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0645,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c3,3,"3 Semi-log, 600 m 1/distance",15,Age,age,A_structural,level,years,0.0008,,1.9952,,,,,medium,Age of house (data section lists year built); positive coefficient as printed,log sale price (2004 dollars),log,spatial_error,12337.0,0.5571,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance",semi_elasticity,0.08,0.040096230954290296,100*b/1 (per year),|b/t|,0.017967498818135388,0.00900536227853618,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9952,12327.0,years,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c3,3,"3 Semi-log, 600 m 1/distance",15,Bathrooms,bathrooms,A_structural,level,count,0.0002,,0.0288,,,,,high,Number of bathrooms,log sale price (2004 dollars),log,spatial_error,12337.0,0.5571,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance",semi_elasticity,0.02,0.6944444444444445,100*b/1 (per unit count),|b/t|,0.00025939629886121606,0.009006815932681113,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0288,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c3,3,"3 Semi-log, 600 m 1/distance",15,Bedrooms,bedrooms,A_structural,level,count,0.0299,,10.697,,,,,high,Number of bedrooms,log sale price (2004 dollars),log,spatial_error,12337.0,0.5571,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance",semi_elasticity,2.9899999999999998,0.2795176217631112,100*b/1 (per unit count),|b/t|,0.09590183536311268,0.008965301987764112,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.697,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c3,3,"3 Semi-log, 600 m 1/distance",15,Dock,waterfront,C_exterior,dummy,binary,0.2597,,6.6802,,,,,high,Presence of a dock (water access),log sale price (2004 dollars),log,spatial_error,12337.0,0.5571,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance",pct_premium,29.556167260727296,5.040443622033872,100*(exp(b - se^2/2) - 1),|b/t|,0.0600587224924566,0.008990557542058112,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.6802,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c3,3,"3 Semi-log, 600 m 1/distance",15,Square feet,living_area,A_structural,level,sqft,0.0002,,26.4267,,,,,high,House square footage,log sale price (2004 dollars),log,spatial_error,12337.0,0.5571,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance",semi_elasticity,0.21527820833419445,0.008146238778742501,100*b/0.092903 (X per sqft->m2),|b/t|,0.23155165652476223,0.008762034477432378,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.4267,12327.0,sqft,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c3,3,"3 Semi-log, 600 m 1/distance",15,Central air,air_conditioning,A_structural,dummy,binary,0.1196,,6.7155,,,,,high,Presence of central air conditioning,log sale price (2004 dollars),log,spatial_error,12337.0,0.5571,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance",pct_premium,12.686721904123566,2.0072175532122016,100*(exp(b - se^2/2) - 1),|b/t|,0.06037493535943291,0.008990385728454012,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.7155,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c3,3,"3 Semi-log, 600 m 1/distance",15,Lot size,lot_size,A_structural,level,acres,0.0186,,1.57,,,,,medium,"Lot size; unit (acres) inferred from the 0.10-acre price-change exercise, not stated in table",log sale price (2004 dollars),log,spatial_error,12337.0,0.5571,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance",semi_elasticity,0.0004596160095289275,0.0002927490506553678,100*b/4046.86 (X per acre->m2),|b/t|,0.014139287918671362,0.0090059158717652,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.57,12327.0,acre,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c3,3,"3 Semi-log, 600 m 1/distance",15,Adjacent golf,green_space,E_environment,dummy,binary,0.1443,,4.2511,,,,,high,Parcel shares a border with a golf course (fixed open space type),log sale price (2004 dollars),log,spatial_error,12337.0,0.5571,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance",pct_premium,15.456528574625473,3.9213328148759854,100*(exp(b - se^2/2) - 1),|b/t|,0.038260840846638874,0.009000221318397327,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.2511,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c3,3,"3 Semi-log, 600 m 1/distance",15,Adjacent fixed,green_space,E_environment,dummy,binary,-0.0883,,-1.3155,,,,,high,"Parcel adjacent to fixed open space (golf course, resource protection area or park)",log sale price (2004 dollars),log,spatial_error,12337.0,0.5571,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance",pct_premium,-8.65738350029469,6.144996620863342,100*(exp(b - se^2/2) - 1),|b/t|,-0.011847635165217871,0.009006184086064517,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3155,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c3,3,"3 Semi-log, 600 m 1/distance",15,Adjacent historic,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0642,,0.9276,,,,,high,Parcel adjacent to a historic area,log sale price (2004 dollars),log,spatial_error,12337.0,0.5571,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance",pct_premium,6.37548156669423,7.379993746856687,100*(exp(b - se^2/2) - 1),|b/t|,0.008354431169859908,0.009006501907999037,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9276,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c3,3,"3 Semi-log, 600 m 1/distance",15,Distance water,water_proximity,E_environment,level,miles,0.0185,,0.6811,,,,,medium,Distance to nearest open water; unit inferred (miles),log sale price (2004 dollars),log,spatial_error,12337.0,0.5571,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance",semi_elasticity,1.1495367056390677,1.6877649473485064,100*b/1.60934 (X per miles->km),|b/t|,0.0061344271119626705,0.009006646765471546,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6811,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c3,3,"3 Semi-log, 600 m 1/distance",15,Adjacent water,waterfront,C_exterior,dummy,binary,0.1963,,5.8833,,,,,high,Parcel adjacent to open water,log sale price (2004 dollars),log,spatial_error,12337.0,0.5571,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance",pct_premium,21.621474496463144,4.060236322027545,100*(exp(b - se^2/2) - 1),|b/t|,0.05291556272745345,0.008994197597853831,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.8833,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c4,3,"4 Semi-log, 600 m 1/distance^2",15,Age,age,A_structural,level,years,0.0015,,3.7181,,,,,medium,Age of house (data section lists year built); positive coefficient as printed,log sale price (2004 dollars),log,spatial_error,12337.0,0.5563,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance^2",semi_elasticity,0.15,0.04034318603587854,100*b/1 (per year),|b/t|,0.03346948132148818,0.009001770076514396,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.7181,12327.0,years,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c4,3,"4 Semi-log, 600 m 1/distance^2",15,Bathrooms,bathrooms,A_structural,level,count,0.0047,,0.6598,,,,,high,Number of bathrooms,log sale price (2004 dollars),log,spatial_error,12337.0,0.5563,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance^2",semi_elasticity,0.47000000000000003,0.7123370718399514,100*b/1 (per unit count),|b/t|,0.005942592419978497,0.009006657199118667,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6598,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c4,3,"4 Semi-log, 600 m 1/distance^2",15,Bedrooms,bedrooms,A_structural,level,count,0.0262,,10.1092,,,,,high,Number of bedrooms,log sale price (2004 dollars),log,spatial_error,12337.0,0.5563,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance^2",semi_elasticity,2.62,0.2591698650733985,100*b/1 (per unit count),|b/t|,0.09067660923033831,0.008969711671580175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.1092,12327.0,count,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c4,3,"4 Semi-log, 600 m 1/distance^2",15,Dock,waterfront,C_exterior,dummy,binary,0.2494,,6.3897,,,,,high,Presence of a dock (water access),log sale price (2004 dollars),log,spatial_error,12337.0,0.5563,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance^2",pct_premium,28.227810866917835,5.008746185102772,100*(exp(b - se^2/2) - 1),|b/t|,0.057455782686566856,0.00899193744410017,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.3897,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c4,3,"4 Semi-log, 600 m 1/distance^2",15,Square feet,living_area,A_structural,level,sqft,0.0002,,30.1076,,,,,high,House square footage,log sale price (2004 dollars),log,spatial_error,12337.0,0.5563,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance^2",semi_elasticity,0.21527820833419445,0.007150294554670396,100*b/0.092903 (X per sqft->m2),|b/t|,0.2617214445344718,0.008692869725068483,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.1076,12327.0,sqft,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c4,3,"4 Semi-log, 600 m 1/distance^2",15,Central air,air_conditioning,A_structural,dummy,binary,0.134,,7.7014,,,,,high,Presence of central air conditioning,log sale price (2004 dollars),log,spatial_error,12337.0,0.5563,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance^2",pct_premium,14.321975720119307,1.9894387751887024,100*(exp(b - se^2/2) - 1),|b/t|,0.06919881870379768,0.008985225894486415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.7014,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c4,3,"4 Semi-log, 600 m 1/distance^2",15,Lot size,lot_size,A_structural,level,acres,0.0157,,1.3638,,,,,medium,"Lot size; unit (acres) inferred from the 0.10-acre price-change exercise, not stated in table",log sale price (2004 dollars),log,spatial_error,12337.0,0.5563,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance^2",semi_elasticity,0.0003879554489034495,0.0002844665265460109,100*b/4046.86 (X per acre->m2),|b/t|,0.01228256939391731,0.009006136819121068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3638,12327.0,acre,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c4,3,"4 Semi-log, 600 m 1/distance^2",15,Adjacent golf,green_space,E_environment,dummy,binary,0.1643,,5.3385,,,,,high,Parcel shares a border with a golf course (fixed open space type),log sale price (2004 dollars),log,spatial_error,12337.0,0.5563,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance^2",pct_premium,17.800980133632493,3.627211667422008,100*(exp(b - se^2/2) - 1),|b/t|,0.048027401710794844,0.008996422536441857,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.3385,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c4,3,"4 Semi-log, 600 m 1/distance^2",15,Adjacent fixed,green_space,E_environment,dummy,binary,-0.0725,,-1.031,,,,,high,"Parcel adjacent to fixed open space (golf course, resource protection area or park)",log sale price (2004 dollars),log,spatial_error,12337.0,0.5563,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance^2",pct_premium,-7.223096016196684,6.540229547320096,100*(exp(b - se^2/2) - 1),|b/t|,-0.0092856271963923,0.009006427930545393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.031,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c4,3,"4 Semi-log, 600 m 1/distance^2",15,Adjacent historic,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0506,,0.7207,,,,,high,Parcel adjacent to a historic area,log sale price (2004 dollars),log,spatial_error,12337.0,0.5563,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance^2",pct_premium,4.931263005165065,7.3853536345227155,100*(exp(b - se^2/2) - 1),|b/t|,0.006491075709047892,0.009006626486815448,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7207,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c4,3,"4 Semi-log, 600 m 1/distance^2",15,Distance water,water_proximity,E_environment,level,miles,0.0026,,0.1546,,,,,medium,Distance to nearest open water; unit inferred (miles),log sale price (2004 dollars),log,spatial_error,12337.0,0.5563,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance^2",semi_elasticity,0.16155650998170681,1.0449968304120754,100*b/1.60934 (X per miles->km),|b/t|,0.0013924524401075801,0.009006807503930014,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.1546,12327.0,miles,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec,2bbdabdc28e5b845377e3ce418d4b3325d2d76ec:T3-c4,3,"4 Semi-log, 600 m 1/distance^2",15,Adjacent water,waterfront,C_exterior,dummy,binary,0.181,,5.3169,,,,,high,Parcel adjacent to open water,log sale price (2004 dollars),log,spatial_error,12337.0,0.5563,t,"Semi-log functional form (regressors in levels); spatial error model, weight matrix: Semi-log, 600 m 1/distance^2",pct_premium,19.772096803463725,4.079692065904363,100*(exp(b - se^2/2) - 1),|b/t|,0.047833524504420535,0.008996506329707261,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.3169,12327.0,binary,,2016.0,United States,North America,High income,1998.0,2004.0,single_family,transaction,journal,True,True,unknown,,2001.0,spatial,journal,True,True,False
3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f:T4-A,4,A,15,Tested,water_quality,E_environment,binary,binary,-0.0239,0.0189,,,,,,high,Private well tested for contamination within 3 years prior to sale (any result),ln real transaction price (2013 USD),log,OLS,1730.0,0.7981,se,"Base model, OLS; wells tested 0-3 years prior to sale; year and quarter dummies; full Table 3 controls included but not printed",pct_premium,-2.3791028164274475,1.8453645186678003,100*(exp(b - se^2/2) - 1),reported,-0.030476850515107658,0.024100940365503542,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2645502645502646,1720.0,binary,,2016.0,United States,North America,High income,1990.0,2013.0,single_family,transaction,journal,True,True,robust,,2001.5,ols,journal,True,True,False
3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f:T4-B,4,B,15,Tested,water_quality,E_environment,binary,binary,0.0021,0.0188,,,,,,high,Private well tested for contamination within 3 years prior to sale (any result),ln real transaction price (2013 USD),log,FE_panel,1730.0,0.7701,se,"Base model, census block-group fixed effects (65 FE); wells tested 0-3 years prior to sale; year and quarter dummies; full Table 3 controls included but not printed",pct_premium,0.19251306892535958,1.883952148303304,100*(exp(b - se^2/2) - 1),reported,0.002693367695042742,0.024112053650858837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.11170212765957446,1720.0,binary,,2016.0,United States,North America,High income,1990.0,2013.0,single_family,transaction,journal,True,True,robust,,2001.5,panel,journal,True,True,False
3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f:T4-C,4,C,15,Tested,water_quality,E_environment,binary,binary,-0.022,0.0172,,,,,,high,Private well tested for contamination within 3 years prior to sale (any result),ln real transaction price (2013 USD),log,spatial_error,1730.0,0.8001,se,"Base model, spatial error model; wells tested 0-3 years prior to sale; year and quarter dummies; full Table 3 controls included but not printed",pct_premium,-2.1904455542778534,1.6825732042880812,100*(exp(b - se^2/2) - 1),reported,-0.030826453542490966,0.02410068186049294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2790697674418603,1720.0,binary,,2016.0,United States,North America,High income,1990.0,2013.0,single_family,transaction,journal,True,True,robust,,2001.5,spatial,journal,True,True,False
3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f:T4-D,4,D,15,Tested,water_quality,E_environment,binary,binary,0.0022,0.017,,,,,,high,Private well tested for contamination within 3 years prior to sale (any result),ln real transaction price (2013 USD),log,spatial_error,1730.0,0.8224,se,"Base model, spatial error model + block-group FE; wells tested 0-3 years prior to sale; year and quarter dummies; full Table 3 controls included but not printed",pct_premium,0.20576139883112798,1.7037441170185934,100*(exp(b - se^2/2) - 1),reported,0.0031203795403733957,0.024112023721067147,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.12941176470588237,1720.0,binary,,2016.0,United States,North America,High income,1990.0,2013.0,single_family,transaction,journal,True,True,robust,,2001.5,spatial,journal,True,True,False
3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f:T4-A1,4,A1,15,Tested,water_quality,E_environment,binary,binary,-0.0239,0.0189,,,,,,high,Private well tested for contamination within 3 years prior to sale (any result),ln real transaction price (2013 USD),log,OLS,1730.0,0.7981,se,"Base model plus Tested x Above MCL interaction, OLS; wells tested 0-3 years prior to sale; year and quarter dummies; full Table 3 controls included but not printed",pct_premium,-2.3791028164274475,1.8453645186678003,100*(exp(b - se^2/2) - 1),reported,-0.030476850515107658,0.024100940365503542,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2645502645502646,1720.0,binary,,2016.0,United States,North America,High income,1990.0,2013.0,single_family,transaction,journal,True,True,robust,,2001.5,ols,journal,True,True,False
3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f:T4-B1,4,B1,15,Tested,water_quality,E_environment,binary,binary,0.002,0.0189,,,,,,high,Private well tested for contamination within 3 years prior to sale (any result),ln real transaction price (2013 USD),log,FE_panel,1730.0,0.7702,se,"Plus Tested x Above MCL, block-group FE; wells tested 0-3 years prior to sale; year and quarter dummies; full Table 3 controls included but not printed",pct_premium,0.1823054747405184,1.8937837825212607,100*(exp(b - se^2/2) - 1),reported,0.002551541017885131,0.024112062619014482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.10582010582010583,1720.0,binary,,2016.0,United States,North America,High income,1990.0,2013.0,single_family,transaction,journal,True,True,robust,,2001.5,panel,journal,True,True,False
3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f:T4-C1,4,C1,15,Tested,water_quality,E_environment,binary,binary,-0.022,0.0172,,,,,,high,Private well tested for contamination within 3 years prior to sale (any result),ln real transaction price (2013 USD),log,spatial_error,1730.0,0.8001,se,"Plus Tested x Above MCL, spatial error model; wells tested 0-3 years prior to sale; year and quarter dummies; full Table 3 controls included but not printed",pct_premium,-2.1904455542778534,1.6825732042880812,100*(exp(b - se^2/2) - 1),reported,-0.030826453542490966,0.02410068186049294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2790697674418603,1720.0,binary,,2016.0,United States,North America,High income,1990.0,2013.0,single_family,transaction,journal,True,True,robust,,2001.5,spatial,journal,True,True,False
3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f,3244bfbe46126d82d9734bb6ef3476cad91ccc3f:T4-D1,4,D1,15,Tested,water_quality,E_environment,binary,binary,0.002,0.017,,,,,,high,Private well tested for contamination within 3 years prior to sale (any result),ln real transaction price (2013 USD),log,spatial_error,1730.0,0.8224,se,"Plus Tested x Above MCL, SEM + block-group FE; wells tested 0-3 years prior to sale; year and quarter dummies; full Table 3 controls included but not printed",pct_premium,0.18572225053297142,1.7034034022678006,100*(exp(b - se^2/2) - 1),reported,0.0028367110698792122,0.024112044093973304,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.11764705882352941,1720.0,binary,,2016.0,United States,North America,High income,1990.0,2013.0,single_family,transaction,journal,True,True,robust,,2001.5,spatial,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c1,3,1,7,Detached (d),dwelling_type,A_structural,binary,binary,0.651,0.016,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9655.0,0.85,se,Model 1: bus stops counted within 300 m; year and ward dummies included,pct_premium,91.7211909101826,3.067931724692258,100*(exp(b - se^2/2) - 1),reported,0.3827477986223604,0.009407011947707782,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.6875,9645.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c1,3,1,7,Semi-detached (s),dwelling_type,A_structural,binary,binary,0.468,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9655.0,0.85,se,Model 1: bus stops counted within 300 m; year and ward dummies included,pct_premium,59.66409242091599,2.235516363761874,100*(exp(b - se^2/2) - 1),reported,0.3222269442468668,0.009639267562940458,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.42857142857143,9645.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c1,3,1,7,Terraced (t),dwelling_type,A_structural,binary,binary,0.36,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9655.0,0.85,se,Model 1: bus stops counted within 300 m; year and ward dummies included,pct_premium,43.31889551603363,2.006661180384476,100*(exp(b - se^2/2) - 1),reported,0.25329386217599803,0.009850316862399925,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.71428571428571,9645.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c2,3,2,7,Detached (d),dwelling_type,A_structural,binary,binary,0.654,0.016,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9650.0,0.85,se,Model 2: bus stops counted within 400 m; year and ward dummies included,pct_premium,92.29721809166504,3.0771493393751492,100*(exp(b - se^2/2) - 1),reported,0.3843366178331483,0.009402730711514332,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.875,9640.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c2,3,2,7,Semi-detached (s),dwelling_type,A_structural,binary,binary,0.471,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9650.0,0.85,se,Model 2: bus stops counted within 400 m; year and ward dummies included,pct_premium,60.14380390562224,2.242232982744169,100*(exp(b - se^2/2) - 1),reported,0.3241513893932211,0.009635073145446062,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.64285714285714,9640.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c2,3,2,7,Terraced (t),dwelling_type,A_structural,binary,binary,0.361,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9650.0,0.85,se,Model 2: bus stops counted within 400 m; year and ward dummies included,pct_premium,43.46228609488989,2.008668845229978,100*(exp(b - se^2/2) - 1),reported,0.2540137411426779,0.009850948409965348,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.785714285714285,9640.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c3,3,3,7,Detached (d),dwelling_type,A_structural,binary,binary,0.654,0.016,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9656.0,0.85,se,Model 3: bus stops counted within 500 m; year and ward dummies included,pct_premium,92.29721809166504,3.0771493393751492,100*(exp(b - se^2/2) - 1),reported,0.3842347192200732,0.00940023777908436,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.875,9646.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c3,3,3,7,Semi-detached (s),dwelling_type,A_structural,binary,binary,0.469,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9656.0,0.85,se,Model 3: bus stops counted within 500 m; year and ward dummies included,pct_premium,59.82383637200046,2.2377529982564965,100*(exp(b - se^2/2) - 1),reported,0.32282877797961507,0.009636679939690002,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.5,9646.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c3,3,3,7,Terraced (t),dwelling_type,A_structural,binary,binary,0.359,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9656.0,0.85,se,Model 3: bus stops counted within 500 m; year and ward dummies included,pct_premium,43.17564825608484,2.004655522200322,100*(exp(b - se^2/2) - 1),reported,0.25262297332722194,0.009851592274599185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.642857142857142,9646.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c4,3,4,7,Detached (d),dwelling_type,A_structural,binary,binary,0.647,0.016,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9653.0,0.851,se,Model 4: bus stops counted within 750 m; year and ward dummies included,pct_premium,90.9558378730865,3.0556845085553794,100*(exp(b - se^2/2) - 1),reported,0.38077161637449913,0.00941629963213599,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.4375,9643.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c4,3,4,7,Semi-detached (s),dwelling_type,A_structural,binary,binary,0.465,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9653.0,0.851,se,Model 4: bus stops counted within 750 m; year and ward dummies included,pct_premium,59.185817914119276,2.2288198644419417,100*(exp(b - se^2/2) - 1),reported,0.3204038194048625,0.009646566605737797,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.214285714285715,9643.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c4,3,4,7,Terraced (t),dwelling_type,A_structural,binary,binary,0.356,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9653.0,0.851,se,Model 4: bus stops counted within 750 m; year and ward dummies included,pct_premium,42.74676495792627,1.9986505675693826,100*(exp(b - se^2/2) - 1),reported,0.2506815998847677,0.009858265164007719,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.428571428571427,9643.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c5,3,5,7,Detached (d),dwelling_type,A_structural,binary,binary,0.644,0.016,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9659.0,0.85,se,Model 5: bus stops counted within 1000 m; year and ward dummies included,pct_premium,90.38382880208049,3.0465311918697284,100*(exp(b - se^2/2) - 1),reported,0.3791595428087891,0.009420112864814636,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.25,9649.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c5,3,5,7,Semi-detached (s),dwelling_type,A_structural,binary,binary,0.464,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9659.0,0.85,se,Model 5: bus stops counted within 1000 m; year and ward dummies included,pct_premium,59.02671166258977,2.226592158616055,100*(exp(b - se^2/2) - 1),reported,0.3196960341275535,0.009646001029710664,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.142857142857146,9649.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c5,3,5,7,Terraced (t),dwelling_type,A_structural,binary,binary,0.354,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9659.0,0.85,se,Model 5: bus stops counted within 1000 m; year and ward dummies included,pct_premium,42.46155673130643,1.9946572610718438,100*(exp(b - se^2/2) - 1),reported,0.24928835693369972,0.00985886157364914,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.285714285714285,9649.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c6,3,6,7,Detached (d),dwelling_type,A_structural,binary,binary,0.645,0.016,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9669.0,0.849,se,Model 6: bus stops counted within 1500 m; year and ward dummies included,pct_premium,90.57430785453555,3.0495792468350764,100*(exp(b - se^2/2) - 1),reported,0.37949522343820885,0.009413835000017584,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.3125,9659.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c6,3,6,7,Semi-detached (s),dwelling_type,A_structural,binary,binary,0.465,0.015,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9669.0,0.849,se,Model 6: bus stops counted within 1500 m; year and ward dummies included,pct_premium,59.183509736493846,2.3880212833306516,100*(exp(b - se^2/2) - 1),reported,0.3008149633654507,0.0097037084956597,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),31.000000000000004,9659.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T3-c6,3,6,7,Terraced (t),dwelling_type,A_structural,binary,binary,0.357,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,OLS,9669.0,0.849,se,Model 6: bus stops counted within 1500 m; year and ward dummies included,pct_premium,42.88958312006375,2.0006502177954277,100*(exp(b - se^2/2) - 1),reported,0.2511462192720896,0.009848871344003514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.5,9659.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,ols,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c1,5,1,9,Detached (d),dwelling_type,A_structural,binary,binary,0.659,0.016,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9655.0,,se,"Model 7: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 300 m",pct_premium,93.26111190855431,3.092573614626259,100*(exp(b - se^2/2) - 1),reported,0.38675140808771674,0.009390019012751848,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),41.1875,9645.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,True
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c1,5,1,9,Semi-detached (s),dwelling_type,A_structural,binary,binary,0.476,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9655.0,,se,"Model 7: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 300 m",pct_premium,60.946528063203,2.253472222341811,100*(exp(b - se^2/2) - 1),reported,0.32715000705770964,0.009622059031109107,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.0,9645.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c1,5,1,9,Terraced (t),dwelling_type,A_structural,binary,binary,0.369,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9655.0,,se,"Model 7: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 300 m",pct_premium,44.61458744344257,2.0248026451446357,100*(exp(b - se^2/2) - 1),reported,0.2592056016894121,0.00983435887168501,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.357142857142858,9645.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c2,5,2,9,Detached (d),dwelling_type,A_structural,binary,binary,0.662,0.016,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9650.0,,se,"Model 8: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 400 m",pct_premium,93.84176578961123,3.1018652659784287,100*(exp(b - se^2/2) - 1),reported,0.388332651181383,0.009385683412238863,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),41.375,9640.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,True
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c2,5,2,9,Semi-detached (s),dwelling_type,A_structural,binary,binary,0.48,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9650.0,,se,"Model 8: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 400 m",pct_premium,61.591603466161416,2.262504163070051,100*(exp(b - se^2/2) - 1),reported,0.3296777943830783,0.009615602336173118,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.285714285714285,9640.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c2,5,2,9,Terraced (t),dwelling_type,A_structural,binary,binary,0.371,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9650.0,,se,"Model 8: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 400 m",pct_premium,44.90410604042025,2.028856302741303,100*(exp(b - se^2/2) - 1),reported,0.2605783670103244,0.0098331459249179,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.5,9640.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c3,5,3,9,Detached (d),dwelling_type,A_structural,binary,binary,0.663,0.016,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9656.0,,se,"Model 9: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 500 m",pct_premium,94.03570450859877,3.104968682694147,100*(exp(b - se^2/2) - 1),reported,0.3887279547858488,0.009381066782162264,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),41.4375,9646.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,True
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c3,5,3,9,Semi-detached (s),dwelling_type,A_structural,binary,binary,0.478,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9656.0,,se,"Model 9: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 500 m",pct_premium,61.26874322708824,2.2579836767370725,100*(exp(b - se^2/2) - 1),reported,0.3283614546016392,0.009617281097119141,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.14285714285714,9646.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c3,5,3,9,Terraced (t),dwelling_type,A_structural,binary,binary,0.37,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9656.0,,se,"Model 9: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 500 m",pct_premium,44.759274362288195,2.0268284605286544,100*(exp(b - se^2/2) - 1),reported,0.2598481199789754,0.0098320910262315,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.428571428571427,9646.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c4,5,4,9,Detached (d),dwelling_type,A_structural,binary,binary,0.655,0.016,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9653.0,,se,"Model 10: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 750 m",pct_premium,92.48961149042331,3.0802280278021805,100*(exp(b - se^2/2) - 1),reported,0.3847863084573217,0.009399360206591064,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.9375,9643.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c4,5,4,9,Semi-detached (s),dwelling_type,A_structural,binary,binary,0.473,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9653.0,,se,"Model 10: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 750 m",pct_premium,60.464412014673165,2.2467219361667627,100*(exp(b - se^2/2) - 1),reported,0.3253371151306416,0.009629428354818146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.785714285714285,9643.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c4,5,4,9,Terraced (t),dwelling_type,A_structural,binary,binary,0.366,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9653.0,,se,"Model 10: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 750 m",pct_premium,44.18139379647788,2.0187373397163224,100*(exp(b - se^2/2) - 1),reported,0.25726312923267924,0.00984066614551232,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.142857142857142,9643.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c5,5,5,9,Detached (d),dwelling_type,A_structural,binary,binary,0.653,0.016,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9659.0,,se,"Model 11: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 1000 m",pct_premium,92.10501699014091,3.074073728097714,100*(exp(b - se^2/2) - 1),reported,0.3836828978580497,0.009401112351805201,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.8125,9649.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c5,5,5,9,Semi-detached (s),dwelling_type,A_structural,binary,binary,0.472,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9659.0,,se,"Model 11: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 1000 m",pct_premium,60.30402780812712,2.2444763372172036,100*(exp(b - se^2/2) - 1),reported,0.32463156077262467,0.009628902226306663,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.714285714285715,9649.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c5,5,5,9,Terraced (t),dwelling_type,A_structural,binary,binary,0.364,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9659.0,,se,"Model 11: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 1000 m",pct_premium,43.89331917952675,2.014703899821265,100*(exp(b - se^2/2) - 1),reported,0.2558752722786639,0.009841356626102457,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.0,9649.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c6,5,6,9,Detached (d),dwelling_type,A_structural,binary,binary,0.654,0.016,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9669.0,,se,"Model 12: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 1500 m",pct_premium,92.29721809166504,3.0771493393751492,100*(exp(b - se^2/2) - 1),reported,0.38401421664334906,0.009394843220632394,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.875,9659.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c6,5,6,9,Semi-detached (s),dwelling_type,A_structural,binary,binary,0.474,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9669.0,,se,"Model 12: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 1500 m",pct_premium,60.624956685644605,2.248969781838445,100*(exp(b - se^2/2) - 1),reported,0.32571050683866537,0.009620141552196869,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.857142857142854,9659.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee,327115a5186cc436d1749ca2acaa98314f882fee:T5-c6,5,6,9,Terraced (t),dwelling_type,A_structural,binary,binary,0.367,0.014,,,***,,,high,Reference category = flat,"log(p), natural log of property sale price (GBP)",log,other,9669.0,,se,"Model 12: multilevel model (random intercepts for ward and year, MLwiN); bus stops counted within 1500 m",pct_premium,44.3256473050075,2.020757086761249,100*(exp(b - se^2/2) - 1),reported,0.2577198259969989,0.009831274016234291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.21428571428571,9659.0,binary,,2015.0,United Kingdom,Europe,High income,2000.0,2008.0,mixed,transaction,journal,True,True,OLS,,2004.0,other,journal,True,True,False
3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796:T5-c1,5,1,17,Dwelling area (overall mean effect),living_area,A_structural,log,m2,0.614,0.019,,,,,,high,Log dwelling area (Table 2); random slope at municipality level in ML model,log yearly rent (CHF),log,OLS,11913.0,0.858,se,OLS 1: with cantonal dummies,elasticity,0.614,0.019,b (log-log),reported,0.28400435045962613,0.008788408238978659,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.31578947368421,11903.0,m2,,2008.0,Switzerland,Europe,High income,2006.0,2007.0,rental,rent,journal,True,True,OLS,,2006.5,ols,journal,True,True,False
3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796:T5-c2,5,2,17,Dwelling area (overall mean effect),living_area,A_structural,log,m2,0.63,0.011,,,,,,high,Log dwelling area (Table 2); random slope at municipality level in ML model,log yearly rent (CHF),log,OLS,11913.0,0.859,se,OLS 2: cantonal dummies + cantonal interaction terms,elasticity,0.63,0.011,b (log-log),reported,0.46480062603292505,0.008115566486289168,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),57.27272727272727,11903.0,m2,,2008.0,Switzerland,Europe,High income,2006.0,2007.0,rental,rent,journal,True,True,OLS,,2006.5,ols,journal,True,True,False
3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796:T5-c3,5,3,17,Dwelling area (overall mean effect),living_area,A_structural,log,m2,0.603,0.017,,,,,,high,Log dwelling area (Table 2); random slope at municipality level in ML model,log yearly rent (CHF),log,other,11913.0,0.877,se,"ML: two-level multilevel model (random intercept + random slope on dwelling area at municipality level, MLwiN); same estimates as Table 4 p. 14",elasticity,0.603,0.017,b (log-log),reported,0.3091870267312343,0.008716715513152545,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.470588235294116,11903.0,m2,,2008.0,Switzerland,Europe,High income,2006.0,2007.0,rental,rent,journal,True,True,OLS,,2006.5,other,journal,True,True,False
3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796:T5-c1,5,1,17,Number of rooms,bedrooms,A_structural,level,count,0.053,0.005,,,,,,high,Number of rooms in the apartment (not bedrooms specifically),log yearly rent (CHF),log,OLS,11913.0,0.858,se,OLS 1: with cantonal dummies,semi_elasticity,5.3,0.5,100*b/1 (per unit count),reported,0.09670244871739685,0.009122872520509138,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.6,11903.0,count,,2008.0,Switzerland,Europe,High income,2006.0,2007.0,rental,rent,journal,True,True,OLS,,2006.5,ols,journal,True,True,False
3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796:T5-c2,5,2,17,Number of rooms,bedrooms,A_structural,level,count,0.054,0.005,,,,,,high,Number of rooms in the apartment (not bedrooms specifically),log yearly rent (CHF),log,OLS,11913.0,0.859,se,OLS 2: cantonal dummies + cantonal interaction terms,semi_elasticity,5.4,0.5,100*b/1 (per unit count),reported,0.09850947971745741,0.009121248121986796,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.799999999999999,11903.0,count,,2008.0,Switzerland,Europe,High income,2006.0,2007.0,rental,rent,journal,True,True,OLS,,2006.5,ols,journal,True,True,False
3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796:T5-c3,5,3,17,Number of rooms,bedrooms,A_structural,level,count,0.052,0.005,,,,,,high,Number of rooms in the apartment (not bedrooms specifically),log yearly rent (CHF),log,other,11913.0,0.877,se,"ML: two-level multilevel model (random intercept + random slope on dwelling area at municipality level, MLwiN); same estimates as Table 4 p. 14",semi_elasticity,5.2,0.5,100*b/1 (per unit count),reported,0.09489446096438996,0.009124467400422113,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.399999999999999,11903.0,count,,2008.0,Switzerland,Europe,High income,2006.0,2007.0,rental,rent,journal,True,True,OLS,,2006.5,other,journal,True,True,False
3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796:T5-c1,5,1,17,Floor level,floor_level,A_structural,level,count,0.006,0.001,,,,,,high,Position of the apartment in the building,log yearly rent (CHF),log,OLS,11913.0,0.858,se,OLS 1: with cantonal dummies,semi_elasticity,0.6,0.1,100*b/1 (per unit count),reported,0.05491200157443693,0.009152000262406156,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,11903.0,count,,2008.0,Switzerland,Europe,High income,2006.0,2007.0,rental,rent,journal,True,True,OLS,,2006.5,ols,journal,True,True,False
3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796:T5-c2,5,2,17,Floor level,floor_level,A_structural,level,count,0.007,0.001,,,,,,high,Position of the apartment in the building,log yearly rent (CHF),log,OLS,11913.0,0.859,se,OLS 2: cantonal dummies + cantonal interaction terms,semi_elasticity,0.7000000000000001,0.1,100*b/1 (per unit count),reported,0.0640291516606527,0.009147021665807529,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,11903.0,count,,2008.0,Switzerland,Europe,High income,2006.0,2007.0,rental,rent,journal,True,True,OLS,,2006.5,ols,journal,True,True,False
3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796:T5-c3,5,3,17,Floor level,floor_level,A_structural,level,count,0.009,0.001,,,,,,high,Position of the apartment in the building,log yearly rent (CHF),log,other,11913.0,0.877,se,"ML: two-level multilevel model (random intercept + random slope on dwelling area at municipality level, MLwiN); same estimates as Table 4 p. 14",semi_elasticity,0.8999999999999999,0.1,100*b/1 (per unit count),reported,0.08221321071471033,0.00913480119052337,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.0,11903.0,count,,2008.0,Switzerland,Europe,High income,2006.0,2007.0,rental,rent,journal,True,True,OLS,,2006.5,other,journal,True,True,False
3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796:T5-c1,5,1,17,Mixed building,dwelling_type,A_structural,binary,binary,0.033,0.005,,,,,,high,Dummy for mixed commercial and residential building,log yearly rent (CHF),log,OLS,11913.0,0.858,se,OLS 1: with cantonal dummies,pct_premium,3.353761994031079,0.5167752696206528,100*(exp(b - se^2/2) - 1),reported,0.06038408658610734,0.009149104028198081,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.6000000000000005,11903.0,binary,,2008.0,Switzerland,Europe,High income,2006.0,2007.0,rental,rent,journal,True,True,OLS,,2006.5,ols,journal,True,True,False
3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796:T5-c2,5,2,17,Mixed building,dwelling_type,A_structural,binary,binary,0.032,0.005,,,,,,high,Dummy for mixed commercial and residential building,log yearly rent (CHF),log,OLS,11913.0,0.859,se,OLS 2: cantonal dummies + cantonal interaction terms,pct_premium,3.250459891696722,0.5162587526525592,100*(exp(b - se^2/2) - 1),reported,0.05856063857503699,0.009150099777349529,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.4,11903.0,binary,,2008.0,Switzerland,Europe,High income,2006.0,2007.0,rental,rent,journal,True,True,OLS,,2006.5,ols,journal,True,True,False
3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796,3372ad7c12532642d33524d3fe7c38467c784796:T5-c3,5,3,17,Mixed building,dwelling_type,A_structural,binary,binary,0.038,0.005,,,,,,high,Dummy for mixed commercial and residential building,log yearly rent (CHF),log,other,11913.0,0.877,se,"ML: two-level multilevel model (random intercept + random slope on dwelling area at municipality level, MLwiN); same estimates as Table 4 p. 14",pct_premium,3.8718248819237244,0.5193656164392488,100*(exp(b - se^2/2) - 1),reported,0.06949190291450835,0.00914367143611952,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.6,11903.0,binary,,2008.0,Switzerland,Europe,High income,2006.0,2007.0,rental,rent,journal,True,True,OLS,,2006.5,other,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T2-c1,2,1,11,Dwelling,dwelling_type,A_structural,binary,binary,0.4,0.18,,,,,,medium,"1 if the rented room is located within a house, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,242.0,0.75,se,Uganda LSMS 2010 renter households; OLS with district fixed effects (not reported),pct_premium,46.78518419546045,26.852844557542866,100*(exp(b - se^2/2) - 1),reported,0.1443676470241678,0.0649654411608755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2222222222222223,232.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T2-c1,2,1,11,Roof,roof_materials,A_structural,binary,binary,-0.38,0.33,,,,,,medium,"1 if roof type is mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,242.0,0.75,se,Uganda LSMS 2010 renter households; OLS with district fixed effects (not reported),pct_premium,-35.237923943834105,22.56742650400774,100*(exp(b - se^2/2) - 1),reported,-0.07538554879765468,0.06546639764006854,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1515151515151514,232.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T2-c1,2,1,11,Floor,flooring,B_interior,binary,binary,0.64,0.24,,,,,,medium,"1 if floor is mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,242.0,0.75,se,Uganda LSMS 2010 renter households; OLS with district fixed effects (not reported),pct_premium,84.26412421009857,45.51554110331883,100*(exp(b - se^2/2) - 1),reported,0.17245224542369075,0.06466959203388403,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.666666666666667,232.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,True
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T2-c1,2,1,11,External wall,roof_materials,A_structural,binary,binary,0.32,0.22,,,,,,medium,"1 if external wall is in mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,242.0,0.75,se,Uganda LSMS 2010 renter households; OLS with district fixed effects (not reported),pct_premium,34.42012896882969,30.296810815391055,100*(exp(b - se^2/2) - 1),reported,0.09506311166323297,0.06535588926847266,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4545454545454546,232.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T2-c1,2,1,11,Number of rooms,bedrooms,A_structural,level,count,0.36,0.18,,,,,,medium,"Number of rooms rented (total rooms, not bedrooms); parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,242.0,0.75,se,Uganda LSMS 2010 renter households; OLS with district fixed effects (not reported),semi_elasticity,36.0,18.0,100*b/1 (per unit count),reported,0.13018891098082389,0.06509445549041193,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,232.0,count,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,True
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T2-c4,2,4,11,Dwelling,dwelling_type,A_structural,binary,binary,0.22,0.14,,,,,,medium,"1 if the rented room is located within a house, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,263.0,0.41,se,Uganda LSMS 2012 renter households; OLS with district fixed effects (not reported),pct_premium,23.392482024394077,17.445074228223334,100*(exp(b - se^2/2) - 1),reported,0.09831622879049641,0.06256487286667954,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5714285714285714,253.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T2-c4,2,4,11,Roof,roof_materials,A_structural,binary,binary,0.23,0.73,,,,,,medium,"1 if roof type is mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,263.0,0.41,se,Uganda LSMS 2012 renter households; OLS with district fixed effects (not reported),pct_premium,-3.5793696993763446,91.87780072485188,100*(exp(b - se^2/2) - 1),reported,0.0198043015826003,0.06285713110999226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.31506849315068497,253.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T2-c4,2,4,11,Floor,flooring,B_interior,binary,binary,0.01,0.09,,,,,,medium,"1 if floor is mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,263.0,0.41,se,Uganda LSMS 2012 renter households; OLS with district fixed effects (not reported),pct_premium,0.5967736409763669,9.09045150375751,100*(exp(b - se^2/2) - 1),reported,0.006985325275228183,0.06286792747705364,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.11111111111111112,253.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T2-c4,2,4,11,External wall,roof_materials,A_structural,binary,binary,0.4,0.18,,,,,,medium,"1 if external wall is in mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,263.0,0.41,se,Uganda LSMS 2012 renter households; OLS with district fixed effects (not reported),pct_premium,46.78518419546045,26.852844557542866,100*(exp(b - se^2/2) - 1),reported,0.13836606606450116,0.06226472972902551,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2222222222222223,253.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T3-c1,3,1,11,Roof,roof_materials,A_structural,binary,binary,-0.63,0.11,,,,,,medium,"1 if roof type is mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,873.0,0.75,se,Tanzania LSMS 2014 renter households; OLS with district fixed effects (not reported),pct_premium,-47.062065192044464,5.858509811075869,100*(exp(b - se^2/2) - 1),reported,-0.19135593409256046,0.03341135357171691,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.7272727272727275,863.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T3-c1,3,1,11,Floor,flooring,B_interior,binary,binary,-0.16,0.07,,,,,,medium,"1 if floor is mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,873.0,0.75,se,Tanzania LSMS 2014 renter households; OLS with district fixed effects (not reported),pct_premium,-14.994140790755273,5.965006522763479,100*(exp(b - se^2/2) - 1),reported,-0.07757216754198588,0.03393782329961883,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.2857142857142856,863.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T3-c1,3,1,11,External wall,roof_materials,A_structural,binary,binary,0.42,0.05,,,,,,medium,"1 if external wall is in mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,873.0,0.75,se,Tanzania LSMS 2014 renter households; OLS with district fixed effects (not reported),pct_premium,52.00602922113005,7.609807778093169,100*(exp(b - se^2/2) - 1),reported,0.2749211604401788,0.03272870957621177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.399999999999999,863.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T3-c4,3,4,11,Roof,roof_materials,A_structural,binary,binary,-0.73,0.14,,,,,,medium,"1 if roof type is mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,1363.0,0.58,se,Tanzania LSMS 2016 renter households; OLS with district fixed effects (not reported),pct_premium,-52.279065215294686,6.746725861262835,100*(exp(b - se^2/2) - 1),reported,-0.14035425356565667,0.026917254108482107,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.2142857142857135,1353.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,True
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T3-c4,3,4,11,Floor,flooring,B_interior,binary,binary,-0.28,0.08,,,,,,medium,"1 if floor is mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,1363.0,0.58,se,Tanzania LSMS 2016 renter households; OLS with district fixed effects (not reported),pct_premium,-24.663090102846365,6.046269931645805,100*(exp(b - se^2/2) - 1),reported,-0.09472441934290148,0.02706411981225756,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5000000000000004,1353.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T4-c1,4,1,12,External wall,roof_materials,A_structural,binary,binary,0.14,0.13,,,,,,medium,"1 if external wall is in mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,662.0,0.75,se,Malawi LSMS 2014 renter households; OLS with district fixed effects (not reported),pct_premium,14.059493604345352,14.953559385143956,100*(exp(b - se^2/2) - 1),reported,0.042138102176325735,0.0391282377351596,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.076923076923077,652.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T4-c1,4,1,12,Number of rooms,bedrooms,A_structural,level,count,0.5,0.07,,,,,,medium,"Number of rooms rented (total rooms, not bedrooms); parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,662.0,0.75,se,Malawi LSMS 2014 renter households; OLS with district fixed effects (not reported),semi_elasticity,50.0,7.000000000000001,100*b/1 (per unit count),reported,0.2693940491899717,0.037715166886596034,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.142857142857142,652.0,count,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,True
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T4-c4,4,4,12,Dwelling,dwelling_type,A_structural,binary,binary,-0.01,0.12,,,,,,medium,"1 if the rented room is located within a house, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,1479.0,0.65,se,Malawi LSMS 2016 renter households; OLS with district fixed effects (not reported),pct_premium,-1.7052924440454476,11.880598004990016,100*(exp(b - se^2/2) - 1),reported,-0.002174236737031047,0.02609084084437256,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.08333333333333334,1469.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T4-c4,4,4,12,Roof,roof_materials,A_structural,binary,binary,0.34,0.1,,,,,,medium,"1 if roof type is mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,1479.0,0.65,se,Malawi LSMS 2016 renter households; OLS with district fixed effects (not reported),pct_premium,39.7940385222467,14.049475905635939,100*(exp(b - se^2/2) - 1),reported,0.08836207606623302,0.02598884590183324,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4,1469.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T4-c4,4,4,12,Floor,flooring,B_interior,binary,binary,-0.15,0.06,,,,,,medium,"1 if floor is mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,1479.0,0.65,se,Malawi LSMS 2016 renter households; OLS with district fixed effects (not reported),pct_premium,-14.083990442181726,5.164247858550347,100*(exp(b - se^2/2) - 1),reported,-0.06508893971228141,0.02603557588491257,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5,1469.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T4-c4,4,4,12,External wall,roof_materials,A_structural,binary,binary,0.17,0.12,,,,,,medium,"1 if external wall is in mud, 0 otherwise; parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,1479.0,0.65,se,Malawi LSMS 2016 renter households; OLS with district fixed effects (not reported),pct_premium,17.680130588969377,14.223658215844385,100*(exp(b - se^2/2) - 1),reported,0.03693688896050249,0.026073098089766465,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4166666666666667,1469.0,binary,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,False
33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a,33b79cf36579ae3f85aa1db50b2d2c31cb4ba23a:T4-c4,4,4,12,Number of rooms,bedrooms,A_structural,level,count,0.41,0.05,,,,,,medium,"Number of rooms rented (total rooms, not bedrooms); parentheses not labelled in table, assumed standard errors (no stars printed)","natural log of monthly house rent (USD), renter households",log,OLS,1479.0,0.65,se,Malawi LSMS 2016 renter households; OLS with district fixed effects (not reported),semi_elasticity,41.0,5.0,100*b/1 (per unit count),reported,0.2092109048991957,0.02551352498770679,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.2,1469.0,count,,2021.0,Uganda,,,2010.0,2016.0,rental,rent,journal,False,True,unknown,Ridge;LASSO;regression tree;bagging;random forest;boosting,2013.0,ols,journal,True,True,True
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c1,4,1,6,Number of bedrooms,bedrooms,A_structural,level,count,0.03,0.00072,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.45; log-likelihood 14,156.1; year/month and city dummies included",semi_elasticity,3.0,0.07200000000000001,100*b/1 (per unit count),reported,0.14807464661758551,0.0035537915188220527,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),41.666666666666664,77444.0,count,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c1,4,1,6,"Lot size, sq. ft",lot_size,A_structural,level,1000 sqft,0.07,0.003,,,***,,,medium,"Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says sq. ft but Table 3 reports lot size in thousands of sq ft and the magnitude (0.07 per unit) is only plausible per 1,000 sq ft; unit scaling uncertain.","Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.45; log-likelihood 14,156.1; year/month and city dummies included",semi_elasticity,0.07534737291696807,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.08355292463937246,0.0035808396274016768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.333333333333336,77444.0,1000sqft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c1,4,1,6,"Living area, sq. ft",living_area,A_structural,level,1000 sqft,0.18,0.004,,,***,,,medium,"Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says sq. ft but Table 3 reports living area in thousands of sq ft and the magnitude (0.18-0.23 per unit) is only plausible per 1,000 sq ft; unit scaling uncertain.","Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.45; log-likelihood 14,156.1; year/month and city dummies included",semi_elasticity,0.193750387500775,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.15962967878181286,0.0035473261951513963,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),45.0,77444.0,1000sqft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c1,4,1,6,"Euclidean distance to coastline, ft",water_proximity,E_environment,level,1000 ft,-0.01,0.00094,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says ft but Table 3 reports distance in thousands of ft (mean ~1.9-2.1); unit scaling uncertain.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.45; log-likelihood 14,156.1; year/month and city dummies included",semi_elasticity,-3.280839895013123,0.3083989501312336,100*b/0.3048 (X per 1000ft->km),reported,-0.03819980624534107,0.003590781787062061,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.638297872340425,77444.0,1000ft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c1,4,1,6,"Euclidean distance to major road, ft",highway_distance,D_location,level,1000 ft,0.01,0.0006,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says ft but Table 3 reports distance in thousands of ft; unit scaling uncertain.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.45; log-likelihood 14,156.1; year/month and city dummies included",semi_elasticity,3.280839895013123,0.19685039370078738,100*b/0.3048 (X per 1000ft->km),reported,0.05978295620628476,0.003586977372377085,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.666666666666668,77444.0,1000ft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c1,4,1,6,FEMA 100-year floodplain,flood_risk,E_environment,binary,binary,0.05,0.004,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. 1 if property lies in a FEMA 100-year floodplain.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.45; log-likelihood 14,156.1; year/month and city dummies included",pct_premium,5.1262686240893585,0.42050843855040965,100*(exp(b - se^2/2) - 1),reported,0.04487231263223542,0.0035897850105788332,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.5,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c2,4,2,6,Number of bedrooms,bedrooms,A_structural,level,count,0.04,0.002,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.47; log-likelihood 25,291.4; year/month and city dummies included",semi_elasticity,4.0,0.2,100*b/1 (per unit count),reported,0.08258119788141761,0.004129059894070881,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.0,58254.0,count,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c2,4,2,6,"Lot size, sq. ft",lot_size,A_structural,level,1000 sqft,0.001,8.4e-05,,,***,,,medium,"Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says sq. ft but Table 3 reports lot size in thousands of sq ft and the magnitude (0.07 per unit) is only plausible per 1,000 sq ft; unit scaling uncertain.","Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.47; log-likelihood 25,291.4; year/month and city dummies included",semi_elasticity,0.0010763910416709723,9.041684750036166e-05,100*b/92.903 (X per 1000sqft->m2),reported,0.04926405911555707,0.004138180965706794,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.904761904761905,58254.0,1000sqft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c2,4,2,6,"Living area, sq. ft",living_area,A_structural,level,1000 sqft,0.23,0.002,,,***,,,medium,"Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says sq. ft but Table 3 reports living area in thousands of sq ft and the magnitude (0.18-0.23 per unit) is only plausible per 1,000 sq ft; unit scaling uncertain.","Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.47; log-likelihood 25,291.4; year/month and city dummies included",semi_elasticity,0.2475699395843236,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.4301387872772204,0.0037403372806714815,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),115.0,58254.0,1000sqft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c2,4,2,6,"Euclidean distance to coastline, ft",water_proximity,E_environment,level,1000 ft,-0.03,0.001,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says ft but Table 3 reports distance in thousands of ft (mean ~1.9-2.1); unit scaling uncertain.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.47; log-likelihood 25,291.4; year/month and city dummies included",semi_elasticity,-9.84251968503937,0.32808398950131235,100*b/0.3048 (X per 1000ft->km),reported,-0.12334717183492869,0.004111572394497623,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.0,58254.0,1000ft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c2,4,2,6,"Euclidean distance to major road, ft",highway_distance,D_location,level,1000 ft,0.01,0.002,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says ft but Table 3 reports distance in thousands of ft; unit scaling uncertain.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.47; log-likelihood 25,291.4; year/month and city dummies included",semi_elasticity,3.280839895013123,0.6561679790026247,100*b/0.3048 (X per 1000ft->km),reported,0.020711614722242564,0.004142322944448513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,58254.0,1000ft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c2,4,2,6,FEMA 100-year floodplain,flood_risk,E_environment,binary,binary,-0.03,0.004,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. 1 if property lies in a FEMA 100-year floodplain.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.47; log-likelihood 25,291.4; year/month and city dummies included",pct_premium,-2.9562229984706034,0.3881782134194033,100*(exp(b - se^2/2) - 1),reported,-0.031059096042471132,0.004141212805662818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.5,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c1,4,1,6,SLR exposure less than 2 ft,flood_risk,E_environment,binary,binary,-0.12,0.02,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.45; log-likelihood 14,156.1; year/month and city dummies included",pct_premium,-11.325692963295964,1.773840873434315,100*(exp(b - se^2/2) - 1),reported,-0.021555417766905696,0.003592569627817616,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c2,4,2,6,SLR exposure less than 2 ft,flood_risk,E_environment,binary,binary,0.02,0.03,,,,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.47; log-likelihood 25,291.4; year/month and city dummies included",pct_premium,1.974235270363689,3.0606040200802673,100*(exp(b - se^2/2) - 1),reported,0.0027621305956689606,0.00414319589350344,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6666666666666667,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c1,4,1,6,SLR exposure 2 to 3 ft,flood_risk,E_environment,binary,binary,-0.02,0.01,,,*,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.45; log-likelihood 14,156.1; year/month and city dummies included",pct_premium,-1.9850335401682129,0.9801986733067553,100*(exp(b - se^2/2) - 1),reported,-0.007186623481896806,0.003593311740948403,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c2,4,2,6,SLR exposure 2 to 3 ft,flood_risk,E_environment,binary,binary,-0.07,0.01,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.47; log-likelihood 25,291.4; year/month and city dummies included",pct_premium,-6.765279861957419,0.9323938199059483,100*(exp(b - se^2/2) - 1),reported,-0.028990291948412183,0.004141470278344598,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.000000000000001,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c1,4,1,6,SLR exposure 3 to 4 ft,flood_risk,E_environment,binary,binary,0.03,0.01,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.45; log-likelihood 14,156.1; year/month and city dummies included",pct_premium,3.040301251486577,1.030454533953517,100*(exp(b - se^2/2) - 1),reported,0.010779587266368252,0.003593195755456084,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c2,4,2,6,SLR exposure 3 to 4 ft,flood_risk,E_environment,binary,binary,-0.03,0.01,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.47; log-likelihood 25,291.4; year/month and city dummies included",pct_premium,-2.9602987515132573,0.9704455335485083,100*(exp(b - se^2/2) - 1),reported,-0.01242867504356977,0.004142891681189923,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c1,4,1,6,SLR exposure 4 to 5 ft,flood_risk,E_environment,binary,binary,0.06,0.01,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.45; log-likelihood 14,156.1; year/month and city dummies included",pct_premium,6.1783456045305885,1.0618365465453596,100*(exp(b - se^2/2) - 1),reported,0.021555417766905696,0.003592569627817616,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c2,4,2,6,SLR exposure 4 to 5 ft,flood_risk,E_environment,binary,binary,-0.01,0.01,,,,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.47; log-likelihood 25,291.4; year/month and city dummies included",pct_premium,-0.9999667504977716,0.9900498337491681,100*(exp(b - se^2/2) - 1),reported,-0.004143176137422553,0.004143176137422553,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c1,4,1,6,SLR exposure 5 to 6 ft,flood_risk,E_environment,binary,binary,0.04,0.01,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.45; log-likelihood 14,156.1; year/month and city dummies included",pct_premium,4.075873495467031,1.0408107741923882,100*(exp(b - se^2/2) - 1),reported,0.014372133578535827,0.003593033394633957,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T4-c2,4,2,6,SLR exposure 5 to 6 ft,flood_risk,E_environment,binary,binary,-0.01,0.005,,,*,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; overall model without owner-type interactions; spatial lag rho = 0.47; log-likelihood 25,291.4; year/month and city dummies included",pct_premium,-0.9962541796406543,0.49502491687458405,100*(exp(b - se^2/2) - 1),reported,-0.008286138918938086,0.004143069459469042,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,Number of bedrooms,bedrooms,A_structural,level,count,0.03,0.001,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",semi_elasticity,3.0,0.1,100*b/1 (per unit count),reported,0.1071811429604603,0.0035727047653486767,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.0,77444.0,count,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,"Lot size, sq. ft",lot_size,A_structural,level,1000 sqft,0.07,0.003,,,***,,,medium,"Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says sq. ft but Table 3 reports lot size in thousands of sq ft and the magnitude (0.07 per unit) is only plausible per 1,000 sq ft; unit scaling uncertain.","Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",semi_elasticity,0.07534737291696807,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.08355292463937246,0.0035808396274016768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.333333333333336,77444.0,1000sqft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,"Living area, sq. ft",living_area,A_structural,level,1000 sqft,0.18,0.004,,,***,,,medium,"Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says sq. ft but Table 3 reports living area in thousands of sq ft and the magnitude (0.18-0.23 per unit) is only plausible per 1,000 sq ft; unit scaling uncertain.","Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",semi_elasticity,0.193750387500775,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.15962967878181286,0.0035473261951513963,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),45.0,77444.0,1000sqft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,"Euclidean distance to coastline, ft",water_proximity,E_environment,level,1000 ft,-0.01,0.001,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says ft but Table 3 reports distance in thousands of ft (mean ~1.9-2.1); unit scaling uncertain.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",semi_elasticity,-3.280839895013123,0.32808398950131235,100*b/0.3048 (X per 1000ft->km),reported,-0.03591086779904764,0.0035910867799047643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.0,77444.0,1000ft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,"Euclidean distance to major road, ft",highway_distance,D_location,level,1000 ft,0.01,0.001,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says ft but Table 3 reports distance in thousands of ft; unit scaling uncertain.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",semi_elasticity,3.280839895013123,0.32808398950131235,100*b/0.3048 (X per 1000ft->km),reported,0.03591086779904764,0.0035910867799047643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.0,77444.0,1000ft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,FEMA 100-year floodplain,flood_risk,E_environment,binary,binary,0.05,0.004,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. 1 if property lies in a FEMA 100-year floodplain.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",pct_premium,5.1262686240893585,0.42050843855040965,100*(exp(b - se^2/2) - 1),reported,0.04487231263223542,0.0035897850105788332,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.5,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,Number of bedrooms,bedrooms,A_structural,level,count,0.04,0.002,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",semi_elasticity,4.0,0.2,100*b/1 (per unit count),reported,0.08258119788141761,0.004129059894070881,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.0,58254.0,count,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,"Lot size, sq. ft",lot_size,A_structural,level,1000 sqft,0.001,8.4e-05,,,***,,,medium,"Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says sq. ft but Table 3 reports lot size in thousands of sq ft and the magnitude (0.07 per unit) is only plausible per 1,000 sq ft; unit scaling uncertain.","Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",semi_elasticity,0.0010763910416709723,9.041684750036166e-05,100*b/92.903 (X per 1000sqft->m2),reported,0.04926405911555707,0.004138180965706794,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.904761904761905,58254.0,1000sqft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,"Living area, sq. ft",living_area,A_structural,level,1000 sqft,0.23,0.002,,,***,,,medium,"Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says sq. ft but Table 3 reports living area in thousands of sq ft and the magnitude (0.18-0.23 per unit) is only plausible per 1,000 sq ft; unit scaling uncertain.","Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",semi_elasticity,0.2475699395843236,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.4301387872772204,0.0037403372806714815,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),115.0,58254.0,1000sqft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,"Euclidean distance to coastline, ft",water_proximity,E_environment,level,1000 ft,-0.03,0.001,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says ft but Table 3 reports distance in thousands of ft (mean ~1.9-2.1); unit scaling uncertain.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",semi_elasticity,-9.84251968503937,0.32808398950131235,100*b/0.3048 (X per 1000ft->km),reported,-0.12334717183492869,0.004111572394497623,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.0,58254.0,1000ft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,"Euclidean distance to major road, ft",highway_distance,D_location,level,1000 ft,0.01,0.002,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Table header says ft but Table 3 reports distance in thousands of ft; unit scaling uncertain.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",semi_elasticity,3.280839895013123,0.6561679790026247,100*b/0.3048 (X per 1000ft->km),reported,0.020711614722242564,0.004142322944448513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,58254.0,1000ft,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,FEMA 100-year floodplain,flood_risk,E_environment,binary,binary,-0.03,0.004,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. 1 if property lies in a FEMA 100-year floodplain.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",pct_premium,-2.9562229984706034,0.3881782134194033,100*(exp(b - se^2/2) - 1),reported,-0.031059096042471132,0.004141212805662818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.5,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,SLR exposure less than 2 ft & PHOs,flood_risk,E_environment,binary,binary,-0.1,0.03,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with primary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",pct_premium,-9.556966720110871,2.7145122541078783,100*(exp(b - se^2/2) - 1),reported,-0.011977155957252834,0.0035931467871758503,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.3333333333333335,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,SLR exposure less than 2 ft & PHOs,flood_risk,E_environment,binary,binary,-0.15,0.05,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with primary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",pct_premium,-14.036723639745773,4.303539882125289,100*(exp(b - se^2/2) - 1),reported,-0.012428675043569768,0.004142891681189923,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.9999999999999996,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,SLR exposure less than 2 ft & NPHOs,flood_risk,E_environment,binary,binary,-0.13,0.03,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with nonprimary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",pct_premium,-12.229962312952514,2.6342862927616837,100*(exp(b - se^2/2) - 1),reported,-0.015569532211288454,0.003592968971835797,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.333333333333334,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,SLR exposure less than 2 ft & NPHOs,flood_risk,E_environment,binary,binary,0.14,0.04,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with nonprimary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",pct_premium,14.935394780762001,4.601095195428909,100*(exp(b - se^2/2) - 1),reported,0.01449971648152996,0.004142776137579987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5000000000000004,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,SLR exposure 2 to 3 ft & PHOs,flood_risk,E_environment,binary,binary,-0.01,0.01,,,,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with primary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",pct_premium,-0.9999667504977716,0.9900498337491681,100*(exp(b - se^2/2) - 1),reported,-0.00359338133763527,0.0035933813376352697,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,SLR exposure 2 to 3 ft & PHOs,flood_risk,E_environment,binary,binary,-0.09,0.02,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with primary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",pct_premium,-8.625158268842092,1.8278623705424566,100*(exp(b - se^2/2) - 1),reported,-0.01864121293674717,0.004142491763721593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.5,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,SLR exposure 2 to 3 ft & NPHOs,flood_risk,E_environment,binary,binary,-0.03,0.01,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with nonprimary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",pct_premium,-2.9602987515132573,0.9704455335485083,100*(exp(b - se^2/2) - 1),reported,-0.010779587266368252,0.003593195755456084,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,SLR exposure 2 to 3 ft & NPHOs,flood_risk,E_environment,binary,binary,-0.05,0.02,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with nonprimary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",pct_premium,-4.896080236086586,1.9024588490014283,100*(exp(b - se^2/2) - 1),reported,-0.010357473641028283,0.004142989456411313,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,SLR exposure 3 to 4 ft & PHOs,flood_risk,E_environment,binary,binary,0.05,0.01,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with primary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",pct_premium,5.121853413527222,1.0512710963760241,100*(exp(b - se^2/2) - 1),reported,0.017964123386709174,0.0035928246773418346,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,SLR exposure 3 to 4 ft & PHOs,flood_risk,E_environment,binary,binary,-0.06,0.01,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with primary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",pct_premium,-5.828255346524447,0.9417645335842487,100*(exp(b - se^2/2) - 1),reported,-0.024851592442693186,0.004141932073782198,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,SLR exposure 3 to 4 ft & NPHOs,flood_risk,E_environment,binary,binary,-0.01,0.01,,,,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with nonprimary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",pct_premium,-0.9999667504977716,0.9900498337491681,100*(exp(b - se^2/2) - 1),reported,-0.00359338133763527,0.0035933813376352697,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,SLR exposure 3 to 4 ft & NPHOs,flood_risk,E_environment,binary,binary,0.003,0.01,,,,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with nonprimary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",pct_premium,0.2954355531886499,1.003004504503377,100*(exp(b - se^2/2) - 1),reported,0.0012429625494092154,0.004143208498030718,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,SLR exposure 4 to 5 ft & PHOs,flood_risk,E_environment,binary,binary,0.08,0.01,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with primary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",pct_premium,8.323290467566103,1.0832870676749586,100*(exp(b - se^2/2) - 1),reported,0.028735365246930312,0.003591920655866289,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,SLR exposure 4 to 5 ft & PHOs,flood_risk,E_environment,binary,binary,-0.002,0.01,,,,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with primary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",pct_premium,-0.20479001851185785,0.9980019986673331,100*(exp(b - se^2/2) - 1),reported,-0.0008286420552216176,0.004143210276108088,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,SLR exposure 4 to 5 ft & NPHOs,flood_risk,E_environment,binary,binary,0.002,0.01,,,,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with nonprimary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",pct_premium,0.19519024864151913,1.0020020013340003,100*(exp(b - se^2/2) - 1),reported,0.000718680721885832,0.0035934036094291593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,SLR exposure 4 to 5 ft & NPHOs,flood_risk,E_environment,binary,binary,-0.01,0.01,,,,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with nonprimary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",pct_premium,-0.9999667504977716,0.9900498337491681,100*(exp(b - se^2/2) - 1),reported,-0.004143176137422553,0.004143176137422553,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,SLR exposure 5 to 6 ft & PHOs,flood_risk,E_environment,binary,binary,0.05,0.01,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with primary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",pct_premium,5.121853413527222,1.0512710963760241,100*(exp(b - se^2/2) - 1),reported,0.017964123386709174,0.0035928246773418346,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,SLR exposure 5 to 6 ft & PHOs,flood_risk,E_environment,binary,binary,-0.003,0.01,,,,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with primary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",pct_premium,-0.3045353475167323,0.997004495503373,100*(exp(b - se^2/2) - 1),reported,-0.0012429625494092154,0.004143208498030718,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c1,5,1,7,SLR exposure 5 to 6 ft & NPHOs,flood_risk,E_environment,binary,binary,0.01,0.01,,,.,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with nonprimary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,77454.0,0.79,se,"Pinellas County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.45; log-likelihood 14,083.7; year/month and city dummies included",pct_premium,0.9999665838355432,1.010050167084168,100*(exp(b - se^2/2) - 1),reported,0.00359338133763527,0.0035933813376352697,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,77444.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92,35e9cf817db8c35d9d40580566f6516793f3cc92:T5-c2,5,2,7,SLR exposure 5 to 6 ft & NPHOs,flood_risk,E_environment,binary,binary,-0.02,0.01,,,***,,,medium,Dependent-variable transformation not stated in the paper (see model notes); coefficient recorded exactly as printed. Dummy = 1 if the property centroid falls within the NOAA sea-level-rise inundation layer for the stated scenario band (elevation exposure); mapped to flood_risk as nearest leaf. Interaction of the SLR exposure dummy with nonprimary homeowner (homestead-exemption) status; effect for that buyer group.,"Housing price (unadjusted sale price, USD); transformation not stated - authors interpret coefficients as percentage discounts and intercept of 2.50 is consistent with log10(price in 1,000 USD)",log,spatial_lag,58264.0,0.81,se,"Miami-Dade County, detached single-family homes within 5,000-ft coastal band, Jan 2004 - Mar 2019; SLR exposure dummies interacted with primary (PHO) / nonprimary (NPHO) homeowner status; spatial lag rho = 0.47; log-likelihood 25,265.1; year/month and city dummies included",pct_premium,-1.9850335401682129,0.9801986733067553,100*(exp(b - se^2/2) - 1),reported,-0.008286138918938086,0.004143069459469042,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,58254.0,binary,,2020.0,United States,North America,High income,2004.0,2019.0,single_family,transaction,journal,True,True,unknown,,2011.5,spatial,journal,True,True,False
36eac2e74fd054fe7faa7ad4134c3aa524d5616d,36eac2e74fd054fe7faa7ad4134c3aa524d5616d,36eac2e74fd054fe7faa7ad4134c3aa524d5616d:T4-c1,4,1,9,ln (FA),living_area,A_structural,log,m2,-0.43255,,7.81141,0.0,,,,medium,"Floor area, log; coefficient printed with a leading dash (negative) while zcalc printed without sign (absolute value); z-statistic recorded in t","ln(UV): natural log of unit value (price per m2, R$/m2) of apartments",log,spatial_error,190.0,0.8169,t,"Training partition (190 apartments, Centro/Agronomica/Trindade); spatial error (CAR) model, distance-band weights 525 m; z-statistics and p-values printed",elasticity,-0.43255,0.05537412579803134,b (log-log),|b/t|,0.5031582297904399,0.06441324034846971,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.81141,180.0,m2,,2023.0,Brazil,South America,Upper middle income,2020.0,2020.0,condo_apartment,listing,journal,False,False,unknown,,2020.0,spatial,journal,True,True,True
36eac2e74fd054fe7faa7ad4134c3aa524d5616d,36eac2e74fd054fe7faa7ad4134c3aa524d5616d,36eac2e74fd054fe7faa7ad4134c3aa524d5616d:T4-c1,4,1,9,ln (DA),cbd_distance,D_location,log,m,-0.1177,,5.35113,0.0,,,,medium,"Distance to Beira-Mar Avenue (seaside avenue in the Centro used as valuation pole), log of metres; could alternatively be read as water proximity; coefficient printed with a leading dash (negative) while zcalc printed without sign (absolute value); z-statistic recorded in t","ln(UV): natural log of unit value (price per m2, R$/m2) of apartments",log,spatial_error,190.0,0.8169,t,"Training partition (190 apartments, Centro/Agronomica/Trindade); spatial error (CAR) model, distance-band weights 525 m; z-statistics and p-values printed",elasticity,-0.1177,0.021995354252279425,b (log-log),|b/t|,0.37046940095074155,0.06923199416772562,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.35113,180.0,m,,2023.0,Brazil,South America,Upper middle income,2020.0,2020.0,condo_apartment,listing,journal,False,False,unknown,,2020.0,spatial,journal,True,True,False
36eac2e74fd054fe7faa7ad4134c3aa524d5616d,36eac2e74fd054fe7faa7ad4134c3aa524d5616d,36eac2e74fd054fe7faa7ad4134c3aa524d5616d:T4-c1,4,1,9,NB,bedrooms,A_structural,level,count,0.05794,,2.76309,0.00573,,,,high,; z-statistic recorded in t,"ln(UV): natural log of unit value (price per m2, R$/m2) of apartments",log,spatial_error,190.0,0.8169,t,"Training partition (190 apartments, Centro/Agronomica/Trindade); spatial error (CAR) model, distance-band weights 525 m; z-statistics and p-values printed",semi_elasticity,5.794,2.0969277149857586,100*b/1 (per unit count),|b/t|,0.20171513788160145,0.07300346274699755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.76309,180.0,count,,2023.0,Brazil,South America,Upper middle income,2020.0,2020.0,condo_apartment,listing,journal,False,False,unknown,,2020.0,spatial,journal,True,True,False
36eac2e74fd054fe7faa7ad4134c3aa524d5616d,36eac2e74fd054fe7faa7ad4134c3aa524d5616d,36eac2e74fd054fe7faa7ad4134c3aa524d5616d:T4-c1,4,1,9,BT,bathrooms,A_structural,level,count,0.03583,,2.12263,0.03379,,,,high,; z-statistic recorded in t,"ln(UV): natural log of unit value (price per m2, R$/m2) of apartments",log,spatial_error,190.0,0.8169,t,"Training partition (190 apartments, Centro/Agronomica/Trindade); spatial error (CAR) model, distance-band weights 525 m; z-statistics and p-values printed",semi_elasticity,3.583,1.6880002638236529,100*b/1 (per unit count),|b/t|,0.1562678263387226,0.07361990848085753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.12263,180.0,count,,2023.0,Brazil,South America,Upper middle income,2020.0,2020.0,condo_apartment,listing,journal,False,False,unknown,,2020.0,spatial,journal,True,True,False
36eac2e74fd054fe7faa7ad4134c3aa524d5616d,36eac2e74fd054fe7faa7ad4134c3aa524d5616d,36eac2e74fd054fe7faa7ad4134c3aa524d5616d:T4-c1,4,1,9,NG,parking,A_structural,level,count,0.1852,,8.92755,0.0,,,,high,Number of parking spaces; z-statistic recorded in t,"ln(UV): natural log of unit value (price per m2, R$/m2) of apartments",log,spatial_error,190.0,0.8169,t,"Training partition (190 apartments, Centro/Agronomica/Trindade); spatial error (CAR) model, distance-band weights 525 m; z-statistics and p-values printed",semi_elasticity,18.52,2.0744773202054314,100*b/1 (per unit count),|b/t|,0.553981619623975,0.06205304026569159,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.92755,180.0,count,,2023.0,Brazil,South America,Upper middle income,2020.0,2020.0,condo_apartment,listing,journal,False,False,unknown,,2020.0,spatial,journal,True,True,False
36eac2e74fd054fe7faa7ad4134c3aa524d5616d,36eac2e74fd054fe7faa7ad4134c3aa524d5616d,36eac2e74fd054fe7faa7ad4134c3aa524d5616d:T4-c1,4,1,9,SP,pool,C_exterior,binary,binary,0.09129,,3.47056,0.00052,,,,high,Swimming pool (building); z-statistic recorded in t,"ln(UV): natural log of unit value (price per m2, R$/m2) of apartments",log,spatial_error,190.0,0.8169,t,"Training partition (190 apartments, Centro/Agronomica/Trindade); spatial error (CAR) model, distance-band weights 525 m; z-statistics and p-values printed",pct_premium,9.520772320878468,2.8818435052579914,100*(exp(b - se^2/2) - 1),|b/t|,0.25043688651135276,0.07216036792660344,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.47056,180.0,binary,,2023.0,Brazil,South America,Upper middle income,2020.0,2020.0,condo_apartment,listing,journal,False,False,unknown,,2020.0,spatial,journal,True,True,False
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,DISTLRT1,transit_distance,D_location,dummy,binary,0.122668,,4.6,0.0,,,,high,Dummy: within 1000 m of nearest LRT station. t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",pct_premium,13.010713358773929,3.0147235140793778,100*(exp(b - se^2/2) - 1),|b/t|,0.1216369489560853,0.02644281499045333,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.6,1409.0,binary,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,False
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,DISTLRT2,transit_distance,D_location,dummy,binary,0.098065,,4.6,0.0,,,,high,Dummy: 1001-2000 m from nearest LRT station. t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",pct_premium,10.278385631147025,2.3515016583287394,100*(exp(b - se^2/2) - 1),|b/t|,0.1216369489560853,0.02644281499045333,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.6,1409.0,binary,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,False
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,FLOORAREA,living_area,A_structural,level,sqft,0.000436,,15.8,0.0,,,,high,Floor area in square feet. t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",semi_elasticity,0.46930649416854386,0.029702942668895182,100*b/0.092903 (X per sqft->m2),|b/t|,0.38795470176891544,0.024554095048665535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.8,1409.0,sqft,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,False
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,LOTAREA,lot_size,A_structural,level,sqft,0.000214,,16.5,0.0,,,,high,Lot (land) area in square feet. t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",semi_elasticity,0.23034768291758803,0.013960465631368973,100*b/0.092903 (X per sqft->m2),|b/t|,0.402409102160797,0.024388430433987692,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.5,1409.0,sqft,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,False
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,BEDROOMS,bedrooms,A_structural,dummy,binary,0.041764,,2.3,0.02,,,,high,Dummy: four or more bedrooms. t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",pct_premium,4.24765065788375,1.8932681364504789,100*(exp(b - se^2/2) - 1),|b/t|,0.06115875003530312,0.0265907608849144,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3,1409.0,binary,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,False
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,SHOPCENTRE,commercial_distance,D_location,level,m,-7.7e-05,,-5.4,0.0,,,,high,Distance to nearest shopping centre (m). t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",semi_elasticity,-7.7,1.425925925925926,100*b/0.001 (X per m->km),|b/t|,-0.14239349741052285,0.026369166187133863,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.4,1409.0,m,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,False
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,HOSPITAL,hospital_distance,D_location,level,m,0.0001,,10.3,0.0,,,,high,Distance to nearest hospital (m). t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",semi_elasticity,10.0,0.9708737864077669,100*b/0.001 (X per m->km),|b/t|,0.26461716290343273,0.025690986689653663,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.3,1409.0,m,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,True
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,PARK,green_space,E_environment,level,m,-2.5e-05,,-2.3,0.02,,,,high,Distance to nearest recreational park (m). t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",semi_elasticity,-2.5,1.0869565217391304,100*b/0.001 (X per m->km),|b/t|,-0.06115875003530312,0.0265907608849144,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3,1409.0,m,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,False
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,PRIMARYSCH,school_distance,D_location,level,m,6.6e-05,,3.9,0.0,,,,high,Distance to nearest primary school (m). t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",semi_elasticity,6.6000000000000005,1.6923076923076923,100*b/0.001 (X per m->km),|b/t|,0.10334217354767049,0.026497993217351412,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9,1409.0,m,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,False
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,HP_SECONDARYSCH,school_distance,D_location,level,m,-6.5e-05,,-7.4,0.0,,,,high,Distance to nearest high-performing secondary school (m). t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",semi_elasticity,-6.5,0.8783783783783783,100*b/0.001 (X per m->km),|b/t|,-0.19341795277140675,0.02613756118532523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.4,1409.0,m,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,False
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,CBD,cbd_distance,D_location,level,m,-2.3e-05,,-3.5,0.0,,,,high,Distance to central business district (m). t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",semi_elasticity,-2.3,0.6571428571428571,100*b/0.001 (X per m->km),|b/t|,-0.09283950270748297,0.026525572202137988,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5,1409.0,m,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,False
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,FOREST,green_space,E_environment,level,m,-3.2e-05,,-3.0,0.0,,,,high,Distance to nearest forest (m). t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",semi_elasticity,-3.1999999999999997,1.0666666666666664,100*b/0.001 (X per m->km),|b/t|,-0.07966785775922171,0.026555952586407236,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,1409.0,m,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,False
3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e,3777ce734c4a5c9380dfa227ede8503f4f25b44e:T2-c1,2,1,5,INDUSTRIAL,hazard_site,E_environment,level,m,3.3e-05,,6.0,0.0,,,,high,Distance to nearest industrial area (m). t-ratio and p-value (Sig.) printed; no stars used.,ln sale price (MYR),log,OLS,1419.0,0.62,t,"Double-storey terraced houses, Greater Kuala Lumpur, 2009-2010; R2 from text (62%), not printed in table",semi_elasticity,3.3000000000000003,0.55,100*b/0.001 (X per m->km),|b/t|,0.15784009252939693,0.026306682088232818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,1409.0,m,,2021.0,Malaysia,Asia,Upper middle income,2009.0,2010.0,single_family,transaction,journal,False,True,OLS,,2009.5,ols,journal,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T2-c1,II,1,2,LOG(AREA),living_area,A_structural,log,m2,0.89,,8.35,0.0,,,,high,Floor space 50-200 m2,ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Preliminary regression with all 11 features; R2 0.72, adj 0.70",elasticity,0.89,0.1065868263473054,b (log-log),|b/t|,0.539302056525832,0.06458707263782419,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.35,170.0,m2,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T2-c1,II,1,2,LOG(DECORATION),condition,A_structural,log,index,0.04,,1.59,0.11,,,,high,"Decoration grade 1-4 (ordinal), entered in log",ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Preliminary regression with all 11 features; R2 0.72, adj 0.70",elasticity,0.04,0.025157232704402514,b (log-log),|b/t|,0.1210506719446535,0.07613249807839843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.59,170.0,index,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T2-c1,II,1,2,LOG(BEDROOM),bedrooms,A_structural,log,count,0.07,,0.89,0.37,,,,high,,ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Preliminary regression with all 11 features; R2 0.72, adj 0.70",elasticity,0.07,0.07865168539325844,b (log-log),|b/t|,0.06810141212888834,0.07651844059425657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.89,170.0,count,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T2-c1,II,1,2,LOG(BATHROOM),bathrooms,A_structural,log,count,0.06,,1.1,0.27,,,,high,,ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Preliminary regression with all 11 features; R2 0.72, adj 0.70",elasticity,0.06,0.054545454545454536,b (log-log),|b/t|,0.08406749786442289,0.07642499805856624,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1,170.0,count,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T2-c1,II,1,2,LOG(FLOORLEVEL),floor_level,A_structural,log,count,-0.01,,-0.84,0.4,,,,high,,ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Preliminary regression with all 11 features; R2 0.72, adj 0.70",elasticity,-0.01,0.011904761904761906,b (log-log),|b/t|,-0.06429177288589208,0.07653782486415724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.84,170.0,count,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T2-c1,II,1,2,LOG(YEAR),age,A_structural,log,years,-0.16,,-5.22,0.0,,,,high,"YEAR = house age in years (mean 8.6), not year built",ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Preliminary regression with all 11 features; R2 0.72, adj 0.70",elasticity,-0.16,0.030651340996168584,b (log-log),|b/t|,-0.3716753494852454,0.07120217423088991,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.22,170.0,years,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T2-c1,II,1,2,LOG(GREENCOVERAGE),green_space,E_environment,log,share,0.05,,2.79,0.01,,,,high,Green coverage rate of the estate in percent,ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Preliminary regression with all 11 features; R2 0.72, adj 0.70",elasticity,0.05,0.017921146953405017,b (log-log),|b/t|,0.20924627937267332,0.07499866644181839,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.79,170.0,share,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T2-c1,II,1,2,LOG(DIST_CBD),cbd_distance,D_location,log,m,-0.09,,-2.04,0.04,,,,high,Distance to Yan Shi Kou CBD in metres,ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Preliminary regression with all 11 features; R2 0.72, adj 0.70",elasticity,-0.09,0.044117647058823525,b (log-log),|b/t|,-0.1545802354626539,0.07577462522679113,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.04,170.0,m,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T3-c1,III,1,3,LOG(AREA),living_area,A_structural,log,m2,0.92,,9.06,0.0,,,,high,Floor space 50-200 m2,ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Stepwise regression (RING and HALL dropped); R2 0.72, adj 0.70",elasticity,0.92,0.10154525386313466,b (log-log),|b/t|,0.570631709690132,0.06298363241612935,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.06,170.0,m2,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T3-c1,III,1,3,LOG(DECORATION),condition,A_structural,log,index,0.05,,1.68,0.09,,,,high,"Decoration grade 1-4 (ordinal), entered in log",ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Stepwise regression (RING and HALL dropped); R2 0.72, adj 0.70",elasticity,0.05,0.029761904761904764,b (log-log),|b/t|,0.1277936474313566,0.0760676472805694,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.68,170.0,index,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T3-c1,III,1,3,LOG(BEDROOM),bedrooms,A_structural,log,count,0.07,,0.94,0.35,,,,high,,ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Stepwise regression (RING and HALL dropped); R2 0.72, adj 0.70",elasticity,0.07,0.07446808510638299,b (log-log),|b/t|,0.07190807475538405,0.07649795186742984,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.94,170.0,count,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T3-c1,III,1,3,LOG(BATHROOM),bathrooms,A_structural,log,count,0.06,,1.06,0.29,,,,high,,ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Stepwise regression (RING and HALL dropped); R2 0.72, adj 0.70",elasticity,0.06,0.056603773584905655,b (log-log),|b/t|,0.0810309463891698,0.0764442890463866,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.06,170.0,count,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T3-c1,III,1,3,LOG(FLOORLEVEL),floor_level,A_structural,log,count,-0.01,,-0.84,0.4,,,,high,,ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Stepwise regression (RING and HALL dropped); R2 0.72, adj 0.70",elasticity,-0.01,0.011904761904761906,b (log-log),|b/t|,-0.06429177288589208,0.07653782486415724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.84,170.0,count,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T3-c1,III,1,3,LOG(YEAR),age,A_structural,log,years,-0.17,,-5.38,0.0,,,,high,"YEAR = house age in years (mean 8.6), not year built",ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Stepwise regression (RING and HALL dropped); R2 0.72, adj 0.70",elasticity,-0.17,0.03159851301115242,b (log-log),|b/t|,-0.3814313774053503,0.07089802554002794,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.38,170.0,years,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T3-c1,III,1,3,LOG(GREENCOVERAGE),green_space,E_environment,log,share,0.05,,2.76,0.01,,,,high,Green coverage rate of the estate in percent,ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Stepwise regression (RING and HALL dropped); R2 0.72, adj 0.70",elasticity,0.05,0.01811594202898551,b (log-log),|b/t|,0.2070933165634045,0.07503381034905961,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.76,170.0,share,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f,37a309783a11809263623703621db3a26e46597f:T3-c1,III,1,3,LOG(DIST_CBD),cbd_distance,D_location,log,m,-0.09,,-3.83,0.0,,,,high,Distance to Yan Shi Kou CBD in metres,ln(PRICE) (asking price),log,OLS,180.0,0.72,none,"Stepwise regression (RING and HALL dropped); R2 0.72, adj 0.70",elasticity,-0.09,0.02349869451697128,b (log-log),|b/t|,-0.28183952149450586,0.07358734242676393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.83,170.0,m,,2015.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,conference,False,False,unknown,,2014.0,ols,other,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c1,2,1,10,House Size ('000 sq ft),living_area,A_structural,level,1000 sqft,0.151,0.007,,,***,,,high,House size in thousands of square feet,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7417,se,All houses (full sample); boundary-segment FE + month/year FE; SE clustered by boundary segment,semi_elasticity,0.1625350472923168,0.007534737291696806,100*b/92.903 (X per 1000sqft->m2),reported,0.07885697025255631,0.0036556211375357232,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.57142857142857,74365.0,1000sqft,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c2,2,2,10,House Size ('000 sq ft),living_area,A_structural,level,1000 sqft,0.106,0.011,,,***,,,high,House size in thousands of square feet,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7502,se,"Houses within 1,000 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment",semi_elasticity,0.11409745041712305,0.011840301458380692,100*b/92.903 (X per 1000sqft->m2),reported,0.0641898678314615,0.006661212699491287,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.636363636363637,22444.0,1000sqft,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c3,2,3,10,House Size ('000 sq ft),living_area,A_structural,level,1000 sqft,0.1007,0.015,,,***,,,high,House size in thousands of square feet,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7462,se,Houses within 500 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,semi_elasticity,0.1083925778962669,0.016145865625064582,100*b/92.903 (X per 1000sqft->m2),reported,0.06282085609750315,0.009357625039350021,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.713333333333334,11375.0,1000sqft,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c4,2,4,10,House Size ('000 sq ft),living_area,A_structural,level,1000 sqft,0.1576,0.027,,,***,,,high,House size in thousands of square feet,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7733,se,Houses within 100 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,semi_elasticity,0.16963922816734522,0.02906255812511625,100*b/92.903 (X per 1000sqft->m2),reported,0.13286353590544833,0.02276215399395371,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.837037037037037,1896.0,1000sqft,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c1,2,1,10,Acreage,lot_size,A_structural,level,acres,0.0011,0.001,,,*,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7417,se,All houses (full sample); boundary-segment FE + month/year FE; SE clustered by boundary segment,semi_elasticity,2.718159196138819e-05,2.4710538146716536e-05,100*b/4046.86 (X per acre->m2),reported,0.004033711755824943,0.0036670106871135844,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1,74365.0,acre,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c2,2,2,10,Acreage,lot_size,A_structural,level,acres,0.0275,0.018,,,,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7502,se,"Houses within 1,000 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment",semi_elasticity,0.0006795397990347047,0.00044478968664089753,100*b/4046.86 (X per acre->m2),reported,0.010197353558835318,0.006674631420328571,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.527777777777778,22444.0,acre,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c3,2,3,10,Acreage,lot_size,A_structural,level,acres,0.0877,0.027,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7462,se,Houses within 500 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,semi_elasticity,0.00216711419546704,0.0006671845299613464,100*b/4046.86 (X per acre->m2),reported,0.03044099283584113,0.009371799390737862,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.248148148148148,11375.0,acre,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c4,2,4,10,Acreage,lot_size,A_structural,level,acres,0.1766,0.036,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7733,se,Houses within 100 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,semi_elasticity,0.00436388103671014,0.0008895793732817951,100*b/4046.86 (X per acre->m2),reported,0.11195159675168062,0.02282139005130522,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.905555555555556,1896.0,acre,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c1,2,1,10,Bathrooms,bathrooms,A_structural,level,count,0.0287,0.001,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7417,se,All houses (full sample); boundary-segment FE + month/year FE; SE clustered by boundary segment,semi_elasticity,2.87,0.1,100*b/1 (per unit count),reported,0.10466600252341897,0.003646899042627839,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.7,74365.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c2,2,2,10,Bathrooms,bathrooms,A_structural,level,count,0.0238,0.002,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7502,se,"Houses within 1,000 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment",semi_elasticity,2.3800000000000003,0.2,100*b/1 (per unit count),reported,0.07918283540906831,0.006654019782274648,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.9,22444.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c3,2,3,10,Bathrooms,bathrooms,A_structural,level,count,0.0256,0.003,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7462,se,Houses within 500 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,semi_elasticity,2.56,0.3,100*b/1 (per unit count),reported,0.07975489666253238,0.009346276952640514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.533333333333333,11375.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c4,2,4,10,Bathrooms,bathrooms,A_structural,level,count,0.0263,0.008,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7733,se,Houses within 100 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,semi_elasticity,2.63,0.8,100*b/1 (per unit count),reported,0.07528566969559436,0.02290058393782338,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2875,1896.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c1,2,1,10,Bedrooms,bedrooms,A_structural,level,count,0.0697,0.002,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7417,se,All houses (full sample); boundary-segment FE + month/year FE; SE clustered by boundary segment,semi_elasticity,6.97,0.2,100*b/1 (per unit count),reported,0.12676539398456219,0.0036374575031438215,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.85,74365.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c2,2,2,10,Bedrooms,bedrooms,A_structural,level,count,0.0603,0.003,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7502,se,"Houses within 1,000 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment",semi_elasticity,6.03,0.3,100*b/1 (per unit count),reported,0.13297557206122876,0.006615700102548695,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.099999999999998,22444.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c3,2,3,10,Bedrooms,bedrooms,A_structural,level,count,0.057,0.004,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7462,se,Houses within 500 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,semi_elasticity,5.7,0.4,100*b/1 (per unit count),reported,0.13243321416294637,0.009293558888627814,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.25,11375.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c4,2,4,10,Bedrooms,bedrooms,A_structural,level,count,0.0492,0.009,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7733,se,Houses within 100 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,semi_elasticity,4.92,0.8999999999999999,100*b/1 (per unit count),reported,0.12456828366310785,0.02278688115788558,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.466666666666667,1896.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c1,2,1,10,Air Conditioning,air_conditioning,A_structural,binary,binary,0.0796,0.002,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7417,se,All houses (full sample); boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,8.285167379378677,0.21657076789986002,100*(exp(b - se^2/2) - 1),reported,0.14441819999280453,0.0036285979897689577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),39.800000000000004,74365.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c2,2,2,10,Air Conditioning,air_conditioning,A_structural,binary,binary,0.0703,0.004,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7502,se,"Houses within 1,000 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment",pct_premium,7.282139937076226,0.4291319927905151,100*(exp(b - se^2/2) - 1),reported,0.11651373907861831,0.006629515737047983,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.575,22444.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c3,2,3,10,Air Conditioning,air_conditioning,A_structural,binary,binary,0.0813,0.005,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7462,se,Houses within 500 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,8.468269801883444,0.5423481283186504,100*(exp(b - se^2/2) - 1),reported,0.15071465227269995,0.0092690438052091,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.259999999999998,11375.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c4,2,4,10,Air Conditioning,air_conditioning,A_structural,binary,binary,0.0763,0.012,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7733,se,Houses within 100 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,7.920860567071841,1.2951435737852433,100*(exp(b - se^2/2) - 1),reported,0.14449158991705763,0.02272475857149006,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.358333333333333,1896.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c1,2,1,10,Deck,terrace_balcony,C_exterior,binary,binary,0.0214,0.002,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7417,se,All houses (full sample); boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,2.1628578907640916,0.20432612443336837,100*(exp(b - se^2/2) - 1),reported,0.03920716411853827,0.0036642209456577827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.7,74365.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c2,2,2,10,Deck,terrace_balcony,C_exterior,binary,binary,0.016,0.003,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7502,se,"Houses within 1,000 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment",pct_premium,1.6124112837298865,0.3048386056218285,100*(exp(b - se^2/2) - 1),reported,0.03557734786504881,0.006670752724696653,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.333333333333333,22444.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c3,2,3,10,Deck,terrace_balcony,C_exterior,binary,binary,0.0067,0.005,,,,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7462,se,Houses within 500 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,0.6709911258702128,0.5033612476056212,100*(exp(b - se^2/2) - 1),reported,0.012563042259106847,0.009375404670975258,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.34,11375.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c4,2,4,10,Deck,terrace_balcony,C_exterior,binary,binary,0.0208,0.009,,,**,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7733,se,Houses within 100 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,2.0976477265611804,0.9189160448852525,100*(exp(b - se^2/2) - 1),reported,0.053001821126033466,0.022933480294918325,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3111111111111113,1896.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c1,2,1,10,Swimming Pool,pool,C_exterior,binary,binary,-0.1137,0.005,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7417,se,All houses (full sample); boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,-10.748548307639306,0.44626283671239825,100*(exp(b - se^2/2) - 1),reported,-0.08310007785490389,0.0036543569857037774,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.74,74365.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c2,2,2,10,Swimming Pool,pool,C_exterior,binary,binary,-0.0552,0.008,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7502,se,"Houses within 1,000 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment",pct_premium,-5.373441113100275,0.7570366958818675,100*(exp(b - se^2/2) - 1),reported,-0.04600857884373564,0.006667909977352992,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.8999999999999995,22444.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c3,2,3,10,Swimming Pool,pool,C_exterior,binary,binary,-0.0477,0.013,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7462,se,Houses within 500 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,-4.66607904579045,1.2394457011416191,100*(exp(b - se^2/2) - 1),reported,-0.034382896846332736,0.009370600817658817,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.6692307692307695,11375.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c4,2,4,10,Swimming Pool,pool,C_exterior,binary,binary,0.0418,0.047,,,,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7733,se,Houses within 100 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,4.153490987483277,4.900623827344107,100*(exp(b - se^2/2) - 1),reported,0.020420608903668824,0.022960971733790306,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8893617021276595,1896.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c1,2,1,10,Fireplace,fireplace,B_interior,binary,binary,0.0741,0.002,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7417,se,All houses (full sample); boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,7.691233773415362,0.21538289831219662,100*(exp(b - se^2/2) - 1),reported,0.13462699404911257,0.0036336570593552657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.05,74365.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c2,2,2,10,Fireplace,fireplace,B_interior,binary,binary,0.0625,0.004,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7502,se,"Houses within 1,000 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment",pct_premium,6.448594299625188,0.4257977835671437,100*(exp(b - se^2/2) - 1),reported,0.10373386830897514,0.006638967571774409,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.625,22444.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c3,2,3,10,Fireplace,fireplace,B_interior,binary,binary,0.0499,0.005,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7462,se,Houses within 500 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,5.115283503000723,0.5255829872612834,100*(exp(b - se^2/2) - 1),reported,0.0931669238053422,0.009335363106747714,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.98,11375.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c4,2,4,10,Fireplace,fireplace,B_interior,binary,binary,0.0145,0.013,,,,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7733,se,Houses within 100 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,1.4519904397412242,1.318987325436818,100*(exp(b - se^2/2) - 1),reported,0.025607256189165702,0.02295822968683821,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1153846153846154,1896.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c1,2,1,10,View,view,E_environment,binary,binary,0.059,0.002,,,***,,,high,Mountain view mentioned in property description,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7417,se,All houses (full sample); boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,6.077311919179906,0.2121550481480318,100*(exp(b - se^2/2) - 1),reported,0.1075502270984841,0.0036457704101181053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.499999999999996,74365.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c2,2,2,10,View,view,E_environment,binary,binary,0.0577,0.004,,,***,,,high,Mountain view mentioned in property description,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7502,se,"Houses within 1,000 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment",pct_premium,5.938865375085034,0.4237588515575924,100*(exp(b - se^2/2) - 1),reported,0.09584330306284213,0.00664424977905318,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.425,22444.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c3,2,3,10,View,view,E_environment,binary,binary,0.0498,0.005,,,***,,,high,Mountain view mentioned in property description,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7462,se,Houses within 500 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,5.104772500209309,0.5255304315903846,100*(exp(b - se^2/2) - 1),reported,0.09298183235010433,0.009335525336355859,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.959999999999999,11375.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T2-c4,2,4,10,View,view,E_environment,binary,binary,0.029,0.012,,,**,,,high,Mountain view mentioned in property description,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7733,se,Houses within 100 ft of the secondary-water boundary; boundary-segment FE + month/year FE; SE clustered by boundary segment,pct_premium,2.9350478572533145,1.2353095133701568,100*(exp(b - se^2/2) - 1),reported,0.055415305455486924,0.02293047122296011,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4166666666666665,1896.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c1,3,1,11,House Size ('000 sq ft),living_area,A_structural,level,1000 sqft,0.1632,0.007,,,***,,,high,House size in thousands of square feet,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7343,se,All houses (full sample); neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),semi_elasticity,0.17566701800070267,0.007534737291696806,100*b/92.903 (X per 1000sqft->m2),reported,0.08518368078067474,0.003653711798190706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.314285714285717,74365.0,1000sqft,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c2,3,2,11,House Size ('000 sq ft),living_area,A_structural,level,1000 sqft,0.12,0.01,,,***,,,high,House size in thousands of square feet,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7431,se,"Houses within 1,000 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE')",semi_elasticity,0.12916692500051666,0.010763910416709722,100*b/92.903 (X per 1000sqft->m2),reported,0.07984401296867373,0.006653667747389478,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,22444.0,1000sqft,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c3,3,3,11,House Size ('000 sq ft),living_area,A_structural,level,1000 sqft,0.109,0.015,,,***,,,high,House size in thousands of square feet,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7419,se,Houses within 500 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),semi_elasticity,0.11732662354213597,0.016145865625064582,100*b/92.903 (X per 1000sqft->m2),reported,0.06797572352783131,0.009354457366215319,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.266666666666667,11375.0,1000sqft,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c4,3,4,11,House Size ('000 sq ft),living_area,A_structural,level,1000 sqft,0.1617,0.025,,,***,,,high,House size in thousands of square feet,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7741,se,Houses within 100 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),semi_elasticity,0.1740524314381962,0.026909776041774306,100*b/92.903 (X per 1000sqft->m2),reported,0.14693038302688433,0.022716509435201662,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.468,1896.0,1000sqft,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c1,3,1,11,Acreage,lot_size,A_structural,level,acres,0.0017,0.001,,,**,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7343,se,All houses (full sample); neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),semi_elasticity,4.2007914849418104e-05,2.4710538146716536e-05,100*b/4046.86 (X per acre->m2),reported,0.006233847754358952,0.0036669692672699717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7,74365.0,acre,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c2,3,2,11,Acreage,lot_size,A_structural,level,acres,0.0343,0.021,,,,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7431,se,"Houses within 1,000 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE')",semi_elasticity,0.000847571458432377,0.0005189213010810472,100*b/4046.86 (X per acre->m2),reported,0.010901816957120362,0.006674581810481856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.633333333333333,22444.0,acre,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c3,3,3,11,Acreage,lot_size,A_structural,level,acres,0.0975,0.027,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7419,se,Houses within 500 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),semi_elasticity,0.002409277469304862,0.0006671845299613464,100*b/4046.86 (X per acre->m2),reported,0.03383890936766155,0.009370774901813967,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.611111111111111,11375.0,acre,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c4,3,4,11,Acreage,lot_size,A_structural,level,acres,0.1895,0.033,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7741,se,Houses within 100 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),semi_elasticity,0.004682646978802783,0.0008154477588416456,100*b/4046.86 (X per acre->m2),reported,0.13074705811412263,0.022768616980295763,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.742424242424242,1896.0,acre,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c1,3,1,11,Bathrooms,bathrooms,A_structural,level,count,0.0246,0.001,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7343,se,All houses (full sample); neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),semi_elasticity,2.46,0.1,100*b/1 (per unit count),reported,0.08984437424982356,0.003652210335358681,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.6,74365.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c2,3,2,11,Bathrooms,bathrooms,A_structural,level,count,0.0206,0.002,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7431,se,"Houses within 1,000 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE')",semi_elasticity,2.06,0.2,100*b/1 (per unit count),reported,0.06859036041942462,0.006659258293148021,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.3,22444.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c3,3,3,11,Bathrooms,bathrooms,A_structural,level,count,0.0226,0.003,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7419,se,Houses within 500 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),semi_elasticity,2.26,0.3,100*b/1 (per unit count),reported,0.07045807996410608,0.009352842473111427,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.533333333333332,11375.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c4,3,4,11,Bathrooms,bathrooms,A_structural,level,count,0.0231,0.008,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7741,se,Houses within 100 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),semi_elasticity,2.31,0.8,100*b/1 (per unit count),reported,0.06616830585517718,0.022915430599195565,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8874999999999997,1896.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c1,3,1,11,Bedrooms,bedrooms,A_structural,level,count,0.0677,0.002,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7343,se,All houses (full sample); neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),semi_elasticity,6.77,0.2,100*b/1 (per unit count),reported,0.12318393485257591,0.0036391118124837795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.849999999999994,74365.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c2,3,2,11,Bedrooms,bedrooms,A_structural,level,count,0.0598,0.003,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7431,se,"Houses within 1,000 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE')",semi_elasticity,5.9799999999999995,0.3,100*b/1 (per unit count),reported,0.13189221478830498,0.006616666293727675,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.933333333333334,22444.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c3,3,3,11,Bedrooms,bedrooms,A_structural,level,count,0.0572,0.004,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7419,se,Houses within 500 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),semi_elasticity,5.72,0.4,100*b/1 (per unit count),reported,0.13288970014088444,0.009292986023838072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.3,11375.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c4,3,4,11,Bedrooms,bedrooms,A_structural,level,count,0.0471,0.008,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7741,se,Houses within 100 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),semi_elasticity,4.71,0.8,100*b/1 (per unit count),reported,0.13399164593466745,0.022758665976164324,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.8875,1896.0,count,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c1,3,1,11,Air Conditioning,air_conditioning,A_structural,binary,binary,0.0681,0.002,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7343,se,All houses (full sample); neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,7.047020941906745,0.21409447007232543,100*(exp(b - se^2/2) - 1),reported,0.12390061646283641,0.003638784624459219,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.05,74365.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c2,3,2,11,Air Conditioning,air_conditioning,A_structural,binary,binary,0.0629,0.004,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7431,se,"Houses within 1,000 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE')",pct_premium,6.491182254368133,0.4259681367489356,100*(exp(b - se^2/2) - 1),reported,0.10439055308071665,0.006638508939950185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.725,22444.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c3,3,3,11,Air Conditioning,air_conditioning,A_structural,binary,binary,0.0796,0.005,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7419,se,Houses within 500 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,8.284030391090402,0.5414269197496501,100*(exp(b - se^2/2) - 1),reported,0.1476325821207363,0.009273403399543738,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.92,11375.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c4,3,4,11,Air Conditioning,air_conditioning,A_structural,binary,binary,0.0771,0.012,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7741,se,Houses within 100 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,8.007231799411985,1.2961801032007558,100*(exp(b - se^2/2) - 1),reported,0.14597445567316694,0.022719759637846997,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.425,1896.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c1,3,1,11,Deck,terrace_balcony,C_exterior,binary,binary,0.0233,0.002,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7343,se,All houses (full sample); neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,2.3571518415596904,0.2047147131121362,100*(exp(b - se^2/2) - 1),reported,0.04268209057763694,0.0036636987620289217,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.65,74365.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c2,3,2,11,Deck,terrace_balcony,C_exterior,binary,binary,0.0174,0.003,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7431,se,"Houses within 1,000 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE')",pct_premium,1.7547682861771774,0.3052656785509942,100*(exp(b - se^2/2) - 1),reported,0.038685894035690144,0.006669981730291404,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.8,22444.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c3,3,3,11,Deck,terrace_balcony,C_exterior,binary,binary,0.0084,0.005,,,*,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7419,se,Houses within 500 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,0.8422773628341762,0.5042176894958977,100*(exp(b - se^2/2) - 1),reported,0.01574996911532522,0.00937498161626501,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.68,11375.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c4,3,4,11,Deck,terrace_balcony,C_exterior,binary,binary,0.0211,0.009,,,**,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7741,se,Houses within 100 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,2.128281615732752,0.9191917610540755,100*(exp(b - se^2/2) - 1),reported,0.05376407643433173,0.022932544450662822,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3444444444444446,1896.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c1,3,1,11,Swimming Pool,pool,C_exterior,binary,binary,-0.1057,0.005,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7343,se,All houses (full sample); neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,-10.03167301626573,0.44984725797425185,100*(exp(b - se^2/2) - 1),reported,-0.07728934766508967,0.003656071318121555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.14,74365.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c2,3,2,11,Swimming Pool,pool,C_exterior,binary,binary,-0.07,0.008,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7431,se,"Houses within 1,000 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE')",pct_premium,-6.763601621890825,0.7459150559247586,100*(exp(b - se^2/2) - 1),reported,-0.05830669649668273,0.006663622456763741,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.75,22444.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c3,3,3,11,Swimming Pool,pool,C_exterior,binary,binary,-0.0723,0.012,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7419,se,Houses within 500 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,-6.981519730472529,1.1163021340945987,100*(exp(b - se^2/2) - 1),reported,-0.05640134722678249,0.009361219456727384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.025,11375.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c4,3,4,11,Swimming Pool,pool,C_exterior,binary,binary,0.0417,0.042,,,,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7741,se,Houses within 100 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,4.166250571637797,4.378842960797328,100*(exp(b - se^2/2) - 1),reported,0.022795794255025488,0.022959792774845816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9928571428571428,1896.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c1,3,1,11,Fireplace,fireplace,B_interior,binary,binary,0.075,0.002,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7343,se,All houses (full sample); neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,7.788199511848548,0.2155768301769263,100*(exp(b - se^2/2) - 1),reported,0.13623197155371328,0.003632852574765688,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.5,74365.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c2,3,2,11,Fireplace,fireplace,B_interior,binary,binary,0.0642,0.004,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7431,se,"Houses within 1,000 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE')",pct_premium,6.629710815354017,0.42652225542581085,100*(exp(b - se^2/2) - 1),reported,0.10652383156845875,0.00663699885161737,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.049999999999997,22444.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c3,3,3,11,Fireplace,fireplace,B_interior,binary,binary,0.0493,0.006,,,***,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7419,se,Houses within 500 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,5.051655464172411,0.6303212784659353,100*(exp(b - se^2/2) - 1),reported,0.07681303941396385,0.009348442930705539,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.216666666666667,11375.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c4,3,4,11,Fireplace,fireplace,B_interior,binary,binary,0.0118,0.012,,,,,,high,,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7741,se,Houses within 100 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,1.1797042638690192,1.2142438735780814,100*(exp(b - se^2/2) - 1),reported,0.0225772415617691,0.02295990667298553,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9833333333333333,1896.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c1,3,1,11,View,view,E_environment,binary,binary,0.0615,0.002,,,***,,,high,Mountain view mentioned in property description,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7343,se,All houses (full sample); neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,6.342836966993337,0.21268609930575993,100*(exp(b - se^2/2) - 1),reported,0.11205137092783046,0.0036439470220432668,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.75,74365.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c2,3,2,11,View,view,E_environment,binary,binary,0.0555,0.004,,,***,,,high,Mountain view mentioned in property description,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7431,se,"Houses within 1,000 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE')",pct_premium,5.706056055411235,0.42282760682896914,100*(exp(b - se^2/2) - 1),reported,0.09222065507274665,0.0066465336989366955,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.875,22444.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c3,3,3,11,View,view,E_environment,binary,binary,0.0496,0.005,,,***,,,high,Mountain view mentioned in property description,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7419,se,Houses within 500 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,5.083753647664602,0.5254253360139745,100*(exp(b - se^2/2) - 1),reported,0.09261162053756967,0.009335848844513071,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.92,11375.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T3-c4,3,4,11,View,view,E_environment,binary,binary,0.0355,0.011,,,***,,,high,Mountain view mentioned in property description,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7741,se,Houses within 100 ft of the secondary-water boundary; neighbourhood (Neighborhood Scout) FE + month/year FE; SE clustered by neighbourhood (table footer still prints 'Boundary FE'),pct_premium,3.6074963696576257,1.1397514129408712,100*(exp(b - se^2/2) - 1),reported,0.07391403507958459,0.022902940447195225,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.227272727272727,1896.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T5-c1,5,1,13,Summer,transaction_timing,G_market,binary,binary,0.0199,0.004,,,***,,,high,Sale occurred in June-August,"Natural log of the real house price (sold price, $)",log,OLS,74375.0,0.7406,se,All houses (full sample); adds Summer dummy and Secondary*Summer interaction; full Table 2 controls included but not printed; boundary FE + month/year FE; clustered SE,pct_premium,2.009116423163304,0.408039729997436,100*(exp(b - se^2/2) - 1),reported,0.01824049138290121,0.0036664304287238603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.9750000000000005,74365.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T5-c2,5,2,13,Summer,transaction_timing,G_market,binary,binary,0.0257,0.006,,,***,,,high,Sale occurred in June-August,"Natural log of the real house price (sold price, $)",log,OLS,22454.0,0.7483,se,"Houses within 1,000 ft of the secondary-water boundary; adds Summer dummy and Secondary*Summer interaction; full Table 2 controls included but not printed; boundary FE + month/year FE; clustered SE",pct_premium,2.6014623940178394,0.6156198554217748,100*(exp(b - se^2/2) - 1),reported,0.028579479006553016,0.006672251908144674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.283333333333333,22444.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T5-c3,5,3,13,Summer,transaction_timing,G_market,binary,binary,0.0352,0.008,,,***,,,high,Sale occurred in June-August,"Natural log of the real house price (sold price, $)",log,OLS,11385.0,0.7441,se,Houses within 500 ft of the secondary-water boundary; adds Summer dummy and Secondary*Summer interaction; full Table 2 controls included but not printed; boundary FE + month/year FE; clustered SE,pct_premium,3.579370752618538,0.8286614827641267,100*(exp(b - se^2/2) - 1),reported,0.04121997349081335,0.00936817579336667,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.4,11375.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5,38bf59597966e99f31288b3b3bfbe1d0b22ac0b5:T5-c4,5,4,13,Summer,transaction_timing,G_market,binary,binary,0.0699,0.02,,,***,,,high,Sale occurred in June-August,"Natural log of the real house price (sold price, $)",log,OLS,1906.0,0.7688,se,Houses within 100 ft of the secondary-water boundary; adds Summer dummy and Secondary*Summer interaction; full Table 2 controls included but not printed; boundary FE + month/year FE; clustered SE,pct_premium,7.218647705788239,2.1448018715969064,100*(exp(b - se^2/2) - 1),reported,0.08000802031355601,0.022892137428771393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.495,1896.0,binary,,2024.0,United States,North America,High income,1999.0,2020.0,single_family,transaction,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m1,3,Model 1,7,LOT,living_area,A_structural,log,m2 (printed 'Lot size (m2)'; ln),0.976,,65.585,,**,,,medium,"Printed label 'Lot size (m2)' but mean ln = 4.52 (~92 m2) for a sample of apartments/houses, i.e. this is effectively the dwelling floor area; mapped to living_area, flag","ln sales (listing) price of property, RMB",log,OLS,688.0,0.917,t,Controlled variables only (no landscape variables); adjusted R2 = 0.916,elasticity,0.976,0.01488145155142182,b (log-log),|b/t|,0.929429289479521,0.014171369817481448,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),65.585,678.0,m2 '; ln),,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m2,3,Model 2,7,LOT,living_area,A_structural,log,m2 (printed 'Lot size (m2)'; ln),0.967,,64.224,,**,,,medium,"Printed label 'Lot size (m2)' but mean ln = 4.52 (~92 m2) for a sample of apartments/houses, i.e. this is effectively the dwelling floor area; mapped to living_area, flag","ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DPAR (log distance to Xiangshan Park); adjusted R2 = 0.917,elasticity,0.967,0.015056676631788737,b (log-log),|b/t|,0.926730845659194,0.014429665633706932,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),64.224,678.0,m2 '; ln),,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m3,3,Model 3,7,LOT,living_area,A_structural,log,m2 (printed 'Lot size (m2)'; ln),0.953,,59.367,,**,,,medium,"Printed label 'Lot size (m2)' but mean ln = 4.52 (~92 m2) for a sample of apartments/houses, i.e. this is effectively the dwelling floor area; mapped to living_area, flag","ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DSEA (log distance to seaside); adjusted R2 = 0.917,elasticity,0.953,0.01605268920444018,b (log-log),|b/t|,0.9157866470331151,0.015425853538718727,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),59.367,678.0,m2 '; ln),,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m4,3,Model 4,7,LOT,living_area,A_structural,log,m2 (printed 'Lot size (m2)'; ln),0.961,,63.918,,**,,,medium,"Printed label 'Lot size (m2)' but mean ln = 4.52 (~92 m2) for a sample of apartments/houses, i.e. this is effectively the dwelling floor area; mapped to living_area, flag","ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + SEAVIEW; adjusted R2 = 0.918,elasticity,0.961,0.015034888450827623,b (log-log),|b/t|,0.926103666852024,0.014488933740918431,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),63.918,678.0,m2 '; ln),,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m5,3,Model 5,7,LOT,living_area,A_structural,log,m2 (printed 'Lot size (m2)'; ln),0.949,,61.395,,**,,,medium,"Printed label 'Lot size (m2)' but mean ln = 4.52 (~92 m2) for a sample of apartments/houses, i.e. this is effectively the dwelling floor area; mapped to living_area, flag","ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + all three landscape variables; adjusted R2 = 0.918,elasticity,0.949,0.01545728479517876,b (log-log),|b/t|,0.9206245315806453,0.014995105978999024,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),61.395,678.0,m2 '; ln),,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m1,3,Model 1,7,PUBS,green_space,E_environment,binary,binary (public open space within 200 m),0.075,,5.99,,**,,,high,Existence of public space reachable within 200 m,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.917,t,Controlled variables only (no landscape variables); adjusted R2 = 0.916,pct_premium,7.7799663094412,1.3496045294882697,100*(exp(b - se^2/2) - 1),|b/t|,0.2241889404728295,0.037427202082275374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.99,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m2,3,Model 2,7,PUBS,green_space,E_environment,binary,binary (public open space within 200 m),0.087,,6.66,,**,,,high,Existence of public space reachable within 200 m,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DPAR (log distance to Xiangshan Park); adjusted R2 = 0.917,pct_premium,9.08036064115494,1.425045212244597,100*(exp(b - se^2/2) - 1),|b/t|,0.24779851943149875,0.037206984899624436,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.66,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m3,3,Model 3,7,PUBS,green_space,E_environment,binary,binary (public open space within 200 m),0.072,,5.746,,**,,,high,Existence of public space reachable within 200 m,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DSEA (log distance to seaside); adjusted R2 = 0.917,pct_premium,7.457098030735443,1.346592147103978,100*(exp(b - se^2/2) - 1),|b/t|,0.21548933314361052,0.037502494455901585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.746,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m4,3,Model 4,7,PUBS,green_space,E_environment,binary,binary (public open space within 200 m),0.086,,6.824,,**,,,high,Existence of public space reachable within 200 m,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + SEAVIEW; adjusted R2 = 0.918,pct_premium,8.971978749590793,1.3734370491535912,100*(exp(b - se^2/2) - 1),|b/t|,0.2535127171905987,0.03715016371491774,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.824,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m5,3,Model 5,7,PUBS,green_space,E_environment,binary,binary (public open space within 200 m),0.081,,5.933,,**,,,high,Existence of public space reachable within 200 m,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + all three landscape variables; adjusted R2 = 0.918,pct_premium,8.426984362481038,1.4804322033019992,100*(exp(b - se^2/2) - 1),|b/t|,0.22216136349888452,0.03744503008577187,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.933,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m1,3,Model 1,7,DEXE,green_space,E_environment,log,m (ln distance to Huafa Exercise Park),-0.033,,-3.145,,**,,,high,Log distance to Huafa Exercise Park (small park),"ln sales (listing) price of property, RMB",log,OLS,688.0,0.917,t,Controlled variables only (no landscape variables); adjusted R2 = 0.916,elasticity,-0.033,0.010492845786963434,b (log-log),|b/t|,-0.11991149792471875,0.03812766229720787,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.145,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m2,3,Model 2,7,DEXE,green_space,E_environment,log,m (ln distance to Huafa Exercise Park),-0.033,,-3.14,,**,,,high,Log distance to Huafa Exercise Park (small park),"ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DPAR (log distance to Xiangshan Park); adjusted R2 = 0.917,elasticity,-0.033,0.010509554140127388,b (log-log),|b/t|,-0.1197235943174113,0.03812853322210551,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.14,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m3,3,Model 3,7,DEXE,green_space,E_environment,log,m (ln distance to Huafa Exercise Park),-0.053,,-4.474,,**,,,high,Log distance to Huafa Exercise Park (small park),"ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DSEA (log distance to seaside); adjusted R2 = 0.917,elasticity,-0.053,0.011846222619579794,b (log-log),|b/t|,-0.16934137454491416,0.03785010606725842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.474,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m4,3,Model 4,7,DEXE,green_space,E_environment,log,m (ln distance to Huafa Exercise Park),-0.028,,-2.639,,**,,,high,Log distance to Huafa Exercise Park (small park),"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + SEAVIEW; adjusted R2 = 0.918,elasticity,-0.028,0.010610079575596818,b (log-log),|b/t|,-0.10083363304204487,0.038209031088308025,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.639,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m5,3,Model 5,7,DEXE,green_space,E_environment,log,m (ln distance to Huafa Exercise Park),-0.041,,-3.237,,**,,,high,Log distance to Huafa Exercise Park (small park),"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + all three landscape variables; adjusted R2 = 0.918,elasticity,-0.041,0.012666048810627124,b (log-log),|b/t|,-0.12336660478593083,0.03811140092243769,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.237,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m1,3,Model 1,7,DCEM,green_space,E_environment,log,m (ln distance to Martyrs' Park),-0.069,,-4.95,,**,,,high,Log distance to Martyrs' Park (Martyrs' Cemetery park),"ln sales (listing) price of property, RMB",log,OLS,688.0,0.917,t,Controlled variables only (no landscape variables); adjusted R2 = 0.916,elasticity,-0.069,0.01393939393939394,b (log-log),|b/t|,-0.18675888047049533,0.03772906676171622,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.95,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m2,3,Model 2,7,DCEM,green_space,E_environment,log,m (ln distance to Martyrs' Park),-0.086,,-5.751,,**,,,high,Log distance to Martyrs' Park (Martyrs' Cemetery park),"ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DPAR (log distance to Xiangshan Park); adjusted R2 = 0.917,elasticity,-0.086,0.01495392105720744,b (log-log),|b/t|,-0.21566812751198106,0.03750097852755713,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.751,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m4,3,Model 4,7,DCEM,green_space,E_environment,log,m (ln distance to Martyrs' Park),-0.015,,-0.757,,,,,high,Log distance to Martyrs' Park (Martyrs' Cemetery park),"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + SEAVIEW; adjusted R2 = 0.918,elasticity,-0.015,0.019815059445178335,b (log-log),|b/t|,-0.02906013156392789,0.03838854896159563,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.757,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m5,3,Model 5,7,DCEM,green_space,E_environment,log,m (ln distance to Martyrs' Park),-0.039,,-2.503,,*,,,high,Log distance to Martyrs' Park (Martyrs' Cemetery park),"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + all three landscape variables; adjusted R2 = 0.918,elasticity,-0.039,0.01558130243707551,b (log-log),|b/t|,-0.09568606246792946,0.03822855072630022,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.503,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m1,3,Model 1,7,PARKING,parking,A_structural,binary,binary (parking space exists),-0.06,,-4.013,,**,,,high,Existence of parking space,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.917,t,Controlled variables only (no landscape variables); adjusted R2 = 0.916,pct_premium,-5.834072372068344,1.408070571020556,100*(exp(b - se^2/2) - 1),|b/t|,-0.15231996571133083,0.03795663237262169,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.013,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m2,3,Model 2,7,PARKING,parking,A_structural,binary,binary (parking space exists),-0.058,,-3.875,,**,,,high,Existence of parking space,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DPAR (log distance to Xiangshan Park); adjusted R2 = 0.917,pct_premium,-5.645575114833656,1.4124308890666921,100*(exp(b - se^2/2) - 1),|b/t|,-0.14719741851382875,0.03798643058421387,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.875,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m3,3,Model 3,7,PARKING,parking,A_structural,binary,binary (parking space exists),-0.051,,-3.339,,**,,,high,Existence of parking space,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DSEA (log distance to seaside); adjusted R2 = 0.917,pct_premium,-4.983217116560034,1.4514588858087385,100*(exp(b - se^2/2) - 1),|b/t|,-0.12719202415071965,0.038092849401233794,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.339,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m4,3,Model 4,7,PARKING,parking,A_structural,binary,binary (parking space exists),-0.068,,-4.556,,**,,,high,Existence of parking space,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + SEAVIEW; adjusted R2 = 0.918,pct_premium,-6.584358171850524,1.3944186172794235,100*(exp(b - se^2/2) - 1),|b/t|,-0.17235369059323366,0.03783004622327341,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.556,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m5,3,Model 5,7,PARKING,parking,A_structural,binary,binary (parking space exists),-0.059,,-3.928,,**,,,high,Existence of parking space,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + all three landscape variables; adjusted R2 = 0.918,pct_premium,-5.739956754809872,1.4159801267889225,100*(exp(b - se^2/2) - 1),|b/t|,-0.149166198301158,0.03797510140049847,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.928,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m1,3,Model 1,7,POOL,pool,C_exterior,binary,binary (swimming pool exists),0.07,,3.476,,**,,,high,Existence of swimming pool,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.917,t,Controlled variables only (no landscape variables); adjusted R2 = 0.916,pct_premium,7.229072939158887,2.1598266020654537,100*(exp(b - se^2/2) - 1),|b/t|,0.13232114089618924,0.03806707160419714,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.476,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m2,3,Model 2,7,POOL,pool,C_exterior,binary,binary (swimming pool exists),0.092,,4.321,,**,,,high,Existence of swimming pool,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DPAR (log distance to Xiangshan Park); adjusted R2 = 0.917,pct_premium,9.611634690829085,2.3343106602970414,100*(exp(b - se^2/2) - 1),|b/t|,0.1637081825763987,0.03788664257727348,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.321,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m3,3,Model 3,7,POOL,pool,C_exterior,binary,binary (swimming pool exists),0.083,,4.117,,**,,,high,Existence of swimming pool,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DSEA (log distance to seaside); adjusted R2 = 0.917,pct_premium,8.632102496913241,2.1905020672699482,100*(exp(b - se^2/2) - 1),|b/t|,0.15617236408217272,0.03793353511833197,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.117,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m4,3,Model 4,7,POOL,pool,C_exterior,binary,binary (swimming pool exists),0.081,,4.079,,**,,,high,Existence of swimming pool,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + SEAVIEW; adjusted R2 = 0.918,pct_premium,8.415711627222455,2.153322937531444,100*(exp(b - se^2/2) - 1),|b/t|,0.15476557343108813,0.03794203810519444,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.079,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m5,3,Model 5,7,POOL,pool,C_exterior,binary,binary (swimming pool exists),0.086,,4.12,,**,,,high,Existence of swimming pool,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + all three landscape variables; adjusted R2 = 0.918,pct_premium,8.956893170555391,2.2748384522874043,100*(exp(b - se^2/2) - 1),|b/t|,0.1562833861522708,0.03793286071657058,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.12,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m1,3,Model 1,7,LIFT,accessibility,B_interior,binary,binary (lift exists),0.025,,1.424,,,,,high,Existence of lift/elevator,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.917,t,Controlled variables only (no landscape variables); adjusted R2 = 0.916,pct_premium,2.5157121668929694,1.8000616582240678,100*(exp(b - se^2/2) - 1),|b/t|,0.054606791953899794,0.03834746625976109,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.424,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m2,3,Model 2,7,LIFT,accessibility,B_interior,binary,binary (lift exists),0.039,,2.183,,*,,,high,Existence of lift/elevator,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DPAR (log distance to Xiangshan Park); adjusted R2 = 0.917,pct_premium,3.960456523954714,1.857583548435921,100*(exp(b - se^2/2) - 1),|b/t|,0.08354451749207704,0.03827050732573387,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.183,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m3,3,Model 3,7,LIFT,accessibility,B_interior,binary,binary (lift exists),0.026,,1.541,,,,,high,Existence of lift/elevator,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DSEA (log distance to seaside); adjusted R2 = 0.917,pct_premium,2.6194874725627093,1.7316589656268326,100*(exp(b - se^2/2) - 1),|b/t|,0.05907837849540077,0.03833768883543204,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.541,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m4,3,Model 4,7,LIFT,accessibility,B_interior,binary,binary (lift exists),0.034,,1.966,,*,,,high,Existence of lift/elevator,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + SEAVIEW; adjusted R2 = 0.918,pct_premium,3.4429905289713014,1.7892104083802651,100*(exp(b - se^2/2) - 1),|b/t|,0.07528947424689622,0.03829576513066949,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.966,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m5,3,Model 5,7,LIFT,accessibility,B_interior,binary,binary (lift exists),0.033,,1.821,,,,,high,Existence of lift/elevator,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + all three landscape variables; adjusted R2 = 0.918,pct_premium,3.3380842284194356,1.872991092529549,100*(exp(b - se^2/2) - 1),|b/t|,0.06976468517116435,0.03831119449267675,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.821,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m2,3,Model 2,7,DPAR,green_space,E_environment,log,m (ln distance to Xiangshan Park),0.056,,3.027,,**,,,high,"Log distance to Xiangshan Park (1,400-acre main park)","ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DPAR (log distance to Xiangshan Park); adjusted R2 = 0.917,elasticity,0.056,0.01850016518004625,b (log-log),|b/t|,0.11547357806352808,0.03814786193046847,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.027,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m5,3,Model 5,7,DPAR,green_space,E_environment,log,m (ln distance to Xiangshan Park),-0.007,,0.408,,,,,high,"Log distance to Xiangshan Park (1,400-acre main park); printed t '(0.408)' without minus sign despite negative coefficient (likely sign typo)","ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + all three landscape variables; adjusted R2 = 0.918,elasticity,-0.007,0.01715686274509804,b (log-log),|b/t|,0.01566722239508963,0.03840005488992556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.408,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m3,3,Model 3,7,DSEA,water_proximity,E_environment,log,m (ln distance to seaside),-0.055,,-3.656,,**,,,high,Log distance to seaside,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.919,t,Controls + DSEA (log distance to seaside); adjusted R2 = 0.917,elasticity,-0.055,0.015043763676148797,b (log-log),|b/t|,-0.13904394221717414,0.038031712860277386,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.656,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m5,3,Model 5,7,DSEA,water_proximity,E_environment,log,m (ln distance to seaside),-0.04,,-3.085,,**,,,high,Log distance to seaside,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + all three landscape variables; adjusted R2 = 0.918,elasticity,-0.04,0.012965964343598056,b (log-log),|b/t|,-0.11765580961572299,0.03813802580736564,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.085,678.0,m,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m4,3,Model 4,7,SEAVIEW,view,E_environment,binary,binary (sea view),0.089,,4.5,,**,,,high,Existence of sea view from property,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + SEAVIEW; adjusted R2 = 0.918,pct_premium,9.286689224636667,2.161870631400964,100*(exp(b - se^2/2) - 1),|b/t|,0.17029701733693423,0.03784378163042982,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb,3b4b454985f862f1a1d6165d8c81255275be3ddb:T3-m5,3,Model 5,7,SEAVIEW,view,E_environment,binary,binary (sea view),0.072,,3.265,,**,,,high,Existence of sea view from property,"ln sales (listing) price of property, RMB",log,OLS,688.0,0.92,t,Controls + all three landscape variables; adjusted R2 = 0.918,pct_premium,7.43940767795217,2.3698372058987616,100*(exp(b - se^2/2) - 1),|b/t|,0.12441727511385159,0.03810636297514597,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.265,678.0,binary,,2022.0,China,Asia,Upper middle income,2015.0,2015.0,mixed,listing,journal,False,False,OLS,,2015.0,ols,journal,True,True,False
3b820e938ca4b455736f08f285e1b5bb43f7674a,3b820e938ca4b455736f08f285e1b5bb43f7674a,3b820e938ca4b455736f08f285e1b5bb43f7674a:T9-c1,9,1,14,Direction of the house (East=1 Non-East=0),sunlight,E_environment,binary,binary,0.456,0.16,0.285,0.036,*,,,medium,"East-facing aspect dummy; printed t = .285 is inconsistent with B/SE = 2.85 and with p = .036 (t likely misprinted, should read 2.85)","Log_ Residential Real Estate Price (sales price, birr)",log,OLS,103.0,0.88,se,"Full survey sample (103 valid of 134 sampled owners); SE, t and p printed in separate columns",pct_premium,55.76838399581712,25.24400551626365,100*(exp(b - se^2/2) - 1),reported,0.029540226089115846,0.10364991610216087,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.285,93.0,binary,,2024.0,Ethiopia,Africa,Low income,2024.0,2024.0,single_family,transaction,journal,False,False,OLS,,2024.0,ols,journal,True,True,True
3b820e938ca4b455736f08f285e1b5bb43f7674a,3b820e938ca4b455736f08f285e1b5bb43f7674a,3b820e938ca4b455736f08f285e1b5bb43f7674a:T9-c1,9,1,14,Log_ Floor Area in square meter,living_area,A_structural,log,m2,0.601,0.175,3.441,0.001,*,,,high,Log of floor area (m2); elasticity,"Log_ Residential Real Estate Price (sales price, birr)",log,OLS,103.0,0.88,se,"Full survey sample (103 valid of 134 sampled owners); SE, t and p printed in separate columns",elasticity,0.601,0.175,b (log-log),reported,0.33606259007601225,0.09766422263179665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.441,93.0,m2,,2024.0,Ethiopia,Africa,Low income,2024.0,2024.0,single_family,transaction,journal,False,False,OLS,,2024.0,ols,journal,True,True,False
3b820e938ca4b455736f08f285e1b5bb43f7674a,3b820e938ca4b455736f08f285e1b5bb43f7674a,3b820e938ca4b455736f08f285e1b5bb43f7674a:T9-c1,9,1,14,Log_ Gross plot size in square meter,lot_size,A_structural,log,m2,0.335,0.11,3.052,0.003,*,,,high,Log of gross plot area (m2); elasticity,"Log_ Residential Real Estate Price (sales price, birr)",log,OLS,103.0,0.88,se,"Full survey sample (103 valid of 134 sampled owners); SE, t and p printed in separate columns",elasticity,0.335,0.11,b (log-log),reported,0.30172792298363493,0.09886236008638102,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.052,93.0,m2,,2024.0,Ethiopia,Africa,Low income,2024.0,2024.0,single_family,transaction,journal,False,False,OLS,,2024.0,ols,journal,True,True,False
3b820e938ca4b455736f08f285e1b5bb43f7674a,3b820e938ca4b455736f08f285e1b5bb43f7674a,3b820e938ca4b455736f08f285e1b5bb43f7674a:T9-c1,9,1,14,Log_ Age of the House in years,age,A_structural,log,years,-0.187,0.054,-3.434,0.001,*,,,high,Log of house age in years (range 1-15),"Log_ Residential Real Estate Price (sales price, birr)",log,OLS,103.0,0.88,se,"Full survey sample (103 valid of 134 sampled owners); SE, t and p printed in separate columns",elasticity,-0.187,0.054,b (log-log),reported,-0.3354559416439194,0.0976866457903085,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.434,93.0,years,,2024.0,Ethiopia,Africa,Low income,2024.0,2024.0,single_family,transaction,journal,False,False,OLS,,2024.0,ols,journal,True,True,False
3b820e938ca4b455736f08f285e1b5bb43f7674a,3b820e938ca4b455736f08f285e1b5bb43f7674a,3b820e938ca4b455736f08f285e1b5bb43f7674a:T9-c1,9,1,14,Log_ Number of rooms,bedrooms,A_structural,log,count,0.148,0.066,2.24,0.028,*,,,high,"Log of number of rooms (all rooms, 3-5)","Log_ Residential Real Estate Price (sales price, birr)",log,OLS,103.0,0.88,se,"Full survey sample (103 valid of 134 sampled owners); SE, t and p printed in separate columns",elasticity,0.148,0.066,b (log-log),reported,0.2262538542191667,0.10100618491927084,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.24,93.0,count,,2024.0,Ethiopia,Africa,Low income,2024.0,2024.0,single_family,transaction,journal,False,False,OLS,,2024.0,ols,journal,True,True,False
3b820e938ca4b455736f08f285e1b5bb43f7674a,3b820e938ca4b455736f08f285e1b5bb43f7674a,3b820e938ca4b455736f08f285e1b5bb43f7674a:T9-c1,9,1,14,Log_ Distance of the property from the main road in meter,highway_distance,D_location,log,m,-0.097,0.031,-3.115,0.002,*,,,high,Log of distance from the property to the main road in metres (234-817 m),"Log_ Residential Real Estate Price (sales price, birr)",log,OLS,103.0,0.88,se,"Full survey sample (103 valid of 134 sampled owners); SE, t and p printed in separate columns",elasticity,-0.097,0.031,b (log-log),reported,-0.30737320843726085,0.09867518729928117,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.115,93.0,m,,2024.0,Ethiopia,Africa,Low income,2024.0,2024.0,single_family,transaction,journal,False,False,OLS,,2024.0,ols,journal,True,True,True
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c1,4,1,8,M2,living_area,A_structural,level,m2,0.013,0.001,,,**,,,high,"Area of apartment, m2. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,OLS,500.0,0.786,se,Base OLS semi-log,semi_elasticity,1.3,0.1,100*b/1 (X per m2->m2),reported,0.5064081016355528,0.03895446935658099,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,490.0,m2,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,ols,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c2,4,2,8,M2,living_area,A_structural,level,m2,0.011,0.001,,,**,,,high,"Area of apartment, m2. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.854,se,"Spatial error model, 5 km weight matrix, ML",semi_elasticity,1.0999999999999999,0.1,100*b/1 (X per m2->m2),reported,0.44501236673450423,0.04045566970313674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.0,490.0,m2,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c3,4,3,8,M2,living_area,A_structural,level,m2,0.011,0.001,,,**,,,high,"Area of apartment, m2. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.737,se,"Spatial error model, 5 km, GM 2-step",semi_elasticity,1.0999999999999999,0.1,100*b/1 (X per m2->m2),reported,0.44501236673450423,0.04045566970313674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.0,490.0,m2,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c4,4,4,8,M2,living_area,A_structural,level,m2,0.011,0.001,,,**,,,high,"Area of apartment, m2. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.734,se,"Spatial error model, 5 km, GM iterated",semi_elasticity,1.0999999999999999,0.1,100*b/1 (X per m2->m2),reported,0.44501236673450423,0.04045566970313674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.0,490.0,m2,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c5,4,5,8,M2,living_area,A_structural,level,m2,0.011,0.001,,,**,,,high,"Area of apartment, m2. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,OLS,500.0,0.786,se,OLS with White heteroskedasticity-robust variance,semi_elasticity,1.0999999999999999,0.1,100*b/1 (X per m2->m2),reported,0.44501236673450423,0.04045566970313674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.0,490.0,m2,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,ols,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c1,4,1,8,HEAT_D,heating,A_structural,binary,binary,-0.148,0.029,,,**,,,high,"Heat type dummy: 1 = individual heating, 0 = central heating. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,OLS,500.0,0.786,se,Base OLS semi-log,pct_premium,-13.793146110483123,2.501050233331932,100*(exp(b - se^2/2) - 1),reported,-0.22465694699957137,0.04402061799315926,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.1034482758620685,490.0,binary,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,ols,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c2,4,2,8,HEAT_D,heating,A_structural,binary,binary,-0.129,0.024,,,**,,,high,"Heat type dummy: 1 = individual heating, 0 = central heating. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.854,se,"Spatial error model, 5 km weight matrix, ML",pct_premium,-12.127914250718486,2.1095375173093998,100*(exp(b - se^2/2) - 1),reported,-0.23596117845519124,0.04389975413119837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.375,490.0,binary,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c3,4,3,8,HEAT_D,heating,A_structural,binary,binary,-0.131,0.024,,,**,,,high,"Heat type dummy: 1 = individual heating, 0 = central heating. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.737,se,"Spatial error model, 5 km, GM 2-step",pct_premium,-12.303482795149778,2.1053226585385048,100*(exp(b - se^2/2) - 1),reported,-0.23941131516645855,0.04386161499232829,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.458333333333333,490.0,binary,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c4,4,4,8,HEAT_D,heating,A_structural,binary,binary,-0.123,0.023,,,**,,,high,"Heat type dummy: 1 = individual heating, 0 = central heating. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.734,se,"Spatial error model, 5 km, GM iterated",pct_premium,-11.597019424900001,2.033806423889888,100*(exp(b - se^2/2) - 1),reported,-0.23483419475688816,0.0439120851984425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.3478260869565215,490.0,binary,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c5,4,5,8,HEAT_D,heating,A_structural,binary,binary,-0.163,0.034,,,*,,,high,"Heat type dummy: 1 = individual heating, 0 = central heating. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,OLS,500.0,0.786,se,OLS with White heteroskedasticity-robust variance,pct_premium,-15.089973340224084,2.888610040609607,100*(exp(b - se^2/2) - 1),reported,-0.21166885575562677,0.04415178586313687,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.794117647058823,490.0,binary,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,ols,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c1,4,1,8,BATH,bathrooms,A_structural,level,count,-0.026,0.034,,,,,,high,Number of bathrooms. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,OLS,500.0,0.786,se,Base OLS semi-log,semi_elasticity,-2.6,3.4000000000000004,100*b/1 (per unit count),reported,-0.03452529498447397,0.04514846267200443,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7647058823529411,490.0,count,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,ols,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c2,4,2,8,BATH,bathrooms,A_structural,level,count,0.001,0.029,,,,,,high,Number of bathrooms. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.854,se,"Spatial error model, 5 km weight matrix, ML",semi_elasticity,0.1,2.9000000000000004,100*b/1 (per unit count),reported,0.0015577703563043883,0.04517534033282726,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.034482758620689655,490.0,count,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c3,4,3,8,BATH,bathrooms,A_structural,level,count,0.004,0.029,,,,,,high,Number of bathrooms. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.737,se,"Spatial error model, 5 km, GM 2-step",semi_elasticity,0.4,2.9000000000000004,100*b/1 (per unit count),reported,0.006230968023481229,0.04517451817023891,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.13793103448275862,490.0,count,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c4,4,4,8,BATH,bathrooms,A_structural,level,count,0.005,0.028,,,,,,high,Number of bathrooms. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.734,se,"Spatial error model, 5 km, GM iterated",semi_elasticity,0.5,2.8000000000000003,100*b/1 (per unit count),reported,0.008066772370759135,0.04517392527625116,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.17857142857142858,490.0,count,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c5,4,5,8,BATH,bathrooms,A_structural,level,count,-0.034,0.035,,,,,,high,Number of bathrooms. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,OLS,500.0,0.786,se,OLS with White heteroskedasticity-robust variance,semi_elasticity,-3.4000000000000004,3.5000000000000004,100*b/1 (per unit count),reported,-0.04384247255167036,0.0451319570384842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9714285714285714,490.0,count,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,ols,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c1,4,1,8,YEARS,age,A_structural,level,years,-0.031,0.006,,,**,,,high,Apartment age in years. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,OLS,500.0,0.786,se,Base OLS semi-log,semi_elasticity,-3.1,0.6,100*b/1 (per year),reported,-0.22729691823301026,0.0439929519160665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.166666666666667,490.0,years,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,ols,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c2,4,2,8,YEARS,age,A_structural,level,years,-0.029,0.005,,,**,,,high,Apartment age in years. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.854,se,"Spatial error model, 5 km weight matrix, ML",semi_elasticity,-2.9000000000000004,0.5,100*b/1 (per year),reported,-0.2534612582355012,0.04370021693715538,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.8,490.0,years,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c3,4,3,8,YEARS,age,A_structural,level,years,-0.031,0.005,,,**,,,high,Apartment age in years. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.737,se,"Spatial error model, 5 km, GM 2-step",semi_elasticity,-3.1,0.5,100*b/1 (per year),reported,-0.2697080117954873,0.043501292225078605,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.2,490.0,years,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c4,4,4,8,YEARS,age,A_structural,level,years,-0.03,0.005,,,**,,,high,Apartment age in years. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.734,se,"Spatial error model, 5 km, GM iterated",semi_elasticity,-3.0,0.5,100*b/1 (per year),reported,-0.2616124321181684,0.04360207201969473,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,490.0,years,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c5,4,5,8,YEARS,age,A_structural,level,years,-0.033,0.006,,,**,,,high,Apartment age in years. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,OLS,500.0,0.786,se,OLS with White heteroskedasticity-robust variance,semi_elasticity,-3.3000000000000003,0.6,100*b/1 (per year),reported,-0.24113299761177795,0.043842363202141445,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.5,490.0,years,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,ols,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c1,4,1,8,PM10,air_pollution,E_environment,level,ug/m3,-0.014,0.003,,,**,,,high,"PM10 concentration, ug/m3 (printed μm/m3). Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,OLS,500.0,0.786,se,Base OLS semi-log,semi_elasticity,-1.4000000000000001,0.3,100*b/1 (per ug/m3),reported,-0.20628424925175867,0.04420376769680543,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.666666666666667,490.0,ug/m3,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,ols,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c2,4,2,8,PM10,air_pollution,E_environment,level,ug/m3,-0.012,0.003,,,**,,,high,"PM10 concentration, ug/m3 (printed μm/m3). Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.854,se,"Spatial error model, 5 km weight matrix, ML",semi_elasticity,-1.2,0.3,100*b/1 (per ug/m3),reported,-0.17782168978975482,0.044455422447438706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,490.0,ug/m3,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c3,4,3,8,PM10,air_pollution,E_environment,level,ug/m3,-0.012,0.003,,,**,,,high,"PM10 concentration, ug/m3 (printed μm/m3). Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.737,se,"Spatial error model, 5 km, GM 2-step",semi_elasticity,-1.2,0.3,100*b/1 (per ug/m3),reported,-0.17782168978975482,0.044455422447438706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,490.0,ug/m3,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c4,4,4,8,PM10,air_pollution,E_environment,level,ug/m3,-0.01,0.004,,,**,,,high,"PM10 concentration, ug/m3 (printed μm/m3). Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.734,se,"Spatial error model, 5 km, GM iterated",semi_elasticity,-1.0,0.4,100*b/1 (per ug/m3),reported,-0.1122250348108084,0.04489001392432335,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5,490.0,ug/m3,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T4-c5,4,5,8,PM10,air_pollution,E_environment,level,ug/m3,-0.013,0.003,,,**,,,high,"PM10 concentration, ug/m3 (printed μm/m3). Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,OLS,500.0,0.786,se,OLS with White heteroskedasticity-robust variance,semi_elasticity,-1.3,0.3,100*b/1 (per ug/m3),reported,-0.19211356472533145,0.04433389955199957,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.333333333333333,490.0,ug/m3,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,ols,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c1,5,1,9,M2,living_area,A_structural,level,m2,0.01,0.001,,,**,,,high,"Area of apartment, m2. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.893,se,"Spatial error model, 1.7 km weight matrix, ML",semi_elasticity,1.0,0.1,100*b/1 (X per m2->m2),reported,0.41169348479630913,0.04116934847963091,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.0,490.0,m2,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c2,5,2,9,M2,living_area,A_structural,level,m2,0.011,0.001,,,**,,,high,"Area of apartment, m2. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.765,se,"Spatial error model, 1.7 km, GM 2-step",semi_elasticity,1.0999999999999999,0.1,100*b/1 (X per m2->m2),reported,0.44501236673450423,0.04045566970313674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.0,490.0,m2,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c3,5,3,9,M2,living_area,A_structural,level,m2,0.011,0.001,,,**,,,high,"Area of apartment, m2. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.822,se,"Spatial error model, 10 km, ML",semi_elasticity,1.0999999999999999,0.1,100*b/1 (X per m2->m2),reported,0.44501236673450423,0.04045566970313674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.0,490.0,m2,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c4,5,4,9,M2,living_area,A_structural,level,m2,0.011,0.001,,,**,,,high,"Area of apartment, m2. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.768,se,"Spatial error model, 10 km, GM 2-step",semi_elasticity,1.0999999999999999,0.1,100*b/1 (X per m2->m2),reported,0.44501236673450423,0.04045566970313674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.0,490.0,m2,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c5,5,5,9,M2,living_area,A_structural,level,m2,0.011,0.001,,,**,,,high,"Area of apartment, m2. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_lag,500.0,0.79,se,"Spatial lag model, 20 km, ML",semi_elasticity,1.0999999999999999,0.1,100*b/1 (X per m2->m2),reported,0.44501236673450423,0.04045566970313674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.0,490.0,m2,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c6,5,6,9,M2,living_area,A_structural,level,m2,0.011,0.001,,,**,,,high,"Area of apartment, m2. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_lag,500.0,0.806,se,"Spatial lag model, 20 km, IV (2SLS)",semi_elasticity,1.0999999999999999,0.1,100*b/1 (X per m2->m2),reported,0.44501236673450423,0.04045566970313674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.0,490.0,m2,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c1,5,1,9,HEAT_D,heating,A_structural,binary,binary,-0.039,0.022,,,**,,,high,"Heat type dummy: 1 = individual heating, 0 = central heating. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.893,se,"Spatial error model, 1.7 km weight matrix, ML",pct_premium,-3.8482006365534005,2.1158515601220067,100*(exp(b - se^2/2) - 1),reported,-0.07982807977514488,0.045031224488543256,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.772727272727273,490.0,binary,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c2,5,2,9,HEAT_D,heating,A_structural,binary,binary,-0.063,0.023,,,**,,,high,"Heat type dummy: 1 = individual heating, 0 = central heating. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.765,se,"Spatial error model, 1.7 km, GM 2-step",pct_premium,-6.130484401819302,2.1595699894850062,100*(exp(b - se^2/2) - 1),reported,-0.12280468437548113,0.04483345620057247,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.739130434782609,490.0,binary,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c3,5,3,9,HEAT_D,heating,A_structural,binary,binary,-0.171,0.026,,,**,,,high,"Heat type dummy: 1 = individual heating, 0 = central heating. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.822,se,"Spatial error model, 10 km, ML",pct_premium,-15.74632520819833,2.1913360910262116,100*(exp(b - se^2/2) - 1),reported,-0.28480979474697277,0.04330441323638182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.5769230769230775,490.0,binary,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c4,5,4,9,HEAT_D,heating,A_structural,binary,binary,-0.173,0.026,,,**,,,high,"Heat type dummy: 1 = individual heating, 0 = central heating. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.768,se,"Spatial error model, 10 km, GM 2-step",pct_premium,-15.91466416271443,2.1869577985960205,100*(exp(b - se^2/2) - 1),reported,-0.28786632917207705,0.043263147736843956,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.653846153846153,490.0,binary,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,True
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c5,5,5,9,HEAT_D,heating,A_structural,binary,binary,-0.162,0.041,,,**,,,high,"Heat type dummy: 1 = individual heating, 0 = central heating. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_lag,500.0,0.79,se,"Spatial lag model, 20 km, ML",pct_premium,-15.027329098337693,3.4868089386149554,100*(exp(b - se^2/2) - 1),reported,-0.17572049305527582,0.044472470464606846,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.951219512195122,490.0,binary,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c6,5,6,9,HEAT_D,heating,A_structural,binary,binary,-0.178,0.028,,,**,,,high,"Heat type dummy: 1 = individual heating, 0 = central heating. Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_lag,500.0,0.806,se,"Spatial lag model, 20 km, IV (2SLS)",pct_premium,-16.338559364568084,2.343438785768551,100*(exp(b - se^2/2) - 1),reported,-0.27602904475986434,0.04342029917570899,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.357142857142857,490.0,binary,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,True
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c1,5,1,9,BATH,bathrooms,A_structural,level,count,-0.034,0.023,,,,,,high,Number of bathrooms. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.893,se,"Spatial error model, 1.7 km weight matrix, ML",semi_elasticity,-3.4000000000000004,2.3,100*b/1 (per unit count),reported,-0.06663260333867135,0.045074996376160026,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4782608695652175,490.0,count,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c2,5,2,9,BATH,bathrooms,A_structural,level,count,0.024,0.026,,,,,,high,Number of bathrooms. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.765,se,"Spatial error model, 1.7 km, GM 2-step",semi_elasticity,2.4,2.6,100*b/1 (per unit count),reported,0.04166415515893598,0.0451361680888473,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9230769230769231,490.0,count,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c3,5,3,9,BATH,bathrooms,A_structural,level,count,0.003,0.032,,,,,,high,Number of bathrooms. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.822,se,"Spatial error model, 10 km, ML",semi_elasticity,0.3,3.2,100*b/1 (per unit count),reported,0.004235155312339974,0.045174989998293065,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.09375,490.0,count,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c4,5,4,9,BATH,bathrooms,A_structural,level,count,0.005,0.032,,,,,,high,Number of bathrooms. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.768,se,"Spatial error model, 10 km, GM 2-step",semi_elasticity,0.5,3.2,100*b/1 (per unit count),reported,0.007058479650613727,0.045174269763927855,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.15625,490.0,count,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c5,5,5,9,BATH,bathrooms,A_structural,level,count,-0.036,0.034,,,,,,high,Number of bathrooms. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_lag,500.0,0.79,se,"Spatial lag model, 20 km, ML",semi_elasticity,-3.5999999999999996,3.4000000000000004,100*b/1 (per unit count),reported,-0.0477781449812862,0.04512380359343698,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0588235294117645,490.0,count,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c6,5,6,9,BATH,bathrooms,A_structural,level,count,-0.018,0.033,,,,,,high,Number of bathrooms. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_lag,500.0,0.806,se,"Spatial lag model, 20 km, IV (2SLS)",semi_elasticity,-1.7999999999999998,3.3000000000000003,100*b/1 (per unit count),reported,-0.024633647168757707,0.045161686476055805,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5454545454545454,490.0,count,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c1,5,1,9,YEARS,age,A_structural,level,years,-0.024,0.004,,,**,,,high,Apartment age in years. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.893,se,"Spatial error model, 1.7 km weight matrix, ML",semi_elasticity,-2.4,0.4,100*b/1 (per year),reported,-0.2616124321181684,0.04360207201969473,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,490.0,years,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c2,5,2,9,YEARS,age,A_structural,level,years,-0.026,0.005,,,**,,,high,Apartment age in years. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.765,se,"Spatial error model, 1.7 km, GM 2-step",semi_elasticity,-2.6,0.5,100*b/1 (per year),reported,-0.22868689199227302,0.043978248460052514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.199999999999999,490.0,years,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c3,5,3,9,YEARS,age,A_structural,level,years,-0.032,0.006,,,**,,,high,Apartment age in years. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.822,se,"Spatial error model, 10 km, ML",semi_elasticity,-3.2,0.6,100*b/1 (per year),reported,-0.23423274901586713,0.043918640440475096,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.333333333333333,490.0,years,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c4,5,4,9,YEARS,age,A_structural,level,years,-0.033,0.006,,,**,,,high,Apartment age in years. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_error,500.0,0.768,se,"Spatial error model, 10 km, GM 2-step",semi_elasticity,-3.3000000000000003,0.6,100*b/1 (per year),reported,-0.24113299761177795,0.043842363202141445,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.5,490.0,years,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c5,5,5,9,YEARS,age,A_structural,level,years,-0.033,0.006,,,**,,,high,Apartment age in years. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_lag,500.0,0.79,se,"Spatial lag model, 20 km, ML",semi_elasticity,-3.3000000000000003,0.6,100*b/1 (per year),reported,-0.24113299761177795,0.043842363202141445,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.5,490.0,years,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c6,5,6,9,YEARS,age,A_structural,level,years,-0.034,0.006,,,**,,,high,Apartment age in years. Table legend: * 5% significance; ** 1% significance; ( ) standard error.,"ln PART (apartment price, million won)",log,spatial_lag,500.0,0.806,se,"Spatial lag model, 20 km, IV (2SLS)",semi_elasticity,-3.4000000000000004,0.6,100*b/1 (per year),reported,-0.24799686959560396,0.04376415345804775,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.666666666666667,490.0,years,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,True
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c1,5,1,9,PM10,air_pollution,E_environment,level,ug/m3,-0.006,0.003,,,,,,high,"PM10 concentration, ug/m3 (printed μm/m3). Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.893,se,"Spatial error model, 1.7 km weight matrix, ML",semi_elasticity,-0.6,0.3,100*b/1 (per ug/m3),reported,-0.0899842541331695,0.04499212706658476,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,490.0,ug/m3,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c2,5,2,9,PM10,air_pollution,E_environment,level,ug/m3,-0.007,0.003,,,*,,,high,"PM10 concentration, ug/m3 (printed μm/m3). Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.765,se,"Spatial error model, 1.7 km, GM 2-step",semi_elasticity,-0.7000000000000001,0.3,100*b/1 (per ug/m3),reported,-0.10482848367219184,0.04492649300236792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3333333333333335,490.0,ug/m3,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c3,5,3,9,PM10,air_pollution,E_environment,level,ug/m3,-0.021,0.003,,,**,,,high,"PM10 concentration, ug/m3 (printed μm/m3). Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.822,se,"Spatial error model, 10 km, ML",semi_elasticity,-2.1,0.3,100*b/1 (per ug/m3),reported,-0.30151134457776363,0.0430730492253948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,490.0,ug/m3,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c4,5,4,9,PM10,air_pollution,E_environment,level,ug/m3,-0.022,0.003,,,**,,,high,"PM10 concentration, ug/m3 (printed μm/m3). Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_error,500.0,0.768,se,"Spatial error model, 10 km, GM 2-step",semi_elasticity,-2.1999999999999997,0.3,100*b/1 (per ug/m3),reported,-0.31447831100338325,0.0428834060459159,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.333333333333333,490.0,ug/m3,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c5,5,5,9,PM10,air_pollution,E_environment,level,ug/m3,-0.013,0.003,,,**,,,high,"PM10 concentration, ug/m3 (printed μm/m3). Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_lag,500.0,0.79,se,"Spatial lag model, 20 km, ML",semi_elasticity,-1.3,0.3,100*b/1 (per ug/m3),reported,-0.19211356472533145,0.04433389955199957,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.333333333333333,490.0,ug/m3,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687,3e2f420e36b96c93f3636cc35296dc7c69414687:T5-c6,5,6,9,PM10,air_pollution,E_environment,level,ug/m3,-0.011,0.003,,,**,,,high,"PM10 concentration, ug/m3 (printed μm/m3). Table legend: * 5% significance; ** 1% significance; ( ) standard error.","ln PART (apartment price, million won)",log,spatial_lag,500.0,0.806,se,"Spatial lag model, 20 km, IV (2SLS)",semi_elasticity,-1.0999999999999999,0.3,100*b/1 (per ug/m3),reported,-0.16341640569676505,0.044568110644572285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.6666666666666665,490.0,ug/m3,,2013.0,South Korea,Asia,High income,2008.0,2008.0,condo_apartment,listing,journal,False,False,OLS,,2008.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,10,Floor1,floor_level,A_structural,dummy,binary,-0.02,,-0.7,,,,,high,first-floor dummy,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",pct_premium,-2.020132614629566,2.800567638019301,100*(exp(b - se^2/2) - 1),|b/t|,-0.03940989166038625,0.05629984522912321,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,10,Floor1,floor_level,A_structural,dummy,binary,-0.02,,-0.62,,,,,high,first-floor dummy,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",pct_premium,-2.0311182948745676,3.1619312042153394,100*(exp(b - se^2/2) - 1),|b/t|,-0.034911747316117805,0.05630926986470614,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.62,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,10,FloorT,floor_level,A_structural,dummy,binary,-0.06,,-2.27,,*,,,high,top-floor dummy,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",pct_premium,-5.856438413534015,2.4892454632182783,100*(exp(b - se^2/2) - 1),|b/t|,-0.12686655213055853,0.055888348956193185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.27,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,10,FloorT,floor_level,A_structural,dummy,binary,-0.06,,-2.13,,*,,,high,top-floor dummy,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",pct_premium,-5.860903425439989,2.6528578410823904,100*(exp(b - se^2/2) - 1),|b/t|,-0.11915687218698962,0.05594219351501859,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.13,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,10,Build,storeys,A_structural,dummy,binary,0.15,,6.53,,*,,,high,"nine-storey (newer, 1970s-80s) vs five-storey (1950s-60s) building; also proxies age","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",pct_premium,16.152775503309847,2.6688382298505733,100*(exp(b - se^2/2) - 1),|b/t|,0.34529444509793267,0.052878169233986624,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.53,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,10,Build,storeys,A_structural,dummy,binary,0.15,,6.48,,*,,,high,"nine-storey (newer, 1970s-80s) vs five-storey (1950s-60s) building; also proxies age","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",pct_premium,16.15230076732388,2.689431117426581,100*(exp(b - se^2/2) - 1),|b/t|,0.3429625796607519,0.05292632402172097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.48,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,10,Area,living_area,A_structural,log,m2,0.65,,7.24,,*,,,medium,"total area of the apartment; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",elasticity,0.65,0.08977900552486189,b (log-log),|b/t|,0.377710091428499,0.052169902131008146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.24,315.0,m2,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,10,Area,living_area,A_structural,log,m2,0.67,,7.46,,*,,,medium,"total area of the apartment; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",elasticity,0.67,0.08981233243967829,b (log-log),|b/t|,0.38748588575837034,0.05194180774240889,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.46,315.0,m2,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,10,Balc,terrace_balcony,C_exterior,level,count,-0.01,,-0.34,,,,,high,rank 0-2: balcony and/or loggia,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",semi_elasticity,-1.0,2.941176470588235,100*b/1 (per unit count),|b/t|,-0.01915331561482207,0.05633328122006491,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.34,315.0,count,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,10,Balc,terrace_balcony,C_exterior,level,count,-0.07,,-0.14,,,,,high,rank 0-2: balcony and/or loggia,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",semi_elasticity,-7.000000000000001,50.0,100*b/1 (per unit count),|b/t|,-0.007887860981163957,0.05634186415117112,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.14,315.0,count,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,10,Cond2,condition,A_structural,dummy,binary,0.02,,0.6,,,,,high,condition 2 satisfactory (ref: repair needed),"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",pct_premium,1.9634718913845939,3.4006711334225193,100*(exp(b - se^2/2) - 1),|b/t|,0.03378686891997429,0.05631144819995716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,10,Cond2,condition,A_structural,dummy,binary,0.02,,0.64,,,,,high,condition 2 satisfactory (ref: repair needed),"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",pct_premium,1.970331643888068,3.1881291875836117,100*(exp(b - se^2/2) - 1),|b/t|,0.036036493039342664,0.056307020373972914,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.64,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,10,Cond3,condition,A_structural,dummy,binary,0.02,,0.42,,,,,high,condition 3 cosmetic repair needed,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",pct_premium,1.9045304637745009,4.858101619175028,100*(exp(b - se^2/2) - 1),|b/t|,0.023657695904667257,0.05632784739206491,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.42,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,10,Cond3,condition,A_structural,dummy,binary,0.02,,0.33,,,,,high,condition 3 cosmetic repair needed,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",pct_premium,1.8329411488157143,6.183038424404581,100*(exp(b - se^2/2) - 1),|b/t|,0.01859018043623746,0.05633388010981049,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.33,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,10,Cond4,condition,A_structural,dummy,binary,0.04,,1.11,,,,,high,condition 4 normal,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",pct_premium,4.01351972430084,3.7506694565491467,100*(exp(b - se^2/2) - 1),|b/t|,0.062419459360192775,0.05623374717134484,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.11,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,10,Cond4,condition,A_structural,dummy,binary,0.04,,1.25,,,,,high,condition 4 normal,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",pct_premium,4.0278015473872,3.3305944774156426,100*(exp(b - se^2/2) - 1),|b/t|,0.0702554919986499,0.05620439359891992,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.25,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,10,Cond5,condition,A_structural,dummy,binary,0.05,,1.58,,,,,high,condition 5 good,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",pct_premium,5.074483458728696,3.326807267012735,100*(exp(b - se^2/2) - 1),|b/t|,0.08867224096627026,0.05612167149763941,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.58,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,10,Cond5,condition,A_structural,dummy,binary,0.06,,1.78,,,,,high,condition 5 good,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",pct_premium,6.123347781333988,3.579224314197841,100*(exp(b - se^2/2) - 1),|b/t|,0.09979102427069753,0.05606237318578512,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.78,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,10,Cond6,condition,A_structural,dummy,binary,0.13,,2.5,,*,,,high,condition 6 perfect,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",pct_premium,13.728972771593462,5.921907593288034,100*(exp(b - se^2/2) - 1),|b/t|,0.13948208816291768,0.05579283526516707,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,10,Cond6,condition,A_structural,dummy,binary,0.14,,2.75,,*,,,high,condition 6 perfect,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",pct_premium,14.878416151119955,5.8559393396367945,100*(exp(b - se^2/2) - 1),|b/t|,0.15311782647725627,0.05567920962809319,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.75,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,10,Cond7,condition,A_structural,dummy,binary,0.3,,6.08,,*,,,high,condition 7 Euro-renovation,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",pct_premium,34.82165949434486,6.660487537381594,100*(exp(b - se^2/2) - 1),|b/t|,0.3240805567107715,0.05330272314321901,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.08,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,10,Cond7,condition,A_structural,dummy,binary,0.31,,6.36,,*,,,high,condition 7 Euro-renovation,"ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",pct_premium,36.18064657152178,6.64562555630464,100*(exp(b - se^2/2) - 1),|b/t|,0.3373402020612933,0.05304091227378825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.36,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,11,DCBD,cbd_distance,D_location,log,km,-0.24,,-10.24,,*,,,medium,"road-network distance to CBD (central square); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",elasticity,-0.24,0.0234375,b (log-log),|b/t|,-0.4997455633034749,0.04880327766635496,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.24,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,11,DCBD,cbd_distance,D_location,log,km,-0.23,,-6.82,,*,,,medium,"road-network distance to CBD (central square); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",elasticity,-0.23,0.03372434017595308,b (log-log),|b/t|,-0.3586928960287861,0.05259426627988066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.82,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,11,DSCent,commercial_distance,D_location,log,km,-0.05,,-4.91,,*,,,medium,"distance to nearest secondary centre (business/commercial concentration); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",elasticity,-0.05,0.010183299389002037,b (log-log),|b/t|,-0.26663208597198074,0.0543038871633362,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.91,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,11,DSCent,commercial_distance,D_location,log,km,-0.04,,-3.47,,*,,,medium,"distance to nearest secondary centre (business/commercial concentration); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",elasticity,-0.04,0.011527377521613832,b (log-log),|b/t|,-0.19187943904785607,0.05529666831350319,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.47,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,11,DStop,transit_distance,D_location,log,km,-0.01,,-0.34,,,,,medium,"distance to nearest public transport stop; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",elasticity,-0.01,0.029411764705882353,b (log-log),|b/t|,-0.01915331561482207,0.05633328122006491,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.34,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,11,DRail,transit_distance,D_location,log,km,-0.11,,-5.44,,*,,,medium,"distance to the main railway station; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",elasticity,-0.11,0.020220588235294115,b (log-log),|b/t|,-0.29305240920200204,0.05386992816213273,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.44,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,11,DRail,transit_distance,D_location,log,km,-0.11,,-4.25,,*,,,medium,"distance to the main railway station; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",elasticity,-0.11,0.02588235294117647,b (log-log),|b/t|,-0.2328767123287671,0.0547945205479452,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.25,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,11,DWater,water_proximity,E_environment,log,km,-0.01,,-0.37,,,,,medium,"straight-line distance to water (ponds, river) merged with main parks/green areas; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",elasticity,-0.01,0.02702702702702703,b (log-log),|b/t|,-0.02084260964313135,0.05633137741386851,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.37,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,11,DWater,water_proximity,E_environment,log,km,-0.01,,-0.93,,,,,medium,"straight-line distance to water (ponds, river) merged with main parks/green areas; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",elasticity,-0.01,0.01075268817204301,b (log-log),|b/t|,-0.05232777447866215,0.05626642417060446,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.93,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOG,3,LOG,11,DNuis,hazard_site,E_environment,log,km,0.03,,1.54,,,,,medium,"distance to nearest nuisance (contaminating factories, slagheaps); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear (adjusted R2)",elasticity,0.03,0.01948051948051948,b (log-log),|b/t|,0.08644436534965663,0.0561327047725043,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.54,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T3-LOGDIR,3,LOGDIR,11,DNuis,hazard_site,E_environment,log,km,0.03,,1.29,,,,,medium,"distance to nearest nuisance (contaminating factories, slagheaps); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,325.0,0.77,t,"Whole sample, log-linear with direction x DCBD interactions (adjusted R2)",elasticity,0.03,0.023255813953488372,b (log-log),|b/t|,0.07249203560053111,0.05619537643452024,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.29,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,Floor1,floor_level,A_structural,dummy,binary,-0.2,,-2.24,,*,,,high,first-floor dummy,"ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),pct_premium,-18.452618729611135,7.310096009624838,100*(exp(b - se^2/2) - 1),|b/t|,-0.2676975571988046,0.11950783803518063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.24,65.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,Floor1,floor_level,A_structural,dummy,binary,-0.01,,-0.22,,,,,high,first-floor dummy,"ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),pct_premium,-1.0972416891766867,4.500226517041673,100*(exp(b - se^2/2) - 1),|b/t|,-0.014199507224627194,0.06454321465739633,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.22,240.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,FloorT,floor_level,A_structural,dummy,binary,-0.1,,-1.84,,,,,high,top-floor dummy,"ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),pct_premium,-9.6497898592384,4.91759466323891,100*(exp(b - se^2/2) - 1),|b/t|,-0.22250280594789706,0.12092543801516145,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.84,65.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,FloorT,floor_level,A_structural,dummy,binary,-0.05,,-1.6,,,,,high,top-floor dummy,"ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),pct_premium,-4.923492961478814,2.9725919515647314,100*(exp(b - se^2/2) - 1),|b/t|,-0.10273309938750283,0.06420818711718926,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6,240.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,Build,storeys,A_structural,dummy,binary,0.16,,2.22,,*,,,high,"nine-storey (newer, 1970s-80s) vs five-storey (1950s-60s) building; also proxies age","ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),pct_premium,17.04669926753386,8.457736007148183,100*(exp(b - se^2/2) - 1),|b/t|,0.2654765583058811,0.1195840352729194,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.22,65.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,Build,storeys,A_structural,dummy,binary,0.2,,7.71,,*,,,high,"nine-storey (newer, 1970s-80s) vs five-storey (1950s-60s) building; also proxies age","ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),pct_premium,22.099188565629202,3.168359943346744,100*(exp(b - se^2/2) - 1),|b/t|,0.4455500510754867,0.05778859287619801,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.71,240.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,Area,living_area,A_structural,log,m2,0.86,,4.81,,*,,,medium,"total area of the apartment; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),elasticity,0.86,0.1787941787941788,b (log-log),|b/t|,0.5123516766837174,0.10651802010056496,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.81,65.0,m2,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,Area,living_area,A_structural,log,m2,0.43,,3.53,,*,,,medium,"total area of the apartment; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),elasticity,0.43,0.12181303116147309,b (log-log),|b/t|,0.22216602379655923,0.06293655065058336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.53,240.0,m2,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,Balc,terrace_balcony,C_exterior,level,count,-0.05,,-0.8,,,,,high,rank 0-2: balcony and/or loggia,"ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),semi_elasticity,-5.0,6.25,100*b/1 (per unit count),|b/t|,-0.09874285972226249,0.12342857465282811,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8,65.0,count,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,Cond2,condition,A_structural,dummy,binary,-0.01,,-0.11,,,,,high,condition 2 satisfactory (ref: repair needed),"ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),pct_premium,-1.403284018019324,9.000453034083346,100*(exp(b - se^2/2) - 1),|b/t|,-0.013642551057226953,0.12402319142933593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.11,65.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,Cond2,condition,A_structural,dummy,binary,0.02,,0.46,,,,,high,condition 2 satisfactory (ref: repair needed),"ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),pct_premium,1.9237522110731486,4.435658000116329,100*(exp(b - se^2/2) - 1),|b/t|,0.02967979136219078,0.06452128556997995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.46,240.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,Cond3,condition,A_structural,dummy,binary,0.04,,0.33,,,,,high,condition 3 cosmetic repair needed,"ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),pct_premium,3.3192797170577437,12.61588817202895,100*(exp(b - se^2/2) - 1),|b/t|,0.040897217467322146,0.12393096202218833,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.33,65.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,Cond3,condition,A_structural,dummy,binary,0.02,,0.31,,,,,high,condition 3 cosmetic repair needed,"ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),pct_premium,1.8080340084591917,6.581944129204875,100*(exp(b - se^2/2) - 1),|b/t|,0.020006408906503785,0.06453680292420577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.31,240.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,Cond4,condition,A_structural,dummy,binary,0.01,,0.07,,,,,high,condition 4 normal,"ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),pct_premium,-0.020406080941326454,14.429288101202397,100*(exp(b - se^2/2) - 1),|b/t|,0.00868210417886961,0.12403005969813728,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.07,65.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,Cond4,condition,A_structural,dummy,binary,0.04,,1.04,,,,,high,condition 4 normal,"ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),pct_premium,4.00412283685363,4.003118362278417,100*(exp(b - se^2/2) - 1),|b/t|,0.06698095059175603,0.06440476018438081,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.04,240.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,Cond5,condition,A_structural,dummy,binary,-0.04,,-0.43,,,,,high,condition 5 good,"ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),pct_premium,-4.335859298392286,8.937576178161146,100*(exp(b - se^2/2) - 1),|b/t|,-0.05325923864269965,0.12385869451790617,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.43,65.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,Cond5,condition,A_structural,dummy,binary,0.09,,2.21,,*,,,high,condition 5 good,"ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),pct_premium,9.32673471051051,4.455913372555155,100*(exp(b - se^2/2) - 1),|b/t|,0.14122512888266253,0.06390277325007354,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.21,240.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,Cond6,condition,A_structural,dummy,binary,0.22,,1.85,,,,,high,condition 6 perfect,"ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),pct_premium,23.729697990754484,14.818209769147229,100*(exp(b - se^2/2) - 1),|b/t|,0.2236517286513659,0.12089282629803562,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.85,65.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,Cond6,condition,A_structural,dummy,binary,0.12,,2.25,,*,,,high,condition 6 perfect,"ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),pct_premium,12.589444026416663,6.01331654175667,100*(exp(b - se^2/2) - 1),|b/t|,0.1437288955267324,0.06387950912299217,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.25,240.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,Cond7,condition,A_structural,dummy,binary,0.15,,1.17,,,,,high,condition 7 Euro-renovation,"ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),pct_premium,15.232509450161679,14.895310804208759,100*(exp(b - se^2/2) - 1),|b/t|,0.14361623985874467,0.12274892295619201,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.17,65.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,Cond7,condition,A_structural,dummy,binary,0.33,,5.79,,*,,,high,condition 7 Euro-renovation,"ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),pct_premium,38.8710745246923,7.927797623368695,100*(exp(b - se^2/2) - 1),|b/t|,0.35009085379741806,0.06046474158850053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.79,240.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,DCBD,cbd_distance,D_location,log,km,-0.13,,-2.06,,*,,,medium,"road-network distance to CBD (central square); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),elasticity,-0.13,0.06310679611650485,b (log-log),|b/t|,-0.24755824824699635,0.12017390691601763,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.06,65.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,DCBD,cbd_distance,D_location,log,km,-0.31,,-10.65,,*,,,medium,"road-network distance to CBD (central square); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),elasticity,-0.31,0.029107981220657275,b (log-log),|b/t|,-0.5665033866172269,0.053192806255138676,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.65,240.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,DSCent,commercial_distance,D_location,log,km,-0.12,,-0.44,,,,,medium,"distance to nearest secondary centre (business/commercial concentration); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),elasticity,-0.12,0.2727272727272727,b (log-log),|b/t|,-0.05449418913505426,0.12385042985239605,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.44,65.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,True
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,DSCent,commercial_distance,D_location,log,km,-0.04,,-3.46,,*,,,medium,"distance to nearest secondary centre (business/commercial concentration); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),elasticity,-0.04,0.011560693641618498,b (log-log),|b/t|,-0.21797179565242103,0.06299762880127775,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.46,240.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,DStop,transit_distance,D_location,log,km,0.01,,0.09,,,,,medium,"distance to nearest public transport stop; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),elasticity,0.01,0.11111111111111112,b (log-log),|b/t|,0.011162430629402012,0.12402700699335571,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.09,65.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,DStop,transit_distance,D_location,log,km,0.01,,0.54,,,,,medium,"distance to nearest public transport stop; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),elasticity,0.01,0.018518518518518517,b (log-log),|b/t|,0.03483569385611229,0.06451054417798571,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.54,240.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,DRail,transit_distance,D_location,log,km,-0.83,,-1.48,,,,,medium,"distance to the main railway station; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),elasticity,-0.83,0.5608108108108107,b (log-log),|b/t|,-0.18055441069973094,0.12199622344576415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.48,65.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,DRail,transit_distance,D_location,log,km,-0.08,,-3.95,,*,,,medium,"distance to the main railway station; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),elasticity,-0.08,0.020253164556962026,b (log-log),|b/t|,-0.24706688914300307,0.06254857952987418,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.95,240.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,DWater,water_proximity,E_environment,log,km,0.07,,0.93,,,,,medium,"straight-line distance to water (ponds, river) merged with main parks/green areas; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),elasticity,0.07,0.07526881720430108,b (log-log),|b/t|,0.11459243030745948,0.12321766699726827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.93,65.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,DWater,water_proximity,E_environment,log,km,-0.04,,-2.03,,*,,,medium,"straight-line distance to water (ponds, river) merged with main parks/green areas; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),elasticity,-0.04,0.01970443349753695,b (log-log),|b/t|,-0.12992524867030236,0.06400258555187309,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.03,240.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Cent,4,2 (LOG_Cent),13,DNuis,hazard_site,E_environment,log,km,-0.12,,-0.54,,,,,medium,"distance to nearest nuisance (contaminating factories, slagheaps); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,75.0,0.47,t,Central administrative district only; Prest omitted (adjusted R2),elasticity,-0.12,0.2222222222222222,b (log-log),|b/t|,-0.06682902178712688,0.12375744775393865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.54,65.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:T4-LOG_Out,4,4 (LOG_Out),13,DNuis,hazard_site,E_environment,log,km,0.03,,1.72,,,,,medium,"distance to nearest nuisance (contaminating factories, slagheaps); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,OLS,250.0,0.73,t,Outside the central district (adjusted R2),elasticity,0.03,0.01744186046511628,b (log-log),|b/t|,0.11034749723188901,0.0641555216464471,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.72,240.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,ols,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,Floor1,floor_level,A_structural,dummy,binary,-0.02,,-0.82,,,,,high,first-floor dummy,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",pct_premium,-2.009283559022046,2.390728471479891,100*(exp(b - se^2/2) - 1),|b/t|,-0.04615253351179462,0.05628357745340808,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.82,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,Floor1,floor_level,A_structural,dummy,binary,-0.03,,-0.99,,,,,high,first-floor dummy,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",pct_premium,-2.9999931457920237,2.9407440410560857,100*(exp(b - se^2/2) - 1),|b/t|,-0.05569360476701566,0.05625616643132895,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.99,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,Floor1,floor_level,A_structural,dummy,binary,-0.02,,-0.77,,,,,high,first-floor dummy,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",pct_premium,-2.0131916461883392,2.545970580017546,100*(exp(b - se^2/2) - 1),|b/t|,-0.04334381290868805,0.05629066611517928,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.77,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,Floor1,floor_level,A_structural,dummy,binary,-0.02,,-0.9,,,,,high,first-floor dummy,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",pct_premium,-2.0043321179932128,2.178219274015012,100*(exp(b - se^2/2) - 1),|b/t|,-0.05064418313919596,0.05627131459910662,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,FloorT,floor_level,A_structural,dummy,binary,-0.06,,-2.51,,*,,,high,top-floor dummy,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",pct_premium,-5.850449929131418,2.25122996075916,100*(exp(b - se^2/2) - 1),|b/t|,-0.14002909794077215,0.055788485235367384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.51,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,FloorT,floor_level,A_structural,dummy,binary,-0.06,,-2.33,,*,,,high,top-floor dummy,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",pct_premium,-5.8547665050125435,2.4251447216761766,100*(exp(b - se^2/2) - 1),|b/t|,-0.13016375884216344,0.05586427418118602,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.33,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,FloorT,floor_level,A_structural,dummy,binary,-0.06,,-2.41,,*,,,high,top-floor dummy,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",pct_premium,-5.852728534274143,2.34464199232593,100*(exp(b - se^2/2) - 1),|b/t|,-0.1345533081928202,0.05583124821278845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.41,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,FloorT,floor_level,A_structural,dummy,binary,-0.05,,-2.24,,*,,,high,top-floor dummy,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",pct_premium,-4.900751919441271,2.1232799654033796,100*(exp(b - se^2/2) - 1),|b/t|,-0.12521636333734257,0.055900162204170795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.24,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,Build,storeys,A_structural,dummy,binary,0.14,,6.11,,*,,,high,"nine-storey (newer, 1970s-80s) vs five-storey (1950s-60s) building; also proxies age","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",pct_premium,14.997188163934494,2.635651912275153,100*(exp(b - se^2/2) - 1),|b/t|,0.3255105763684502,0.053275053415458296,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.11,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,Build,storeys,A_structural,dummy,binary,0.16,,6.59,,*,,,high,"nine-storey (newer, 1970s-80s) vs five-storey (1950s-60s) building; also proxies age","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",pct_premium,17.31650413163226,2.849191796034744,100*(exp(b - se^2/2) - 1),|b/t|,0.34808426333136583,0.05282007030824974,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.59,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,Build,storeys,A_structural,dummy,binary,0.14,,6.14,,*,,,high,"nine-storey (newer, 1970s-80s) vs five-storey (1950s-60s) building; also proxies age","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",pct_premium,14.997482438029941,2.6227741342021473,100*(exp(b - se^2/2) - 1),|b/t|,0.3269383658767514,0.053247290859405765,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.14,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,Build,storeys,A_structural,dummy,binary,0.16,,6.58,,*,,,high,"nine-storey (newer, 1970s-80s) vs five-storey (1950s-60s) building; also proxies age","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",pct_premium,17.316398951903466,2.8535218747521225,100*(exp(b - se^2/2) - 1),|b/t|,0.3476199328318098,0.05282977702611092,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.58,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,Area,living_area,A_structural,log,m2,0.6,,6.4,,*,,,medium,"total area of the apartment; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",elasticity,0.6,0.09374999999999999,b (log-log),|b/t|,0.3392183793497032,0.05300287177339113,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.4,315.0,m2,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,Area,living_area,A_structural,log,m2,0.6,,6.25,,*,,,medium,"total area of the apartment; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",elasticity,0.6,0.096,b (log-log),|b/t|,0.332154431909686,0.05314470910554976,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.25,315.0,m2,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,Area,living_area,A_structural,log,m2,0.62,,6.56,,*,,,medium,"total area of the apartment; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",elasticity,0.62,0.09451219512195122,b (log-log),|b/t|,0.34669050432024484,0.052849162243939755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.56,315.0,m2,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,Area,living_area,A_structural,log,m2,0.61,,6.44,,*,,,medium,"total area of the apartment; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",elasticity,0.61,0.09472049689440994,b (log-log),|b/t|,0.34109250876411906,0.052964675273931526,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.44,315.0,m2,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,Balc,terrace_balcony,C_exterior,level,count,-0.01,,-0.31,,,,,high,rank 0-2: balcony and/or loggia,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",semi_elasticity,-1.0,3.225806451612903,100*b/1 (per unit count),|b/t|,-0.017463857536251477,0.056335024310488625,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.31,315.0,count,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,Balc,terrace_balcony,C_exterior,level,count,-0.01,,-0.08,,,,,high,rank 0-2: balcony and/or loggia,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",semi_elasticity,-1.0,12.5,100*b/1 (per unit count),|b/t|,-0.004507443568881748,0.056343044611021846,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.08,315.0,count,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,Balc,terrace_balcony,C_exterior,level,count,-0.01,,-0.14,,,,,high,rank 0-2: balcony and/or loggia,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",semi_elasticity,-1.0,7.142857142857142,100*b/1 (per unit count),|b/t|,-0.007887860981163957,0.05634186415117112,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.14,315.0,count,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,Balc,terrace_balcony,C_exterior,level,count,0.01,,0.11,,,,,high,rank 0-2: balcony and/or loggia,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",semi_elasticity,1.0,9.090909090909092,100*b/1 (per unit count),|b/t|,0.00619767883436825,0.05634253485789318,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.11,315.0,count,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,Cond2,condition,A_structural,dummy,binary,0.01,,0.34,,,,,high,condition 2 satisfactory (ref: repair needed),"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",pct_premium,0.9613388640344889,2.9707357855416703,100*(exp(b - se^2/2) - 1),|b/t|,0.01915331561482207,0.05633328122006491,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.34,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,Cond2,condition,A_structural,dummy,binary,0.01,,0.26,,,,,high,condition 2 satisfactory (ref: repair needed),"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",pct_premium,0.9303364776549916,3.8848083349391076,100*(exp(b - se^2/2) - 1),|b/t|,0.014647768770770208,0.05633757219527003,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.26,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,Cond2,condition,A_structural,dummy,binary,0.01,,0.38,,,,,high,condition 2 satisfactory (ref: repair needed),"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",pct_premium,0.9700487265232871,2.658026755484652,100*(exp(b - se^2/2) - 1),|b/t|,0.021405668700097802,0.05633070710552054,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.38,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,Cond2,condition,A_structural,dummy,binary,0.01,,0.3,,,,,high,condition 2 satisfactory (ref: repair needed),"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",pct_premium,0.9489183945532886,3.3668338902805597,100*(exp(b - se^2/2) - 1),|b/t|,0.016900670885446462,0.05633556961815487,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,Cond3,condition,A_structural,dummy,binary,0.02,,0.29,,,,,high,condition 3 cosmetic repair needed,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",pct_premium,1.7778060074763014,7.035871310529352,100*(exp(b - se^2/2) - 1),|b/t|,0.016337468147964496,0.05633609706194654,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.29,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,Cond3,condition,A_structural,dummy,binary,0.01,,0.21,,,,,high,condition 3 cosmetic repair needed,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",pct_premium,0.890563443946979,4.8097627004008,100*(exp(b - se^2/2) - 1),|b/t|,0.011831331401985824,0.056339673342789644,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.21,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,Cond3,condition,A_structural,dummy,binary,0.01,,0.25,,,,,high,condition 3 cosmetic repair needed,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",pct_premium,0.9242450080380493,4.040200668336672,100*(exp(b - se^2/2) - 1),|b/t|,0.014084507042253521,0.056338028169014086,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.25,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,Cond3,condition,A_structural,dummy,binary,0.01,,0.16,,,,,high,condition 3 cosmetic repair needed,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",pct_premium,0.8079338115755785,6.312813544276049,100*(exp(b - se^2/2) - 1),|b/t|,0.009014612416486226,0.05634132760303891,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.16,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,Cond4,condition,A_structural,dummy,binary,0.03,,0.82,,,,,high,condition 4 normal,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",pct_premium,2.976513863966801,3.769955612025062,100*(exp(b - se^2/2) - 1),|b/t|,0.04615253351179462,0.05628357745340808,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.82,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,Cond4,condition,A_structural,dummy,binary,0.03,,0.71,,,,,high,condition 4 normal,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",pct_premium,2.9535078226555322,4.354033242057114,100*(exp(b - se^2/2) - 1),|b/t|,0.0399719969007544,0.05629858718416112,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.71,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,Cond4,condition,A_structural,dummy,binary,0.03,,0.91,,,,,high,condition 4 normal,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",pct_premium,2.9894724061419797,3.397102859187419,100*(exp(b - se^2/2) - 1),|b/t|,0.051205428939339034,0.05626970213114179,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.91,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,Cond4,condition,A_structural,dummy,binary,0.03,,0.8,,,,,high,condition 4 normal,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",pct_premium,2.973025027015286,3.8642045023256886,100*(exp(b - se^2/2) - 1),|b/t|,0.045029172875303725,0.05628646609412965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,Cond5,condition,A_structural,dummy,binary,0.05,,1.31,,,,,high,condition 5 good,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",pct_premium,5.050563375831252,4.0124851006718485,100*(exp(b - se^2/2) - 1),|b/t|,0.0736098995681557,0.056190763029126484,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.31,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,Cond5,condition,A_structural,dummy,binary,0.05,,1.33,,,,,high,condition 5 good,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",pct_premium,5.0528474024937875,3.9521469788572334,100*(exp(b - se^2/2) - 1),|b/t|,0.07472748614816546,0.05618607981065071,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.33,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,Cond5,condition,A_structural,dummy,binary,0.05,,1.44,,,,,high,condition 5 good,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",pct_premium,5.063756393345464,3.6502468624167506,100*(exp(b - se^2/2) - 1),|b/t|,0.08086907029713811,0.0561590765952348,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.44,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,Cond5,condition,A_structural,dummy,binary,0.05,,1.46,,,,,high,condition 5 good,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",pct_premium,5.065479704887821,3.600243480739809,100*(exp(b - se^2/2) - 1),|b/t|,0.08198475373036565,0.05615394091120936,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.46,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,Cond6,condition,A_structural,dummy,binary,0.12,,2.56,,*,,,high,condition 6 perfect,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",pct_premium,12.625882673412292,5.285141491778324,100*(exp(b - se^2/2) - 1),|b/t|,0.14276221489679658,0.055766490194061165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.56,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,Cond6,condition,A_structural,dummy,binary,0.13,,2.65,,*,,,high,condition 6 perfect,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",pct_premium,13.74588834966497,5.586705276686824,100*(exp(b - se^2/2) - 1),|b/t|,0.1476735670200202,0.05572587434717744,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.65,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,Cond6,condition,A_structural,dummy,binary,0.13,,2.8,,*,,,high,condition 6 perfect,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",pct_premium,13.760160835220248,5.2874174940071725,100*(exp(b - se^2/2) - 1),|b/t|,0.15583476916873645,0.055655274703120164,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,Cond6,condition,A_structural,dummy,binary,0.14,,2.88,,*,,,high,condition 6 perfect,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",pct_premium,14.891552985644463,5.591608744444856,100*(exp(b - se^2/2) - 1),|b/t|,0.16017450730260027,0.05561614836895843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.88,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,Cond7,condition,A_structural,dummy,binary,0.3,,5.92,,*,,,high,condition 7 Euro-renovation,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",pct_premium,34.81266848689699,6.840500714067583,100*(exp(b - se^2/2) - 1),|b/t|,0.3164163372364734,0.053448705614269156,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.92,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,Cond7,condition,A_structural,dummy,binary,0.3,,5.83,,*,,,high,condition 7 Euro-renovation,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",pct_premium,34.80728288314119,6.946100210511164,100*(exp(b - se^2/2) - 1),|b/t|,0.31207770805439095,0.05352962402305162,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.83,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,Cond7,condition,A_structural,dummy,binary,0.31,,6.01,,*,,,high,condition 7 Euro-renovation,"ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",pct_premium,36.16125770440826,7.032642019650169,100*(exp(b - se^2/2) - 1),|b/t|,0.3207352005971049,0.053366921896356896,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.01,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,Cond7,condition,A_structural,dummy,binary,0.3,,5.94,,*,,,high,condition 7 Euro-renovation,"ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",pct_premium,34.813832193436056,6.817468725131328,100*(exp(b - se^2/2) - 1),|b/t|,0.31737779808081695,0.053430605737511266,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.94,315.0,binary,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,DCBD,cbd_distance,D_location,log,km,-0.19,,-9.11,,*,,,medium,"road-network distance to CBD (central square); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",elasticity,-0.19,0.020856201975850714,b (log-log),|b/t|,-0.456647570261186,0.05012596819551988,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.11,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,DCBD,cbd_distance,D_location,log,km,-0.23,,-11.18,,*,,,medium,"road-network distance to CBD (central square); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",elasticity,-0.23,0.020572450805008947,b (log-log),|b/t|,-0.5329901905052631,0.047673541190095085,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.18,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,DCBD,cbd_distance,D_location,log,km,-0.18,,-7.25,,*,,,medium,"road-network distance to CBD (central square); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",elasticity,-0.18,0.02482758620689655,b (log-log),|b/t|,-0.37815723008406554,0.05215961794262974,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.25,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,DCBD,cbd_distance,D_location,log,km,-0.21,,-7.72,,*,,,medium,"road-network distance to CBD (central square); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",elasticity,-0.21,0.027202072538860103,b (log-log),|b/t|,-0.3988727260325916,0.05166745155862586,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.72,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,DSCent,commercial_distance,D_location,log,km,-0.05,,-4.26,,*,,,medium,"distance to nearest secondary centre (business/commercial concentration); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",elasticity,-0.05,0.011737089201877935,b (log-log),|b/t|,-0.23339484236062255,0.05478752168089732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.26,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,DSCent,commercial_distance,D_location,log,km,-0.05,,-4.04,,*,,,medium,"distance to nearest secondary centre (business/commercial concentration); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",elasticity,-0.05,0.012376237623762377,b (log-log),|b/t|,-0.2219506852121695,0.054938288418853835,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.04,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,DSCent,commercial_distance,D_location,log,km,-0.04,,-3.26,,*,,,medium,"distance to nearest secondary centre (business/commercial concentration); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",elasticity,-0.04,0.012269938650306749,b (log-log),|b/t|,-0.18065791593248273,0.05541653862959593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.26,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,DSCent,commercial_distance,D_location,log,km,-0.04,,-2.84,,*,,,medium,"distance to nearest secondary centre (business/commercial concentration); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",elasticity,-0.04,0.014084507042253521,b (log-log),|b/t|,-0.15800578272253007,0.055635838986806366,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.84,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,DStop,transit_distance,D_location,log,km,-0.01,,-0.32,,,,,medium,"distance to nearest public transport stop; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",elasticity,-0.01,0.03125,b (log-log),|b/t|,-0.01802702756496147,0.056334461140504596,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.32,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,DStop,transit_distance,D_location,log,km,-0.01,,-0.62,,,,,medium,"distance to nearest public transport stop; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",elasticity,-0.01,0.016129032258064516,b (log-log),|b/t|,-0.034911747316117805,0.05630926986470614,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.62,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,DStop,transit_distance,D_location,log,km,-0.01,,-0.22,,,,,medium,"distance to nearest public transport stop; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",elasticity,-0.01,0.045454545454545456,b (log-log),|b/t|,-0.012394643549183727,0.05633928885992604,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.22,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,DStop,transit_distance,D_location,log,km,-0.01,,-0.52,,,,,medium,"distance to nearest public transport stop; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",elasticity,-0.01,0.019230769230769232,b (log-log),|b/t|,-0.029286113740986164,0.05631944950189647,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.52,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,DRail,transit_distance,D_location,log,km,-0.08,,-4.32,,*,,,medium,"distance to the main railway station; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",elasticity,-0.08,0.018518518518518517,b (log-log),|b/t|,-0.23649943751613672,0.05474524016577239,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.32,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,DRail,transit_distance,D_location,log,km,-0.11,,-4.86,,*,,,medium,"distance to the main railway station; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",elasticity,-0.11,0.022633744855967076,b (log-log),|b/t|,-0.26410718913075637,0.054343043031019826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.86,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,DRail,transit_distance,D_location,log,km,-0.08,,-3.56,,*,,,medium,"distance to the main railway station; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",elasticity,-0.08,0.02247191011235955,b (log-log),|b/t|,-0.19666599409323496,0.05524325676776263,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.56,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,DRail,transit_distance,D_location,log,km,-0.1,,-4.01,,*,,,medium,"distance to the main railway station; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",elasticity,-0.1,0.02493765586034913,b (log-log),|b/t|,-0.22038286963327514,0.05495832160430801,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.01,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,21,DWater,water_proximity,E_environment,log,km,-0.01,,-0.36,,,,,medium,"straight-line distance to water (ponds, river) merged with main parks/green areas; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",elasticity,-0.01,0.02777777777777778,b (log-log),|b/t|,-0.020279530753310925,0.05633202987030813,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.36,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,21,DWater,water_proximity,E_environment,log,km,-0.01,,-0.68,,,,,medium,"straight-line distance to water (ponds, river) merged with main parks/green areas; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",elasticity,-0.01,0.014705882352941176,b (log-log),|b/t|,-0.03828556945996004,0.05630230802935301,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.68,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,21,DWater,water_proximity,E_environment,log,km,-0.01,,-0.87,,,,,medium,"straight-line distance to water (ponds, river) merged with main parks/green areas; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",elasticity,-0.01,0.011494252873563218,b (log-log),|b/t|,-0.04896015993215738,0.05627604589903147,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.87,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,21,DWater,water_proximity,E_environment,log,km,-0.02,,-1.27,,,,,medium,"straight-line distance to water (ponds, river) merged with main parks/green areas; regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",elasticity,-0.02,0.015748031496062992,b (log-log),|b/t|,-0.07137389836806626,0.05619991997485532,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.27,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SAR,Appendix,LOG SAR,22,DNuis,hazard_site,E_environment,log,km,0.02,,1.16,,,,,medium,"distance to nearest nuisance (contaminating factories, slagheaps); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial autoregressive (lag) model, rho 0.21 (3.74)* (adjusted R2)",elasticity,0.02,0.01724137931034483,b (log-log),|b/t|,0.06521944369624494,0.05622365835883185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.16,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOG-SEM,Appendix,LOG SEM,22,DNuis,hazard_site,E_environment,log,km,0.02,,1.18,,,,,medium,"distance to nearest nuisance (contaminating factories, slagheaps); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model, lambda 0.22 (3.32)* (adjusted R2)",elasticity,0.02,0.01694915254237288,b (log-log),|b/t|,0.0663390099659505,0.0562194999711445,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.18,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SAR,Appendix,LOGDIR SAR,22,DNuis,hazard_site,E_environment,log,km,0.02,,1.0,,,,,medium,"distance to nearest nuisance (contaminating factories, slagheaps); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_lag,325.0,0.77,t,"Spatial lag model with direction interactions, rho 0.19 (3.31)* (adjusted R2)",elasticity,0.02,0.02,b (log-log),|b/t|,0.0562543950463012,0.0562543950463012,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba,416244dcac790a50e1100858c6071c54dd1650ba:A-LOGDIR-SEM,Appendix,LOGDIR SEM,22,DNuis,hazard_site,E_environment,log,km,0.02,,0.91,,,,,medium,"distance to nearest nuisance (contaminating factories, slagheaps); regressor assumed logged in the log model (not stated; inferred from coefficient magnitudes, see study notes)","ln(asking price, USD)",log,spatial_error,325.0,0.78,t,"Spatial error model with direction interactions, lambda 0.21 (3.18)* (adjusted R2)",elasticity,0.02,0.021978021978021976,b (log-log),|b/t|,0.051205428939339034,0.05626970213114179,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.91,315.0,km,,2007.0,Ukraine,Europe,Lower middle income,2005.0,2005.0,condo_apartment,listing,journal,False,False,robust,,2005.0,spatial,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T6-M1,6,Model 1,9,Bedrooms,bedrooms,A_structural,level,count,0.589,0.005,114.16,0.0,,0.579,0.599,high,studios coded 0,"ln(monthly rent, THB)",log,OLS,14849.0,0.492,se,Pooled three cities; city dummies + bedrooms (adj. R2 0.492),semi_elasticity,58.9,0.5,100*b/1 (per unit count),reported,0.683807319649105,0.005989902940163848,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),114.16,14839.0,count,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,True
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T6-M2,6,Model 2,9,Bedrooms,bedrooms,A_structural,level,count,0.104,0.009,12.202,0.0,,0.087,0.12,high,,"ln(monthly rent, THB)",log,OLS,14849.0,0.662,se,Pooled three cities; adds ln(size) (adj. R2 0.662),semi_elasticity,10.4,0.8999999999999999,100*b/1 (per unit count),reported,0.09966915802033444,0.008168264056739422,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.202,14839.0,count,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T6-M2,6,Model 2,9,ln(size),living_area,A_structural,log,m2,0.822,0.012,67.554,0.0,,0.798,0.846,high,"unit size in sqm, log","ln(monthly rent, THB)",log,OLS,14849.0,0.662,se,Pooled three cities; adds ln(size) (adj. R2 0.662),elasticity,0.822,0.012,b (log-log),reported,0.4849776705275907,0.007179111089315077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),67.554,14839.0,m2,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T7-M3,7,Model 3,11,View: Garden,view,E_environment,binary,binary,-0.074,0.016,-4.728,0.0,,-0.105,-0.043,high,ref: city view; %change -7.1,"ln(monthly rent, THB)",log,OLS,13224.0,0.668,se,"Pooled three cities, listings with bathrooms and view type; adds bathrooms + view dummies (ref: city view); adj. R2 0.668",pct_premium,-7.144716852817057,1.4858747101460597,100*(exp(b - se^2/2) - 1),reported,-0.04109540656009852,0.008691921861272952,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.728,13214.0,binary,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T7-M3,7,Model 3,11,View: Lake,view,E_environment,binary,binary,0.183,0.033,5.49,0.0,,0.117,0.248,high,ref: city view; %change +20.0,"ln(monthly rent, THB)",log,OLS,13224.0,0.668,se,"Pooled three cities, listings with bathrooms and view type; adds bathrooms + view dummies (ref: city view); adj. R2 0.668",pct_premium,20.016074261220453,3.9626875466667415,100*(exp(b - se^2/2) - 1),reported,0.047704622264080176,0.00868936653261934,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.49,13214.0,binary,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T7-M3,7,Model 3,11,View: Mountain,view,E_environment,binary,binary,-0.079,0.017,-4.519,0.0,,-0.113,-0.045,high,ref: city view; %change -7.6,"ln(monthly rent, THB)",log,OLS,13224.0,0.668,se,"Pooled three cities, listings with bathrooms and view type; adds bathrooms + view dummies (ref: city view); adj. R2 0.668",pct_premium,-7.6093589677367905,1.5708678715566475,100*(exp(b - se^2/2) - 1),reported,-0.039281662728273464,0.00869255647892752,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.519,13214.0,binary,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T7-M3,7,Model 3,11,View: Pool,view,E_environment,binary,binary,-0.136,0.013,-10.314,0.0,,-0.162,-0.11,high,ref: city view; %change -12.7,"ln(monthly rent, THB)",log,OLS,13224.0,0.668,se,"Pooled three cities, listings with bathrooms and view type; adds bathrooms + view dummies (ref: city view); adj. R2 0.668",pct_premium,-12.723111959765642,1.134695422235335,100*(exp(b - se^2/2) - 1),reported,-0.08936528458881621,0.008664464280474715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.314,13214.0,binary,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,True
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T7-M3,7,Model 3,11,View: River,view,E_environment,binary,binary,-0.158,0.049,-3.205,0.001,,-0.255,-0.061,high,ref: city view; %change -14.6,"ln(monthly rent, THB)",log,OLS,13224.0,0.668,se,"Pooled three cities, listings with bathrooms and view type; adds bathrooms + view dummies (ref: city view); adj. R2 0.668",pct_premium,-14.717464965665418,4.18386393164556,100*(exp(b - se^2/2) - 1),reported,-0.027870332294304807,0.00869589151148356,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.205,13214.0,binary,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,True
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T7-M3,7,Model 3,11,View: Sea,view,E_environment,binary,binary,0.159,0.015,10.491,0.0,,0.129,0.188,high,ref: city view; %change +17.2,"ln(monthly rent, THB)",log,OLS,13224.0,0.668,se,"Pooled three cities, listings with bathrooms and view type; adds bathrooms + view dummies (ref: city view); adj. R2 0.668",pct_premium,17.2206066080139,1.7585069200210761,100*(exp(b - se^2/2) - 1),reported,0.09088633264497305,0.008663266861593084,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.491,13214.0,binary,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T7-M3,7,Model 3,11,View: Skyline,view,E_environment,binary,binary,0.044,0.014,3.206,0.001,,0.017,0.071,high,ref: city view; %change +4.5,"ln(monthly rent, THB)",log,OLS,13224.0,0.668,se,"Pooled three cities, listings with bathrooms and view type; adds bathrooms + view dummies (ref: city view); adj. R2 0.668",pct_premium,4.487995163550607,1.4629752968438214,100*(exp(b - se^2/2) - 1),reported,0.027879021428076266,0.008695889403642005,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.206,13214.0,binary,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T7-M3,7,Model 3,11,View: Unblocked Open,view,E_environment,binary,binary,-0.092,0.015,-6.075,0.0,,-0.121,-0.062,high,ref: city view; %change -8.8,"ln(monthly rent, THB)",log,OLS,13224.0,0.668,se,"Pooled three cities, listings with bathrooms and view type; adds bathrooms + view dummies (ref: city view); adj. R2 0.668",pct_premium,-8.799745651253444,1.3681577243176355,100*(exp(b - se^2/2) - 1),reported,-0.052774423985483356,0.008687147981149522,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.075,13214.0,binary,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T7-M3,7,Model 3,11,Bedrooms,bedrooms,A_structural,level,count,0.088,0.009,9.521,0.0,,0.07,0.107,high,,"ln(monthly rent, THB)",log,OLS,13224.0,0.668,se,"Pooled three cities, listings with bathrooms and view type; adds bathrooms + view dummies (ref: city view); adj. R2 0.668",semi_elasticity,8.799999999999999,0.8999999999999999,100*b/1 (per unit count),reported,0.08254311366447378,0.00866958446218609,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.521,13214.0,count,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T7-M3,7,Model 3,11,ln(size),living_area,A_structural,log,m2,0.755,0.016,47.358,0.0,,0.723,0.786,high,"unit size in sqm, log","ln(monthly rent, THB)",log,OLS,13224.0,0.668,se,"Pooled three cities, listings with bathrooms and view type; adds bathrooms + view dummies (ref: city view); adj. R2 0.668",elasticity,0.755,0.016,b (log-log),reported,0.38092005477507007,0.008043415152140507,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.358,13214.0,m2,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T7-M3,7,Model 3,11,Bathrooms,bathrooms,A_structural,level,count,0.077,0.013,5.997,0.0,,0.052,0.102,high,,"ln(monthly rent, THB)",log,OLS,13224.0,0.668,se,"Pooled three cities, listings with bathrooms and view type; adds bathrooms + view dummies (ref: city view); adj. R2 0.668",semi_elasticity,7.7,1.3,100*b/1 (per unit count),reported,0.05209867755491866,0.00868745665414685,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.997,13214.0,count,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T8-BKK,8,Bangkok (+ transit distance),12,Distance to BTS/MRT (km),transit_distance,D_location,level,km,-0.082,0.004,,0.0,,,,high,distance to nearest BTS skytrain / MRT station; %change -7.9,"ln(monthly rent, THB)",log,OLS,7195.0,0.674,se,Bangkok only; Model 3 covariates + distance to BTS/MRT; adj. R2 0.674; only listed coefficients printed,semi_elasticity,-8.200000000000001,0.4,100*b/1 (X per km->km),reported,-0.2350699493108347,0.011466826795650472,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-20.5,7185.0,km,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T8-BKK,8,Bangkok (+ transit distance),12,ln(size),living_area,A_structural,log,m2,0.735,0.024,,0.0,,,,high,,"ln(monthly rent, THB)",log,OLS,7195.0,0.674,se,Bangkok only; Model 3 covariates + distance to BTS/MRT; adj. R2 0.674; only listed coefficients printed,elasticity,0.735,0.024,b (log-log),reported,0.3397979814429507,0.011095444292014716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.625,7185.0,m2,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T8-BKK,8,Bangkok (+ transit distance),12,Bathrooms,bathrooms,A_structural,level,count,0.086,0.015,,0.0,,,,high,,"ln(monthly rent, THB)",log,OLS,7195.0,0.674,se,Bangkok only; Model 3 covariates + distance to BTS/MRT; adj. R2 0.674; only listed coefficients printed,semi_elasticity,8.6,1.5,100*b/1 (per unit count),reported,0.06748428189236445,0.011770514283551938,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.733333333333333,7185.0,count,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T8-BKK,8,Bangkok (+ transit distance),12,Bedrooms,bedrooms,A_structural,level,count,0.07,0.014,,0.0,,,,high,,"ln(monthly rent, THB)",log,OLS,7195.0,0.674,se,Bangkok only; Model 3 covariates + distance to BTS/MRT; adj. R2 0.674; only listed coefficients printed,semi_elasticity,7.000000000000001,1.4000000000000001,100*b/1 (per unit count),reported,0.058884687143838495,0.0117769374287677,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,7185.0,count,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T8-PKT,8,Phuket & Pattaya (+ floor level),12,Floor level,floor_level,A_structural,level,count,0.002,0.001,,0.183,,,,high,"text reports 0.0017 per storey, p=0.18","ln(monthly rent, THB)",log,OLS,4422.0,0.703,se,Phuket and Pattaya only (Phuket reference); Model 3 covariates + floor level; adj. R2 0.703; only listed coefficients printed,semi_elasticity,0.2,0.1,100*b/1 (per unit count),reported,0.0300964632714423,0.01504823163572115,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,4412.0,count,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T8-PKT,8,Phuket & Pattaya (+ floor level),12,ln(size),living_area,A_structural,log,m2,0.629,0.021,,0.0,,,,high,,"ln(monthly rent, THB)",log,OLS,4422.0,0.703,se,Phuket and Pattaya only (Phuket reference); Model 3 covariates + floor level; adj. R2 0.703; only listed coefficients printed,elasticity,0.629,0.021,b (log-log),reported,0.41107309444665124,0.013724220959268165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.95238095238095,4412.0,m2,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T8-PKT,8,Phuket & Pattaya (+ floor level),12,Bathrooms,bathrooms,A_structural,level,count,0.073,0.026,,0.005,,,,high,,"ln(monthly rent, THB)",log,OLS,4422.0,0.703,se,Phuket and Pattaya only (Phuket reference); Model 3 covariates + floor level; adj. R2 0.703; only listed coefficients printed,semi_elasticity,7.3,2.6,100*b/1 (per unit count),reported,0.042232240179363716,0.015041619789910365,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8076923076923075,4412.0,count,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4,41a24683a4b966679145f8c822178e61a9a339a4:T8-PKT,8,Phuket & Pattaya (+ floor level),12,Bedrooms,bedrooms,A_structural,level,count,0.157,0.014,,0.0,,,,high,,"ln(monthly rent, THB)",log,OLS,4422.0,0.703,se,Phuket and Pattaya only (Phuket reference); Model 3 covariates + floor level; adj. R2 0.703; only listed coefficients printed,semi_elasticity,15.7,1.4000000000000001,100*b/1 (per unit count),reported,0.16647569846862992,0.014844966742425598,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.214285714285714,4412.0,count,,2026.0,Thailand,Asia,Upper middle income,2026.0,2026.0,condo_apartment,rent,journal,False,True,robust,,2026.0,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,Living Area [log],living_area,A_structural,log,m2,0.8,0.01,81.98,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",elasticity,0.8,0.01,b (log-log),reported,0.6487838848011535,0.007913928821677891,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),81.98,9246.0,m2,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,Rooms,bedrooms,A_structural,level,count,0.04,0.0,10.05,0.0,***,,,high,Number of rooms,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",semi_elasticity,4.0,0.3980099502487562,100*b/1 (per unit count),|b/t|,0.10395128980496335,0.010343411920891875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.05,9246.0,count,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,Bathtub,bathroom_quality,B_interior,binary,binary,-0.04,0.0,-9.78,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",pct_premium,-3.92185968246187,0.39296091580872117,100*(exp(b - se^2/2) - 1),|b/t|,-0.10118755359441099,0.01034637562315041,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.78,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,Refurbished,renovation,A_structural,binary,binary,0.02,0.01,3.03,0.0,**,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",pct_premium,2.0150331234984886,1.0202013400267558,100*(exp(b - se^2/2) - 1),reported,0.03149562077022479,0.010394594313605541,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.03,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,Built-in kitchen,kitchen_quality,B_interior,binary,binary,0.11,0.01,21.65,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",pct_premium,11.622225795067266,1.1162780704588713,100*(exp(b - se^2/2) - 1),reported,0.21965581297032855,0.010145765033271527,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.65,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,Balcony,terrace_balcony,C_exterior,binary,binary,0.02,0.0,3.84,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",pct_premium,2.0187502754330566,0.5313548645972687,100*(exp(b - se^2/2) - 1),|b/t|,0.0399032480044534,0.010391470834493073,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.84,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,Parking,parking,A_structural,binary,binary,0.03,0.01,4.88,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",pct_premium,3.040301251486577,1.030454533953517,100*(exp(b - se^2/2) - 1),reported,0.05068556623675214,0.01038638652392462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.88,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,Elevator,accessibility,B_interior,binary,binary,0.04,0.01,7.64,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",pct_premium,4.075873495467031,1.0408107741923882,100*(exp(b - se^2/2) - 1),reported,0.07920450456558127,0.010367081749421633,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.64,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,Terrace,terrace_balcony,C_exterior,binary,binary,0.04,0.01,5.99,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",pct_premium,4.075873495467031,1.0408107741923882,100*(exp(b - se^2/2) - 1),reported,0.06217400522651872,0.010379633593742691,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.99,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,NUTS centroid [km],cbd_distance,D_location,level,km,-0.02,0.0,-13.02,0.0,***,,,high,Distance to NUTS-3 centroid (city centre proxy),"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",semi_elasticity,-2.0,0.15360983102918588,100*b/1 (X per km->km),|b/t|,-0.13418031895913196,0.010305708061377263,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.02,9246.0,km,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,School [km],school_distance,D_location,level,km,-0.03,0.01,-2.35,0.02,*,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",semi_elasticity,-3.0,1.0,100*b/1 (X per km->km),reported,-0.024432125895573968,0.010396649317265519,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.35,9246.0,km,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,Supermarket [km],commercial_distance,D_location,level,km,0.02,0.01,1.2,0.23,,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",semi_elasticity,2.0,1.0,100*b/1 (X per km->km),reported,0.012478732784139274,0.010398943986782727,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2,9246.0,km,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-A,6,Panel A,32,Bus station [km],transit_distance,D_location,level,km,-0.04,0.0,-17.16,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,"OLS including spatial controls (coordinates, distances); SE/t/p printed in columns",semi_elasticity,-4.0,0.2331002331002331,100*b/1 (X per km->km),|b/t|,-0.17568411633240608,0.01023800211727308,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.16,9246.0,km,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-B,6,Panel B,32,Living Area [log],living_area,A_structural,log,m2,0.84,0.01,76.62,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,OLS excluding spatial controls; continued on page 33,elasticity,0.84,0.01,b (log-log),reported,0.6231817643615948,0.008133408566452555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),76.62,9246.0,m2,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-B,6,Panel B,33,Rooms,bedrooms,A_structural,level,count,0.03,0.0,6.32,0.0,***,,,high,Number of rooms,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,OLS excluding spatial controls; continued on page 33,semi_elasticity,3.0,0.4746835443037974,100*b/1 (per unit count),|b/t|,0.0655849339583329,0.010377362968090649,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.32,9246.0,count,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-B,6,Panel B,33,Floor,floor_level,A_structural,level,count,0.01,0.0,6.43,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,OLS excluding spatial controls; continued on page 33,semi_elasticity,1.0,0.15552099533437014,100*b/1 (per unit count),|b/t|,0.06672140544962463,0.010376579385633692,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.43,9246.0,count,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-B,6,Panel B,33,Bathtub,bathroom_quality,B_interior,binary,binary,-0.05,0.0,-10.78,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,OLS excluding spatial controls; continued on page 33,pct_premium,-4.878080737913026,0.4412010317721308,100*(exp(b - se^2/2) - 1),|b/t|,-0.11141139413611181,0.010335008732477904,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.78,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-B,6,Panel B,33,Refurbished,renovation,A_structural,binary,binary,0.03,0.01,4.53,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,OLS excluding spatial controls; continued on page 33,pct_premium,3.040301251486577,1.030454533953517,100*(exp(b - se^2/2) - 1),reported,0.047058691507471474,0.010388232120854629,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.53,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-B,6,Panel B,33,Built-in kitchen,kitchen_quality,B_interior,binary,binary,0.15,0.01,26.57,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,OLS excluding spatial controls; continued on page 33,pct_premium,16.177615246841537,1.161834242728283,100*(exp(b - se^2/2) - 1),reported,0.26634045455171157,0.010024104424227007,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.57,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,True
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-B,6,Panel B,33,Balcony,terrace_balcony,C_exterior,binary,binary,0.02,0.01,2.94,0.0,**,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,OLS excluding spatial controls; continued on page 33,pct_premium,2.0150331234984886,1.0202013400267558,100*(exp(b - se^2/2) - 1),reported,0.030560994388410576,0.010394896050479788,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.94,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-B,6,Panel B,33,Parking,parking,A_structural,binary,binary,0.01,0.01,1.52,0.13,,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,OLS excluding spatial controls; continued on page 33,pct_premium,0.9999665838355432,1.010050167084168,100*(exp(b - se^2/2) - 1),reported,0.01580565103702695,0.010398454629622996,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.52,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-B,6,Panel B,33,Elevator,accessibility,B_interior,binary,binary,0.1,0.01,16.78,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,OLS excluding spatial controls; continued on page 33,pct_premium,10.511566091118452,1.1051709180756477,100*(exp(b - se^2/2) - 1),reported,0.1719099123255177,0.010244929220829422,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.78,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d,41c05e4c190bfd812f576bb4bc53a0c147331a7d:T6-B,6,Panel B,33,Terrace,terrace_balcony,C_exterior,binary,binary,0.03,0.01,4.06,0.0,***,,,high,,"log(rent) (monthly asking rent, EUR)",log,OLS,9256.0,,se,OLS excluding spatial controls; continued on page 33,pct_premium,3.040301251486577,1.030454533953517,100*(exp(b - se^2/2) - 1),reported,0.04218541322379711,0.010390495867930323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.06,9246.0,binary,,2022.0,Germany,Europe,High income,2019.0,2020.0,rental,rent,journal,False,False,unknown,random_forest;gradient_boosting,2019.5,ols,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,lnHousesize,living_area,A_structural,log,m2,0.82,0.01,,,***,,,high,"ln heated area (m2). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.82,0.01,b (log-log),reported,0.6159149282747173,0.007511157661886797,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),82.0,11001.0,m2,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,lnHousesize,living_area,A_structural,log,m2,0.75,0.02,,,***,,,high,"ln heated area (m2). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.75,0.02,b (log-log),reported,0.3366615364826964,0.008977640972871905,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.5,11001.0,m2,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,lnHousesize,living_area,A_structural,log,m2,0.75,0.02,,,***,,,high,"ln heated area (m2). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.75,0.02,b (log-log),reported,0.3366615364826964,0.008977640972871905,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.5,11001.0,m2,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,lnParcelsize,lot_size,A_structural,log,m2,0.13,0.01,,,***,,,high,"ln parcel size (m2). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.13,0.01,b (log-log),reported,0.1230033007541626,0.009461792365704816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,11001.0,m2,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,lnParcelsize,lot_size,A_structural,log,m2,0.13,0.01,,,***,,,high,"ln parcel size (m2). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.13,0.01,b (log-log),reported,0.1230033007541626,0.009461792365704816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,11001.0,m2,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,lnParcelsize,lot_size,A_structural,log,m2,0.1,0.01,,,***,,,high,"ln parcel size (m2). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.1,0.01,b (log-log),reported,0.09491152437764508,0.009491152437764508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.0,11001.0,m2,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,Beds,bedrooms,A_structural,level,count,-0.01,0.008,,,,,,high,"Number of bedrooms. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",semi_elasticity,-1.0,0.8,100*b/1 (per unit count),reported,-0.011916894399039497,0.009533515519231596,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.25,11001.0,count,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,Beds,bedrooms,A_structural,level,count,0.001,0.009,,,,,,high,"Number of bedrooms. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",semi_elasticity,0.1,0.8999999999999999,100*b/1 (per unit count),reported,0.0010593541311257313,0.009534187180131581,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.11111111111111112,11001.0,count,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,Beds,bedrooms,A_structural,level,count,0.002,0.008,,,,,,high,"Number of bedrooms. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",semi_elasticity,0.2,0.8,100*b/1 (per unit count),reported,0.002383541361680103,0.009534165446720411,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.25,11001.0,count,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,Age,age,A_structural,level,years,-0.007,0.0007,,,***,,,high,"Age of house (years), quadratic. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",semi_elasticity,-0.7000000000000001,0.06999999999999999,100*b/1 (per year),reported,-0.09491152437764508,0.009491152437764508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.0,11001.0,years,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,Age,age,A_structural,level,years,-0.007,0.0007,,,***,,,high,"Age of house (years), quadratic. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",semi_elasticity,-0.7000000000000001,0.06999999999999999,100*b/1 (per year),reported,-0.09491152437764508,0.009491152437764508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.0,11001.0,years,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,Age,age,A_structural,level,years,-0.008,0.0007,,,***,,,high,"Age of house (years), quadratic. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",semi_elasticity,-0.8,0.06999999999999999,100*b/1 (per year),reported,-0.10832106269528104,0.00947809298583709,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.428571428571429,11001.0,years,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,Fireplace,fireplace,B_interior,binary,binary,0.04,0.01,,,***,,,high,"Presence of a fireplace. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,4.075873495467031,1.0408107741923882,100*(exp(b - se^2/2) - 1),reported,0.03810906702321704,0.00952726675580426,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,Fireplace,fireplace,B_interior,binary,binary,0.034,0.01,,,***,,,high,"Presence of a fireplace. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,3.453287879099065,1.034584606728118,100*(exp(b - se^2/2) - 1),reported,0.03239923629285777,0.009529187144958167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4000000000000004,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,Fireplace,fireplace,B_interior,binary,binary,0.04,0.01,,,***,,,high,"Presence of a fireplace. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,4.075873495467031,1.0408107741923882,100*(exp(b - se^2/2) - 1),reported,0.03810906702321704,0.00952726675580426,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,Brick,roof_materials,A_structural,binary,binary,-0.013,0.01,,,,,,high,"Masonry exterior dummy. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,-1.2965217952628838,0.9870841350202877,100*(exp(b - se^2/2) - 1),reported,-0.012393498365980955,0.009533460281523812,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2999999999999998,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,Brick,roof_materials,A_structural,binary,binary,0.01,0.01,,,,,,high,"Masonry exterior dummy. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,0.9999665838355432,1.010050167084168,100*(exp(b - se^2/2) - 1),reported,0.009533759226463817,0.009533759226463817,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,Brick,roof_materials,A_structural,binary,binary,0.01,0.01,,,,,,high,"Masonry exterior dummy. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,0.9999665838355432,1.010050167084168,100*(exp(b - se^2/2) - 1),reported,0.009533759226463817,0.009533759226463817,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,Garage,garage,A_structural,binary,binary,0.07,0.01,,,***,,,high,"Presence of a garage. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,7.2454557185766655,1.0725081812542165,100*(exp(b - se^2/2) - 1),reported,0.06659120918162918,0.009513029883089882,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.000000000000001,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,Garage,garage,A_structural,binary,binary,0.09,0.01,,,***,,,high,"Presence of a garage. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,9.411957635872014,1.0941742837052104,100*(exp(b - se^2/2) - 1),reported,0.08549356685113257,0.009499285205681397,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,Garage,garage,A_structural,binary,binary,0.1,0.01,,,***,,,high,"Presence of a garage. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,10.511566091118452,1.1051709180756477,100*(exp(b - se^2/2) - 1),reported,0.09491152437764508,0.009491152437764508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,Deck,terrace_balcony,C_exterior,binary,binary,0.06,0.01,,,***,,,high,"Presence of a deck. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,6.1783456045305885,1.0618365465453596,100*(exp(b - se^2/2) - 1),reported,0.05711178435255364,0.009518630725425605,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,Deck,terrace_balcony,C_exterior,binary,binary,0.04,0.01,,,***,,,high,"Presence of a deck. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,4.075873495467031,1.0408107741923882,100*(exp(b - se^2/2) - 1),reported,0.03810906702321704,0.00952726675580426,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,Deck,terrace_balcony,C_exterior,binary,binary,0.04,0.01,,,***,,,high,"Presence of a deck. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,4.075873495467031,1.0408107741923882,100*(exp(b - se^2/2) - 1),reported,0.03810906702321704,0.00952726675580426,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,Pool,pool,C_exterior,binary,binary,0.1,0.02,,,***,,,high,"Presence of a pool. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,10.494990599397735,2.2103418361512954,100*(exp(b - se^2/2) - 1),reported,0.04761688817195134,0.009523377634390269,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,Pool,pool,C_exterior,binary,binary,0.1,0.02,,,***,,,high,"Presence of a pool. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,10.494990599397735,2.2103418361512954,100*(exp(b - se^2/2) - 1),reported,0.04761688817195134,0.009523377634390269,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,Pool,pool,C_exterior,binary,binary,0.1,0.02,,,***,,,high,"Presence of a pool. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,10.494990599397735,2.2103418361512954,100*(exp(b - se^2/2) - 1),reported,0.04761688817195134,0.009523377634390269,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,lnCommonspace,green_space,E_environment,log,share,0.07,0.005,,,***,,,high,"ln percent of neighbourhood (subdivision) area set aside as common/open space by developer. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.07,0.005,b (log-log),reported,0.13230528619793228,0.00945037758556659,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.000000000000002,11001.0,share,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,lnCommonspace,green_space,E_environment,log,share,0.06,0.005,,,***,,,high,"ln percent of neighbourhood (subdivision) area set aside as common/open space by developer. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.06,0.005,b (log-log),reported,0.11366878284651809,0.009472398570543173,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,11001.0,share,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,lnCommonspace,green_space,E_environment,log,share,0.04,0.006,,,***,,,high,"ln percent of neighbourhood (subdivision) area set aside as common/open space by developer. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.04,0.006,b (log-log),reported,0.06343327630675547,0.009514991446013319,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.666666666666667,11001.0,share,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,lnMajorroads,highway_distance,D_location,log,m,0.02,0.005,,,***,,,high,"ln distance to nearest major road (metres; unit per Table 1/2 distances in meters). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.02,0.005,b (log-log),reported,0.03810906702321704,0.00952726675580426,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,11001.0,m,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,lnMajorroads,highway_distance,D_location,log,m,0.008,0.005,,,,,,high,"ln distance to nearest major road (metres; unit per Table 1/2 distances in meters). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.008,0.005,b (log-log),reported,0.015252933425642814,0.009533083391026759,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6,11001.0,m,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,lnMajorroads,highway_distance,D_location,log,m,0.002,0.005,,,,,,high,"ln distance to nearest major road (metres; unit per Table 1/2 distances in meters). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.002,0.005,b (log-log),reported,0.00381364927895776,0.0095341231973944,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4,11001.0,m,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,lnSchool,school_distance,D_location,log,m,0.03,0.008,,,***,,,high,"ln distance to nearest school (metres). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.03,0.008,b (log-log),reported,0.03573039232750708,0.009528104620668556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.75,11001.0,m,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,lnSchool,school_distance,D_location,log,m,0.04,0.009,,,***,,,high,"ln distance to nearest school (metres). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.04,0.009,b (log-log),reported,0.04233619722551051,0.009525644375739864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.444444444444445,11001.0,m,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,lnSchool,school_distance,D_location,log,m,0.04,0.008,,,***,,,high,"ln distance to nearest school (metres). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.04,0.008,b (log-log),reported,0.04761688817195134,0.009523377634390269,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,11001.0,m,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,SFHA,flood_risk,E_environment,binary,binary,0.03,0.01,,,*,,,high,"Property inside FEMA special flood hazard area. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,3.040301251486577,1.030454533953517,100*(exp(b - se^2/2) - 1),reported,0.028590884772914823,0.009530294924304942,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,SFHA,flood_risk,E_environment,binary,binary,0.009,0.015,,,,,,high,"Property inside FEMA special flood hazard area. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,0.8927111089013895,1.5135609326608017,100*(exp(b - se^2/2) - 1),reported,0.005720421920320792,0.009534036533867985,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,SFHA,flood_risk,E_environment,binary,binary,-0.0004,0.015,,,,,,high,"Property inside FEMA special flood hazard area. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,-0.051236869430737464,1.4994001199840017,100*(exp(b - se^2/2) - 1),reported,-0.0002542451259138462,0.009534192221769234,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.02666666666666667,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,lnNonwhite,demographics,F_neighbourhood,log,share,-0.09,0.006,,,***,,,high,"ln percent nonwhite at census block group (2010). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,-0.09,0.006,b (log-log),reported,-0.14157244747296263,0.009438163164864177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.0,11001.0,share,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,lnNonwhite,demographics,F_neighbourhood,log,share,-0.0861,0.006,,,***,,,high,"ln percent nonwhite at census block group (2010). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,-0.0861,0.006,b (log-log),reported,-0.13555286987999182,0.009446193022995947,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.35,11001.0,share,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,lnNonwhite,demographics,F_neighbourhood,log,share,-0.086,0.006,,,***,,,high,"ln percent nonwhite at census block group (2010). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,-0.086,0.006,b (log-log),reported,-0.13539832121475104,0.009446394503354726,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.333333333333332,11001.0,share,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c1,3,1,13,lnIncome,income,F_neighbourhood,log,currency,0.26,0.02,,,***,,,high,"ln median household income at block group (2010 Census, USD). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 1: structural + neighbourhood/location variables; SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.26,0.02,b (log-log),reported,0.1230033007541626,0.009461792365704816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,11001.0,currency,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,lnIncome,income,F_neighbourhood,log,currency,0.25,0.019,,,***,,,high,"ln median household income at block group (2010 Census, USD). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.25,0.019,b (log-log),reported,0.12447425743690374,0.009460043565204683,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.157894736842106,11001.0,currency,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,lnIncome,income,F_neighbourhood,log,currency,0.27,0.0189,,,***,,,high,"ln median household income at block group (2010 Census, USD). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,0.27,0.0189,b (log-log),reported,0.13495669917306982,0.009446968942114888,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.285714285714286,11001.0,currency,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,lnPark,green_space,E_environment,log,m,-0.09,0.008,,,***,,,high,"ln distance to nearest park (metres). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,-0.09,0.008,b (log-log),reported,-0.10664794742536449,0.009479817548921287,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.25,11001.0,m,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,True
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,lnPark,green_space,E_environment,log,m,-0.08,0.008,,,***,,,high,"ln distance to nearest park (metres). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,-0.08,0.008,b (log-log),reported,-0.09491152437764508,0.009491152437764508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.0,11001.0,m,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,lnMarsh,water_proximity,E_environment,log,m,-0.07,0.005,,,***,,,high,"ln distance to nearest marsh or lake (metres). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,-0.07,0.005,b (log-log),reported,-0.13230528619793228,0.00945037758556659,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.000000000000002,11001.0,m,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,lnMarsh,water_proximity,E_environment,log,m,-0.04,0.006,,,***,,,high,"ln distance to nearest marsh or lake (metres). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",elasticity,-0.04,0.006,b (log-log),reported,-0.06343327630675547,0.009514991446013319,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.666666666666667,11001.0,m,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c2,3,2,13,Waterview,view,E_environment,binary,binary,0.1,0.02,,,***,,,high,"Property has view (no access) of marsh. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 2: + environmental amenity proximity (park, marsh, water view); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,10.494990599397735,2.2103418361512954,100*(exp(b - se^2/2) - 1),reported,0.04761688817195134,0.009523377634390269,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,Waterview,view,E_environment,binary,binary,0.17,0.02,,,***,,,high,"Property has view (no access) of marsh. Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,18.506781405461826,2.370609702640731,100*(exp(b - se^2/2) - 1),reported,0.08077581957363356,0.009503037596898066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.5,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,Wateraccess,waterfront,C_exterior,binary,binary,0.38,0.06,,,***,,,high,"Property has navigable water access to marsh (no dock). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,45.96548446535766,8.773707536605347,100*(exp(b - se^2/2) - 1),reported,0.0602734368465292,0.009516858449451977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.333333333333334,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd,467b5db9559e6802d7f96e2e470749e1440b69fd:T3-c3,3,3,13,Dock,waterfront,C_exterior,binary,binary,0.51,0.03,,,***,,,high,"Presence of a boat dock (water access with dock). Heteroskedasticity-consistent standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; N=11,011.","lnPrice (sale price, 2011 USD)",log,SAC,11011.0,,se,"Model 3: + marsh accessibility (water access, dock); SARAR (spatial lag + spatial error), inverse-distance weights truncated at 200 m, generalized 2SLS; sale-year dummies included (not extracted)",pct_premium,66.45419824936054,4.995873584837659,100*(exp(b - se^2/2) - 1),reported,0.1599933568151436,0.009411373930302565,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.0,11001.0,binary,,2016.0,United States,North America,High income,2005.0,2011.0,single_family,transaction,journal,True,False,robust,,2008.0,spatial,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G1,2,Geneva Model 1,18,Building was renovated before 1990,renovation,A_structural,binary,binary,0.0234,0.0059,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6285,se,Geneva; Model 1: traditional characteristics only,pct_premium,2.3658111110800295,0.6039687975408125,100*(exp(b - se^2/2) - 1),reported,0.019314067049724593,0.004869786136469022,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9661016949152543,42152.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2,2,Geneva Model 2,18,Building was renovated before 1990,renovation,A_structural,binary,binary,0.0179,0.0062,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6318,se,Geneva; Model 2: + household head nationality + share of foreigners per hectare,pct_premium,1.8041598235244205,0.6311979224133359,100*(exp(b - se^2/2) - 1),reported,0.014060776765536607,0.0048702131813590475,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8870967741935485,42152.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2fix,2,Geneva Model 2-fix,18,Building was renovated before 1990,renovation,A_structural,binary,binary,0.0169,0.0062,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6417,se,Geneva; Model 2 + district fixed effects,pct_premium,1.702406548817681,0.6305670399847105,100*(exp(b - se^2/2) - 1),reported,0.013275401042286646,0.004870265471134746,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.725806451612903,42152.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z1,2,Zurich Model 1,18,Building was renovated before 1990,renovation,A_structural,binary,binary,0.0096,0.0042,,,**,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6689,se,Zurich; Model 1: traditional characteristics only,pct_premium,0.9637322770116974,0.4240514156804414,100*(exp(b - se^2/2) - 1),reported,0.014045212437716769,0.006144780441501086,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2857142857142856,26479.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2,2,Zurich Model 2,18,Building was renovated before 1990,renovation,A_structural,binary,binary,0.0095,0.0042,,,**,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6696,se,Zurich; Model 2: + household head nationality + share of foreigners per hectare,pct_premium,0.953636408585834,0.4240090126590598,100*(exp(b - se^2/2) - 1),reported,0.013898936553342746,0.006144793002530477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.261904761904762,26479.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2fix,2,Zurich Model 2-fix,18,Building was renovated before 1990,renovation,A_structural,binary,binary,0.0084,0.0041,,,**,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6769,se,Zurich; Model 2 + district fixed effects,pct_premium,0.842690312805483,0.4134585053866362,100*(exp(b - se^2/2) - 1),reported,0.01258955036752259,0.006144899584147933,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0487804878048776,26479.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G1,2,Geneva Model 1,18,Floor level,floor_level,A_structural,level,count,0.0188,0.0006,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6285,se,Geneva; Model 1: traditional characteristics only,semi_elasticity,1.8800000000000001,0.06,100*b/1 (per unit count),reported,0.1508682492520164,0.004814944125064354,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),31.333333333333336,42152.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2,2,Geneva Model 2,18,Floor level,floor_level,A_structural,level,count,0.0194,0.0007,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6318,se,Geneva; Model 2: + household head nationality + share of foreigners per hectare,semi_elasticity,1.94,0.06999999999999999,100*b/1 (per unit count),reported,0.13377452582668398,0.0048269158803442664,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.714285714285715,42152.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2fix,2,Geneva Model 2-fix,18,Floor level,floor_level,A_structural,level,count,0.0196,0.0006,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6417,se,Geneva; Model 2 + district fixed effects,semi_elasticity,1.96,0.06,100*b/1 (per unit count),reported,0.15713282037728166,0.004810188378896377,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.66666666666667,42152.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z1,2,Zurich Model 1,18,Floor level,floor_level,A_structural,level,count,0.0108,0.0008,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6689,se,Zurich; Model 1: traditional characteristics only,semi_elasticity,1.08,0.08,100*b/1 (per unit count),reported,0.08267867629844998,0.006124346392477777,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.5,26479.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2,2,Zurich Model 2,18,Floor level,floor_level,A_structural,level,count,0.0111,0.0008,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6696,se,Zurich; Model 2: + household head nationality + share of foreigners per hectare,semi_elasticity,1.11,0.08,100*b/1 (per unit count),reported,0.08495895150859989,0.006123167676295488,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.875,26479.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2fix,2,Zurich Model 2-fix,18,Floor level,floor_level,A_structural,level,count,0.0113,0.0008,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6769,se,Zurich; Model 2 + district fixed effects,semi_elasticity,1.13,0.08,100*b/1 (per unit count),reported,0.08647839594621536,0.00612236431477631,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.124999999999998,26479.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G1,2,Geneva Model 1,18,Number of floors in the building,storeys,A_structural,level,count,-0.0058,0.0007,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6285,se,Geneva; Model 1: traditional characteristics only,semi_elasticity,-0.58,0.06999999999999999,100*b/1 (per unit count),reported,-0.040324359716418734,0.004866733069222952,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.285714285714285,42152.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2,2,Geneva Model 2,18,Number of floors in the building,storeys,A_structural,level,count,-0.0068,0.0007,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6318,se,Geneva; Model 2: + household head nationality + share of foreigners per hectare,semi_elasticity,-0.6799999999999999,0.06999999999999999,100*b/1 (per unit count),reported,-0.04726244523784824,0.004865251715660848,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.714285714285714,42152.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2fix,2,Geneva Model 2-fix,18,Number of floors in the building,storeys,A_structural,level,count,-0.0065,0.0007,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6417,se,Geneva; Model 2 + district fixed effects,semi_elasticity,-0.65,0.06999999999999999,100*b/1 (per unit count),reported,-0.04518169188550023,0.004865720664592333,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.285714285714285,42152.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z1,2,Zurich Model 1,18,Number of floors in the building,storeys,A_structural,level,count,0.0005,0.0006,,,,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6689,se,Zurich; Model 1: traditional characteristics only,semi_elasticity,0.05,0.06,100*b/1 (per unit count),reported,0.005121088359874486,0.006145306031849384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8333333333333334,26479.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2,2,Zurich Model 2,18,Number of floors in the building,storeys,A_structural,level,count,0.0004,0.0006,,,,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6696,se,Zurich; Model 2: + household head nationality + share of foreigners per hectare,semi_elasticity,0.04,0.06,100*b/1 (per unit count),reported,0.0040968900277172475,0.006145335041575871,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6666666666666667,26479.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2fix,2,Zurich Model 2-fix,18,Number of floors in the building,storeys,A_structural,level,count,0.0019,0.0006,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6769,se,Zurich; Model 2 + district fixed effects,semi_elasticity,0.19,0.06,100*b/1 (per unit count),reported,0.01945670710382889,0.0061442232959459655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.166666666666667,26479.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G1,2,Geneva Model 1,18,Number of rooms,bedrooms,A_structural,level,count,0.2703,0.0014,,,***,,,medium,"Total number of rooms (Swiss definition), not bedrooms; parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6285,se,Geneva; Model 1: traditional characteristics only,semi_elasticity,27.029999999999998,0.13999999999999999,100*b/1 (per unit count),reported,0.685061593294019,0.0035482287481007277,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),193.07142857142856,42152.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2,2,Geneva Model 2,18,Number of rooms,bedrooms,A_structural,level,count,0.2677,0.0015,,,***,,,medium,"Total number of rooms (Swiss definition), not bedrooms; parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6318,se,Geneva; Model 2: + household head nationality + share of foreigners per hectare,semi_elasticity,26.77,0.15,100*b/1 (per unit count),reported,0.6560460926577897,0.003676014714182609,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),178.46666666666667,42152.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2fix,2,Geneva Model 2-fix,18,Number of rooms,bedrooms,A_structural,level,count,0.2639,0.0016,,,***,,,medium,"Total number of rooms (Swiss definition), not bedrooms; parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6417,se,Geneva; Model 2 + district fixed effects,semi_elasticity,26.39,0.16,100*b/1 (per unit count),reported,0.6262910454054376,0.0037971416167059497,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),164.9375,42152.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z1,2,Zurich Model 1,18,Number of rooms,bedrooms,A_structural,level,count,0.275,0.0016,,,***,,,medium,"Total number of rooms (Swiss definition), not bedrooms; parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6689,se,Zurich; Model 1: traditional characteristics only,semi_elasticity,27.500000000000004,0.16,100*b/1 (per unit count),reported,0.7261746738946244,0.004225016284477814,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),171.875,26479.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2,2,Zurich Model 2,18,Number of rooms,bedrooms,A_structural,level,count,0.2745,0.0016,,,***,,,medium,"Total number of rooms (Swiss definition), not bedrooms; parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6696,se,Zurich; Model 2: + household head nationality + share of foreigners per hectare,semi_elasticity,27.450000000000003,0.16,100*b/1 (per unit count),reported,0.7255497005092894,0.004229069292586022,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),171.5625,26479.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2fix,2,Zurich Model 2-fix,18,Number of rooms,bedrooms,A_structural,level,count,0.2728,0.0016,,,***,,,medium,"Total number of rooms (Swiss definition), not bedrooms; parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6769,se,Zurich; Model 2 + district fixed effects,semi_elasticity,27.279999999999998,0.16,100*b/1 (per unit count),reported,0.7234112919096157,0.004242881477475752,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),170.49999999999997,26479.0,count,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G1,2,Geneva Model 1,19,Kitchenette,kitchen_quality,B_interior,binary,binary,-0.0755,0.0072,,,***,,,medium,"Dummy: kitchenette instead of full kitchen; parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6285,se,Geneva; Model 1: traditional characteristics only,pct_premium,-7.274430424512457,0.6676414059844791,100*(exp(b - se^2/2) - 1),reported,-0.05100815856670383,0.00486435419444063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.48611111111111,42152.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2,2,Geneva Model 2,19,Kitchenette,kitchen_quality,B_interior,binary,binary,-0.0792,0.0071,,,***,,,medium,"Dummy: kitchenette instead of full kitchen; parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6318,se,Geneva; Model 2: + household head nationality + share of foreigners per hectare,pct_premium,-7.616815053545545,0.6559371458072326,100*(exp(b - se^2/2) - 1),reported,-0.054252239087269116,0.004863521433328418,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.15492957746479,42152.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2fix,2,Geneva Model 2-fix,19,Kitchenette,kitchen_quality,B_interior,binary,binary,-0.0791,0.0071,,,***,,,medium,"Dummy: kitchenette instead of full kitchen; parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6417,se,Geneva; Model 2 + district fixed effects,pct_premium,-7.607576273119577,0.6560027428016084,100*(exp(b - se^2/2) - 1),reported,-0.054183940022133635,0.004863539496297709,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.140845070422536,42152.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z1,2,Zurich Model 1,19,Kitchenette,kitchen_quality,B_interior,binary,binary,-0.0761,0.0076,,,***,,,medium,"Dummy: kitchenette instead of full kitchen; parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6689,se,Zurich; Model 1: traditional characteristics only,pct_premium,-7.330323381641602,0.7043098824752162,100*(exp(b - se^2/2) - 1),reported,-0.06141855499993812,0.006133784730611429,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.013157894736842,26479.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2,2,Zurich Model 2,19,Kitchenette,kitchen_quality,B_interior,binary,binary,-0.078,0.0075,,,***,,,medium,"Dummy: kitchenette instead of full kitchen; parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6696,se,Zurich; Model 2: + household head nationality + share of foreigners per hectare,pct_premium,-7.506158771513006,0.6937233199076545,100*(exp(b - se^2/2) - 1),reported,-0.06378188713884317,0.0061328737633503045,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.4,26479.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2fix,2,Zurich Model 2-fix,19,Kitchenette,kitchen_quality,B_interior,binary,binary,-0.0872,0.0076,,,***,,,medium,"Dummy: kitchenette instead of full kitchen; parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6769,se,Zurich; Model 2 + district fixed effects,pct_premium,-8.353268941177983,0.6965352716952224,100*(exp(b - se^2/2) - 1),reported,-0.07033559869299125,0.006130166858563458,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.473684210526315,26479.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,True
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G1,2,Geneva Model 1,19,Attic,storage,B_interior,binary,binary,0.0235,0.0073,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6285,se,Geneva; Model 1: traditional characteristics only,pct_premium,2.37510225372215,0.7473581595450394,100*(exp(b - se^2/2) - 1),reported,0.01567770650933915,0.0048700960646032255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.219178082191781,42152.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2,2,Geneva Model 2,19,Attic,storage,B_interior,binary,binary,0.0228,0.0079,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6318,se,Geneva; Model 2: + household head nationality + share of foreigners per hectare,pct_premium,2.3029982554575,0.8082189062955869,100*(exp(b - se^2/2) - 1),reported,0.014055806113408979,0.004870213521751357,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8860759493670884,42152.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2fix,2,Geneva Model 2-fix,19,Attic,storage,B_interior,binary,binary,0.0252,0.0077,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6417,se,Geneva; Model 2 + district fixed effects,pct_premium,2.5489802960376506,0.7896505571232766,100*(exp(b - se^2/2) - 1),reported,0.015938430503949257,0.00487007598731783,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2727272727272725,42152.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z1,2,Zurich Model 1,19,Attic,storage,B_interior,binary,binary,0.0316,0.0061,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6689,se,Zurich; Model 1: traditional characteristics only,pct_premium,3.2085378766285144,0.6295837943449646,100*(exp(b - se^2/2) - 1),reported,0.031818997757287214,0.006142274883526961,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.180327868852459,26479.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2,2,Zurich Model 2,19,Attic,storage,B_interior,binary,binary,0.0313,0.0061,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6696,se,Zurich; Model 2: + household head nationality + share of foreigners per hectare,pct_premium,3.177579959185328,0.6293949475350988,100*(exp(b - se^2/2) - 1),reported,0.031517220167013485,0.006142333642772596,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.131147540983607,26479.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2fix,2,Zurich Model 2-fix,19,Attic,storage,B_interior,binary,binary,0.0345,0.0061,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6769,se,Zurich; Model 2 + district fixed effects,pct_premium,3.5082770482023573,0.6314122373094297,100*(exp(b - se^2/2) - 1),reported,0.03473572026633023,0.0061416780760757805,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.655737704918033,26479.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G1,2,Geneva Model 1,19,Gas heating,heating,A_structural,binary,binary,0.0169,0.0035,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6285,se,Geneva; Model 1: traditional characteristics only,pct_premium,1.703738350551398,0.3559652645074979,100*(exp(b - se^2/2) - 1),reported,0.023511995625745304,0.0048693482065153,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.828571428571428,42152.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2,2,Geneva Model 2,19,Gas heating,heating,A_structural,binary,binary,0.0246,0.0037,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6318,se,Geneva; Model 2: + household head nationality + share of foreigners per hectare,pct_premium,2.489806103925485,0.3792148783014824,100*(exp(b - se^2/2) - 1),reported,0.03236657078666835,0.004868142760596461,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.648648648648648,42152.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2fix,2,Geneva Model 2-fix,19,Gas heating,heating,A_structural,binary,binary,0.0278,0.0036,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6417,se,Geneva; Model 2 + district fixed effects,pct_premium,2.818336320130288,0.3701484093063899,100*(exp(b - se^2/2) - 1),reported,0.03758600955339147,0.004867253035690982,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.722222222222222,42152.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z1,2,Zurich Model 1,19,Gas heating,heating,A_structural,binary,binary,0.0485,0.0035,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6689,se,Zurich; Model 1: traditional characteristics only,pct_premium,4.968894245586264,0.36739338013711376,100*(exp(b - se^2/2) - 1),reported,0.08485039695180883,0.006123224522295483,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.857142857142858,26479.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2,2,Zurich Model 2,19,Gas heating,heating,A_structural,binary,binary,0.0486,0.0035,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6696,se,Zurich; Model 2: + household head nationality + share of foreigners per hectare,pct_premium,4.9793916598728005,0.36743012131215563,100*(exp(b - se^2/2) - 1),reported,0.08502408279079719,0.006123133534316671,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.885714285714284,26479.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2fix,2,Zurich Model 2-fix,19,Gas heating,heating,A_structural,binary,binary,0.0513,0.0035,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6769,se,Zurich; Model 2 + district fixed effects,pct_premium,5.263219011854536,0.36842352312865917,100*(exp(b - se^2/2) - 1),reported,0.08971062051884364,0.006120607637737871,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.657142857142857,26479.0,binary,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G1,2,Geneva Model 1,19,Distance to nearest transportation stop [km],transit_distance,D_location,level,km,-0.1021,0.0226,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6285,se,Geneva; Model 1: traditional characteristics only,semi_elasticity,-10.209999999999999,2.26,100*b/1 (X per km->km),reported,-0.02199900786254038,0.0048695159421489964,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.517699115044248,42152.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2,2,Geneva Model 2,19,Distance to nearest transportation stop [km],transit_distance,D_location,level,km,-0.1261,0.0218,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6318,se,Geneva; Model 2: + household head nationality + share of foreigners per hectare,semi_elasticity,-12.61,2.18,100*b/1 (X per km->km),reported,-0.028162888897105966,0.004868762711791516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.78440366972477,42152.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2fix,2,Geneva Model 2-fix,19,Distance to nearest transportation stop [km],transit_distance,D_location,level,km,-0.1081,0.0223,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6417,se,Geneva; Model 2 + district fixed effects,semi_elasticity,-10.81,2.23,100*b/1 (X per km->km),reported,-0.023604277854210397,0.004869337614698352,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.8475336322869955,42152.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z1,2,Zurich Model 1,19,Distance to nearest transportation stop [km],transit_distance,D_location,level,km,-0.1521,0.0223,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6689,se,Zurich; Model 1: traditional characteristics only,semi_elasticity,-15.21,2.23,100*b/1 (X per km->km),reported,-0.041878622668869284,0.0061399953025363906,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.820627802690583,26479.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2,2,Zurich Model 2,19,Distance to nearest transportation stop [km],transit_distance,D_location,level,km,-0.1523,0.0223,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6696,se,Zurich; Model 2: + household head nationality + share of foreigners per hectare,semi_elasticity,-15.229999999999999,2.23,100*b/1 (X per km->km),reported,-0.04193359312313297,0.006139981133590711,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.829596412556053,26479.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,True
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2fix,2,Zurich Model 2-fix,19,Distance to nearest transportation stop [km],transit_distance,D_location,level,km,-0.0979,0.0219,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6769,se,Zurich; Model 2 + district fixed effects,semi_elasticity,-9.790000000000001,2.19,100*b/1 (X per km->km),reported,-0.027461481784902316,0.006143068959033307,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.470319634703197,26479.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G1,2,Geneva Model 1,19,Distance to nearest park [km],green_space,E_environment,level,km,0.1,0.0148,,,***,,,medium,"Distance to nearest park (km); parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6285,se,Geneva; Model 1: traditional characteristics only,semi_elasticity,10.0,1.48,100*b/1 (X per km->km),reported,0.03289229165078397,0.004868059164316028,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.756756756756757,42152.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2,2,Geneva Model 2,19,Distance to nearest park [km],green_space,E_environment,level,km,0.1266,0.0143,,,***,,,medium,"Distance to nearest park (km); parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6318,se,Geneva; Model 2: + household head nationality + share of foreigners per hectare,semi_elasticity,12.659999999999998,1.43,100*b/1 (X per km->km),reported,0.04308094118877341,0.004866172661923065,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.853146853146852,42152.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,True
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2fix,2,Geneva Model 2-fix,19,Distance to nearest park [km],green_space,E_environment,level,km,0.0064,0.0156,,,,,,medium,"Distance to nearest park (km); parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6417,se,Geneva; Model 2 + district fixed effects,semi_elasticity,0.64,1.5599999999999998,100*b/1 (X per km->km),reported,0.0019982297281737208,0.004870684962423444,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4102564102564103,42152.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z1,2,Zurich Model 1,19,Distance to nearest park [km],green_space,E_environment,level,km,0.0465,0.016,,,***,,,medium,"Distance to nearest park (km); parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6689,se,Zurich; Model 1: traditional characteristics only,semi_elasticity,4.65,1.6,100*b/1 (X per km->km),reported,0.017857182030285742,0.00614440672009832,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.90625,26479.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2,2,Zurich Model 2,19,Distance to nearest park [km],green_space,E_environment,level,km,0.0449,0.016,,,***,,,medium,"Distance to nearest park (km); parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6696,se,Zurich; Model 2: + household head nationality + share of foreigners per hectare,semi_elasticity,4.49,1.6,100*b/1 (X per km->km),reported,0.01724292729683752,0.0061444729788285146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.80625,26479.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2fix,2,Zurich Model 2-fix,19,Distance to nearest park [km],green_space,E_environment,level,km,0.0026,0.0162,,,,,,medium,"Distance to nearest park (km); parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6769,se,Zurich; Model 2 + district fixed effects,semi_elasticity,0.26,1.6199999999999999,100*b/1 (X per km->km),reported,0.0009862961375674553,0.006145383626381837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.16049382716049382,26479.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G1,2,Geneva Model 1,19,Distance to city centre [km],cbd_distance,D_location,level,km,-0.0117,0.0013,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6285,se,Geneva; Model 1: traditional characteristics only,semi_elasticity,-1.17,0.13,100*b/1 (X per km->km),reported,-0.0437941945397623,0.004866021615529145,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.0,42152.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2,2,Geneva Model 2,19,Distance to city centre [km],cbd_distance,D_location,level,km,-0.0106,0.0012,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6318,se,Geneva; Model 2: + household head nationality + share of foreigners per hectare,semi_elasticity,-1.06,0.12,100*b/1 (X per km->km),reported,-0.0429847035261324,0.004866192852014988,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.833333333333334,42152.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-G2fix,2,Geneva Model 2-fix,19,Distance to city centre [km],cbd_distance,D_location,level,km,0.0218,0.0036,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,42162.0,0.6417,se,Geneva; Model 2 + district fixed effects,semi_elasticity,2.18,0.36,100*b/1 (X per km->km),reported,0.029481941281776294,0.004868577459375902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.055555555555555,42152.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z1,2,Zurich Model 1,19,Distance to city centre [km],cbd_distance,D_location,level,km,-0.0392,0.0012,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6689,se,Zurich; Model 1: traditional characteristics only,semi_elasticity,-3.92,0.12,100*b/1 (X per km->km),reported,-0.19682246812858617,0.006025177595773045,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-32.66666666666667,26479.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2,2,Zurich Model 2,19,Distance to city centre [km],cbd_distance,D_location,level,km,-0.039,0.0012,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6696,se,Zurich; Model 2: + household head nationality + share of foreigners per hectare,semi_elasticity,-3.9,0.12,100*b/1 (X per km->km),reported,-0.19585688771545673,0.006026365775860207,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-32.5,26479.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9,4a0a05883004ee538ec38fa812f7d2e81fdd4eb9:T2-Z2fix,2,Zurich Model 2-fix,19,Distance to city centre [km],cbd_distance,D_location,level,km,-0.0416,0.0018,,,***,,,medium,"parentheses unlabelled (star legend only), consistent with standard errors","ln(net monthly rent, 2000, CHF)",log,OLS,26489.0,0.6769,se,Zurich; Model 2 + district fixed effects,semi_elasticity,-4.16,0.18,100*b/1 (X per km->km),reported,-0.14061557393540167,0.006084327718358725,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-23.11111111111111,26479.0,km,,2008.0,Switzerland,Europe,High income,2000.0,2000.0,rental,rent,journal,False,True,unknown,,2000.0,ols,journal,True,True,False
4e94c698b9b6217c36e2e8842148142f5bccfb36,4e94c698b9b6217c36e2e8842148142f5bccfb36,4e94c698b9b6217c36e2e8842148142f5bccfb36:T2-c1,2,"1 (b, unstandardized)",9,m2 (log),living_area,A_structural,log,m2,0.811,0.001,,,***,,,medium,Log of dwelling surface in m2; averaged beta,log of asking price,log,OLS,596170.0,0.768,se,"Average of four urban-level HI model betas, Alicante province, 2010 (4 quarters); Adj R2 0.768; SE column is an average of model SEs",elasticity,0.811,0.001,b (log-log),reported,0.7242569867126145,0.0008930419071672189,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),811.0,596160.0,m2,,2019.0,Spain,Europe,High income,2010.0,2010.0,unknown,listing,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,Terrace,dwelling_type,A_structural,binary,binary,-0.063,0.015,,0.0,,,,high,terrace house vs semi-detached (reference),"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,-6.116215151012794,1.4084152105336998,100*(exp(b - se^2/2) - 1),reported,-0.2921743548953888,0.06956532259414018,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.2,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,offroad,parking,A_structural,binary,binary,0.011,0.02,,0.585,,,,high,off-road parking vs on-road,"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,1.0858530520096998,2.022121444889439,100*(exp(b - se^2/2) - 1),reported,0.03997463571617019,0.07268115584758215,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5499999999999999,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,FVista2,view,E_environment,binary,binary,0.045,0.039,,0.253,,,,high,front vista = field (ref: houses),"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,4.523265813505684,4.079508653643996,100*(exp(b - se^2/2) - 1),reported,0.08363589914737059,0.07248444592772117,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1538461538461537,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,FVista3,view,E_environment,binary,binary,-0.132,0.075,,0.079,,,,high,front vista = countryside (ref: houses),"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,-12.612025121927662,6.572557463095299,100*(exp(b - se^2/2) - 1),reported,-0.12698478802203933,0.07215044773979506,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7600000000000002,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,RVista2,view,E_environment,binary,binary,0.069,0.051,,0.175,,,,high,rear vista = field (ref: houses),"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,7.004371202586368,5.464324666656566,100*(exp(b - se^2/2) - 1),reported,0.09793886745740699,0.0723895976859095,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3529411764705885,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,RVista3,view,E_environment,binary,binary,-0.004,0.036,,0.91,,,,high,rear vista = countryside (ref: houses),"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,-0.4637214764395381,3.585628761638369,100*(exp(b - se^2/2) - 1),reported,-0.00808188012866489,0.07273692115798401,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.11111111111111112,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,RVista4,view,E_environment,binary,binary,0.041,0.038,,0.281,,,,high,rear vista = sea (ref: houses),"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,4.110015981035087,3.959038001072822,100*(exp(b - se^2/2) - 1),reported,0.07824128285879837,0.07251631094230093,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0789473684210527,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,fWF1,hazard_site,E_environment,binary,binary,-0.024,0.065,,0.714,,,,high,partial/full view of 1 wind turbine from front of house (ref: no view),"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,-2.5774516923348645,6.345857113426411,100*(exp(b - se^2/2) - 1),reported,-0.026847905137068282,0.07271307641289326,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.36923076923076925,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,fWF3,hazard_site,E_environment,binary,binary,-0.007,0.032,,0.813,,,,high,view of up to 2 turbines from front of house (ref: no view),"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,-0.7483855446057674,3.1776782173863523,100*(exp(b - se^2/2) - 1),reported,-0.015909707257829475,0.07273009032150617,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.21875,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,FscreenV,hazard_site,E_environment,binary,binary,0.1,0.046,,0.033,,,,high,screened view of wind farm from front,"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,10.400226557051106,5.083786223147979,100*(exp(b - se^2/2) - 1),reported,0.15618823854259092,0.07184658972959182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.173913043478261,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,FsideV,hazard_site,E_environment,binary,binary,0.16,0.04,,0.0,,,,high,side view of wind farm from front,"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,17.257243771837594,4.694043483967241,100*(exp(b - se^2/2) - 1),reported,0.27937211830783126,0.06984302957695782,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,RfacingV,hazard_site,E_environment,binary,binary,-0.042,0.035,,0.233,,,,high,facing view of wind farm from rear of house,"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,-4.171734734183696,3.356044232003696,100*(exp(b - se^2/2) - 1),reported,-0.08695652173913043,0.07246376811594203,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,newH,age,A_structural,dummy,binary,-0.015,0.026,,0.56,,,,high,new-build dummy (not age in years),"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,-1.5220971967298325,2.5612910429679627,100*(exp(b - se^2/2) - 1),reported,-0.04192807621385372,0.07267533210401311,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.576923076923077,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T5-c1,5,1,13,Bed3&4,bedrooms,A_structural,dummy,binary,0.055,0.043,,0.204,,,,high,dummy for 3- or 4-bedroom house vs 2-bedroom; VIF 13.9,"ln(house price, GBP)",log,OLS,199.0,,se,"All independent variables (model with multicollinearity, VIF>10 for Bed3&4 and location dummies)",pct_premium,5.556429425088161,4.543124643104625,100*(exp(b - se^2/2) - 1),reported,0.09263855096638261,0.07242650348280823,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2790697674418605,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,Terrace,dwelling_type,A_structural,binary,binary,-0.073,0.017,,0.0,,,,high,terrace vs semi-detached,"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,-7.0533487589464645,1.5803214110438477,100*(exp(b - se^2/2) - 1),reported,-0.2981455052239388,0.06943114505215012,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.294117647058823,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,offroad,parking,A_structural,binary,binary,0.013,0.02,,0.523,,,,high,off-road parking vs on-road,"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,1.288227064668379,2.0261697347196184,100*(exp(b - se^2/2) - 1),reported,0.047227784683194385,0.07265813028183753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6499999999999999,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,FVista2,view,E_environment,binary,binary,0.04,0.038,,0.295,,,,high,front vista = field,"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,4.005958002714705,3.955080941931075,100*(exp(b - se^2/2) - 1),reported,0.07634421963945381,0.07252700865748113,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0526315789473684,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,FVista3,view,E_environment,binary,binary,-0.038,0.08,,0.636,,,,high,front vista = countryside,"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,-4.036281668288777,7.701703527129596,100*(exp(b - se^2/2) - 1),reported,-0.03453056110202922,0.07269591810953521,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.475,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,RVista2,view,E_environment,binary,binary,0.024,0.055,,0.663,,,,high,rear vista = field,"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,2.2742249806421366,5.633596748398419,100*(exp(b - se^2/2) - 1),reported,0.031724807044826664,0.0727026828110611,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4363636363636364,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,RVista3,view,E_environment,binary,binary,-0.011,0.035,,0.749,,,,high,rear vista = countryside,"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,-1.1545335157181036,3.4617109757137907,100*(exp(b - se^2/2) - 1),reported,-0.02285495036730397,0.07272029662323992,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3142857142857142,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,RVista4,view,E_environment,binary,binary,0.022,0.036,,0.551,,,,high,rear vista = sea,"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,2.158158507387764,3.680077624093577,100*(exp(b - se^2/2) - 1),reported,0.04440793990992342,0.07266753803442014,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6111111111111112,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,fWF1,hazard_site,E_environment,binary,binary,-0.026,0.061,,0.675,,,,high,partial/full view of 1 wind turbine from front (ref: no view),"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,-2.747597555968395,5.9434440466133704,100*(exp(b - se^2/2) - 1),reported,-0.030988744671963955,0.07270436249960775,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4262295081967213,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,FscreenV,hazard_site,E_environment,binary,binary,0.1,0.041,,0.016,,,,high,screened view of wind farm from front,"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,10.424241217826967,4.531200764110156,100*(exp(b - se^2/2) - 1),reported,0.17468508101305913,0.07162088321535426,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4390243902439024,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,FsideV,hazard_site,E_environment,binary,binary,0.261,0.063,,0.0,,,,high,side view of wind farm from front,"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,29.565388730766195,8.178834292232247,100*(exp(b - se^2/2) - 1),reported,0.28853221902855336,0.06964570804137495,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.142857142857143,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,FfacingV,hazard_site,E_environment,binary,binary,0.013,0.031,,0.685,,,,high,facing view of wind farm from front,"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,1.2598197012957169,3.1405630888154086,100*(exp(b - se^2/2) - 1),reported,0.030489394647215295,0.07270547954335956,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4193548387096774,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,RfacingV,hazard_site,E_environment,binary,binary,-0.074,0.036,,0.041,,,,high,facing view of wind farm from rear,"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,-7.192989048195065,3.343218097828634,100*(exp(b - se^2/2) - 1),reported,-0.14787583642422142,0.07193959609826987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.055555555555556,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,newH,age,A_structural,dummy,binary,-0.021,0.024,,0.394,,,,high,new-build dummy (not age in years),"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,-2.1063009886065798,2.350125514966703,100*(exp(b - se^2/2) - 1),reported,-0.06351836059412146,0.07259241210756738,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.875,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,Bed3,bedrooms,A_structural,dummy,binary,0.012,0.028,,0.684,,,,high,dummy for 3-bedroom house vs 2-bedroom,"ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",pct_premium,1.1675634278220715,2.8338024088250178,100*(exp(b - se^2/2) - 1),reported,0.031158847642487792,0.07270397783247151,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.42857142857142855,189.0,binary,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566,4f4475636117754066fcc0578aecfcf69e646566:T6-c1,6,1,14,DistMetre,hazard_site,E_environment,level,m,7.426e-05,,,0.707,,,,medium,"Distance to wind farm in metres; Std. Error printed as .000 (rounded), standardized beta .012","ln(house price, GBP)",log,OLS,199.0,0.975,se,"Model after removing medlocation and adding interactions (R2 0.975 from Table 7, adj. R2 0.971)",semi_elasticity,7.425999999999999,19.75587327636193,100*b/0.001 (X per m->km),|b/z(p)| (two-sided normal),0.027331630295740716,0.07271212288702238,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.37588821795517746,189.0,m,,2008.0,United Kingdom,Europe,High income,2000.0,2007.0,single_family,transaction,journal,True,True,OLS,,2003.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c1,3,Parcel,10,Living area,living_area,A_structural,level,1000 sqft,0.212,0.029,,,***,,,high,Living area in 1000 ft2,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7558,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Parcel; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,0.2281949008342461,0.031215340208458196,100*b/92.903 (X per 1000sqft->m2),reported,0.1745791066765188,0.023881104215184176,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.310344827586206,1700.0,1000sqft,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c2,3,Buffer 0.1 km,10,Living area,living_area,A_structural,level,1000 sqft,0.214,0.029,,,***,,,high,Living area in 1000 ft2,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,0.23034768291758803,0.031215340208458196,100*b/92.903 (X per 1000sqft->m2),reported,0.17617519266207188,0.023874208351402266,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.379310344827585,1700.0,1000sqft,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c3,3,Buffer 0.5 km,10,Living area,living_area,A_structural,level,1000 sqft,0.215,0.029,,,***,,,high,Living area in 1000 ft2,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7567,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.5 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,0.231424073959259,0.031215340208458196,100*b/92.903 (X per 1000sqft->m2),reported,0.17697271571485787,0.023870738398748273,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.413793103448276,1700.0,1000sqft,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c4,3,Buffer 1 km,10,Living area,living_area,A_structural,level,1000 sqft,0.214,0.029,,,***,,,high,Living area in 1000 ft2,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,0.23034768291758803,0.031215340208458196,100*b/92.903 (X per 1000sqft->m2),reported,0.17617519266207188,0.023874208351402266,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.379310344827585,1700.0,1000sqft,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c1,3,Parcel,10,Lot size,lot_size,A_structural,level,1000 sqft,0.006,0.001,,,***,,,high,Lot size in 1000 ft2,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7558,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Parcel; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,0.006458346250025833,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.1440046082211958,0.024000768036865967,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,1700.0,1000sqft,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c2,3,Buffer 0.1 km,10,Lot size,lot_size,A_structural,level,1000 sqft,0.004,0.002,,,**,,,high,Lot size in 1000 ft2,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,0.004305564166683889,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.04845015831115092,0.024225079155575462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,1700.0,1000sqft,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c3,3,Buffer 0.5 km,10,Lot size,lot_size,A_structural,level,1000 sqft,0.004,0.002,,,**,,,high,Lot size in 1000 ft2,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7567,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.5 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,0.004305564166683889,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.04845015831115092,0.024225079155575462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,1700.0,1000sqft,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c4,3,Buffer 1 km,10,Lot size,lot_size,A_structural,level,1000 sqft,0.004,0.002,,,**,,,high,Lot size in 1000 ft2,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,0.004305564166683889,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.04845015831115092,0.024225079155575462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,1700.0,1000sqft,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c1,3,Parcel,10,Baths,bathrooms,A_structural,level,count,0.069,0.014,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7558,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Parcel; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,6.9,1.4000000000000001,100*b/1 (per unit count),reported,0.11869045576035737,0.02408212145862323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.928571428571429,1700.0,count,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c2,3,Buffer 0.1 km,10,Baths,bathrooms,A_structural,level,count,0.07,0.014,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,7.000000000000001,1.4000000000000001,100*b/1 (per unit count),reported,0.12038585308576921,0.02407717061715384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,1700.0,count,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c3,3,Buffer 0.5 km,10,Baths,bathrooms,A_structural,level,count,0.068,0.014,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7567,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.5 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,6.800000000000001,1.4000000000000001,100*b/1 (per unit count),reported,0.11699401969383899,0.02408700405461391,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.857142857142858,1700.0,count,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c4,3,Buffer 1 km,10,Baths,bathrooms,A_structural,level,count,0.068,0.014,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,6.800000000000001,1.4000000000000001,100*b/1 (per unit count),reported,0.11699401969383899,0.02408700405461391,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.857142857142858,1700.0,count,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c1,3,Parcel,10,Bedrooms,bedrooms,A_structural,level,count,0.01,0.012,,,,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7558,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Parcel; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,1.0,1.2,100*b/1 (per unit count),reported,0.020207175225248876,0.024248610270298645,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8333333333333334,1700.0,count,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c2,3,Buffer 0.1 km,10,Bedrooms,bedrooms,A_structural,level,count,0.008,0.012,,,,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,0.8,1.2,100*b/1 (per unit count),reported,0.01616692848321183,0.024250392724817743,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6666666666666666,1700.0,count,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c3,3,Buffer 0.5 km,10,Bedrooms,bedrooms,A_structural,level,count,0.01,0.012,,,,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7567,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.5 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,1.0,1.2,100*b/1 (per unit count),reported,0.020207175225248876,0.024248610270298645,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8333333333333334,1700.0,count,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c4,3,Buffer 1 km,10,Bedrooms,bedrooms,A_structural,level,count,0.008,0.012,,,,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,0.8,1.2,100*b/1 (per unit count),reported,0.01616692848321183,0.024250392724817743,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6666666666666666,1700.0,count,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c1,3,Parcel,10,Age,age,A_structural,level,years,-0.002,0.0004,,,***,,,high,"Home age at sale, years","ln(sale price), 2005 USD",log,OLS,1710.0,0.7558,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Parcel; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,-0.2,0.04,100*b/1 (per year),reported,-0.12038585308576921,0.02407717061715384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,1700.0,years,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c2,3,Buffer 0.1 km,10,Age,age,A_structural,level,years,-0.002,0.0004,,,***,,,high,"Home age at sale, years","ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,-0.2,0.04,100*b/1 (per year),reported,-0.12038585308576921,0.02407717061715384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,1700.0,years,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c3,3,Buffer 0.5 km,10,Age,age,A_structural,level,years,-0.002,0.0004,,,***,,,high,"Home age at sale, years","ln(sale price), 2005 USD",log,OLS,1710.0,0.7567,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.5 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,-0.2,0.04,100*b/1 (per year),reported,-0.12038585308576921,0.02407717061715384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,1700.0,years,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c4,3,Buffer 1 km,10,Age,age,A_structural,level,years,-0.002,0.0004,,,***,,,high,"Home age at sale, years","ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,-0.2,0.04,100*b/1 (per year),reported,-0.12038585308576921,0.02407717061715384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,1700.0,years,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c1,3,Parcel,10,Stories,storeys,A_structural,level,count,0.082,0.029,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7558,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Parcel; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,8.200000000000001,2.9000000000000004,100*b/1 (per unit count),reported,0.06841833891124921,0.024196729614953987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8275862068965516,1700.0,count,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c2,3,Buffer 0.1 km,10,Stories,storeys,A_structural,level,count,0.084,0.029,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,8.4,2.9000000000000004,100*b/1 (per unit count),reported,0.07007898069176266,0.024193933810251395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.896551724137931,1700.0,count,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c3,3,Buffer 0.5 km,10,Stories,storeys,A_structural,level,count,0.081,0.029,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7567,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.5 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,8.1,2.9000000000000004,100*b/1 (per unit count),reported,0.06758780383837522,0.024198102608801005,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.793103448275862,1700.0,count,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c4,3,Buffer 1 km,10,Stories,storeys,A_structural,level,count,0.083,0.029,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,8.3,2.9000000000000004,100*b/1 (per unit count),reported,0.06924873176008074,0.02419534001255833,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8620689655172415,1700.0,count,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c1,3,Parcel,10,Air conditioning,air_conditioning,A_structural,binary,binary,0.105,0.015,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7558,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Parcel; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,11.058566244049217,1.6660659155335578,100*(exp(b - se^2/2) - 1),reported,0.16737983495058364,0.02391140499294052,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c2,3,Buffer 0.1 km,10,Air conditioning,air_conditioning,A_structural,binary,binary,0.106,0.015,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.1 km; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,11.169680358090783,1.6677328147597963,100*(exp(b - se^2/2) - 1),reported,0.1689286466552302,0.023904997168192957,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.066666666666666,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c3,3,Buffer 0.5 km,10,Air conditioning,air_conditioning,A_structural,binary,binary,0.105,0.015,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7567,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.5 km; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,11.058566244049217,1.6660659155335578,100*(exp(b - se^2/2) - 1),reported,0.16737983495058364,0.02391140499294052,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c4,3,Buffer 1 km,10,Air conditioning,air_conditioning,A_structural,binary,binary,0.105,0.015,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 1 km; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,11.058566244049217,1.6660659155335578,100*(exp(b - se^2/2) - 1),reported,0.16737983495058364,0.02391140499294052,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c1,3,Parcel,10,Fireplace,fireplace,B_interior,binary,binary,0.092,0.016,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7558,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Parcel; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,9.622449636462814,1.754183715329307,100*(exp(b - se^2/2) - 1),reported,0.13812132380685582,0.024021099792496666,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.75,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c2,3,Buffer 0.1 km,10,Fireplace,fireplace,B_interior,binary,binary,0.089,0.016,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.1 km; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,9.294075095645503,1.7489290501221284,100*(exp(b - se^2/2) - 1),reported,0.1336992098208472,0.024035813001500626,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.5625,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c3,3,Buffer 0.5 km,10,Fireplace,fireplace,B_interior,binary,binary,0.091,0.016,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7567,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.5 km; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,9.512881979785327,1.7524304084135447,100*(exp(b - se^2/2) - 1),reported,0.13664818991007824,0.024026055368804967,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.6875,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c4,3,Buffer 1 km,10,Fireplace,fireplace,B_interior,binary,binary,0.092,0.016,,,***,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 1 km; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,9.622449636462814,1.754183715329307,100*(exp(b - se^2/2) - 1),reported,0.13812132380685582,0.024021099792496666,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.75,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c1,3,Parcel,10,Pool,pool,C_exterior,binary,binary,0.014,0.052,,,,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7558,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Parcel; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,1.2728324241768618,5.273311986480159,100*(exp(b - se^2/2) - 1),reported,0.0065296660838064235,0.024253045454138138,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2692307692307693,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c2,3,Buffer 0.1 km,10,Pool,pool,C_exterior,binary,binary,0.007,0.052,,,,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.1 km; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,0.5663980022891035,5.236527697787612,100*(exp(b - se^2/2) - 1),reported,0.003264885243598369,0.024253433238159306,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.13461538461538464,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c3,3,Buffer 0.5 km,10,Pool,pool,C_exterior,binary,binary,0.013,0.052,,,,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7567,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.5 km; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,1.1716102112943272,5.268041310271007,100*(exp(b - se^2/2) - 1),reported,0.006063279169595053,0.02425311667838021,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.25,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c4,3,Buffer 1 km,10,Pool,pool,C_exterior,binary,binary,0.011,0.052,,,,,,high,,"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 1 km; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,0.9694691992640836,5.257515756712541,100*(exp(b - se^2/2) - 1),reported,0.005130493775170161,0.0242532433008044,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.21153846153846154,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c1,3,Parcel,10,Distance to highway,highway_distance,D_location,level,km,0.041,0.014,,,***,,,high,Linear term of a quadratic in distance to highway (km),"ln(sale price), 2005 USD",log,OLS,1710.0,0.7558,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Parcel; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,4.1000000000000005,1.4000000000000001,100*b/1 (X per km->km),reported,0.07084979578508309,0.024192613194906416,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.928571428571429,1700.0,km,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c2,3,Buffer 0.1 km,10,Distance to highway,highway_distance,D_location,level,km,0.043,0.014,,,***,,,high,Linear term of a quadratic in distance to highway (km),"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,4.3,1.4000000000000001,100*b/1 (X per km->km),reported,0.07428725185038029,0.024186547114077306,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.071428571428571,1700.0,km,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c3,3,Buffer 0.5 km,10,Distance to highway,highway_distance,D_location,level,km,0.044,0.014,,,***,,,high,Linear term of a quadratic in distance to highway (km),"ln(sale price), 2005 USD",log,OLS,1710.0,0.7567,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.5 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,4.3999999999999995,1.4000000000000001,100*b/1 (X per km->km),reported,0.07600499513704667,0.024183407543605758,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.142857142857143,1700.0,km,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c4,3,Buffer 1 km,10,Distance to highway,highway_distance,D_location,level,km,0.043,0.014,,,***,,,high,Linear term of a quadratic in distance to highway (km),"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,4.3,1.4000000000000001,100*b/1 (X per km->km),reported,0.07428725185038029,0.024186547114077306,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.071428571428571,1700.0,km,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c1,3,Parcel,10,Distance to Airport,airport_distance,D_location,level,km,-0.03,0.006,,,***,,,high,Linear term of a quadratic in distance to airport (km),"ln(sale price), 2005 USD",log,OLS,1710.0,0.7558,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Parcel; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,-3.0,0.6,100*b/1 (X per km->km),reported,-0.12038585308576921,0.02407717061715384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,1700.0,km,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c2,3,Buffer 0.1 km,10,Distance to Airport,airport_distance,D_location,level,km,-0.03,0.006,,,***,,,high,Linear term of a quadratic in distance to airport (km),"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,-3.0,0.6,100*b/1 (X per km->km),reported,-0.12038585308576921,0.02407717061715384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,1700.0,km,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c3,3,Buffer 0.5 km,10,Distance to Airport,airport_distance,D_location,level,km,-0.028,0.006,,,***,,,high,Linear term of a quadratic in distance to airport (km),"ln(sale price), 2005 USD",log,OLS,1710.0,0.7567,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 0.5 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,-2.8000000000000003,0.6,100*b/1 (X per km->km),reported,-0.11246521862381834,0.024099689705103927,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.666666666666667,1700.0,km,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c4,3,Buffer 1 km,10,Distance to Airport,airport_distance,D_location,level,km,-0.028,0.006,,,***,,,high,Linear term of a quadratic in distance to airport (km),"ln(sale price), 2005 USD",log,OLS,1710.0,0.757,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Buffer 1 km; year-of-sale and zip-code fixed effects; adjusted R2",semi_elasticity,-2.8000000000000003,0.6,100*b/1 (X per km->km),reported,-0.11246521862381834,0.024099689705103927,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.666666666666667,1700.0,km,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T3-c1,3,Parcel,10,Ash,landscaping,C_exterior,binary,binary,0.005,0.015,,,,,,high,Ash_parcel: 1 if ash trees on the sales parcel,"ln(sale price), 2005 USD",log,OLS,1710.0,0.7558,se,"Model 1, home sales 2008-2011 (pre-EAB), ash variable measured at Parcel; year-of-sale and zip-code fixed effects; adjusted R2",pct_premium,0.489946331041069,1.5075187812891013,100*(exp(b - se^2/2) - 1),reported,0.008084256647467437,0.02425276994240231,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.33333333333333337,1700.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T5-c1,5,Parcel,12,Ash,landscaping,C_exterior,binary,binary,0.007,0.016,,,,,,high,Ash_parcel: 1 if ash trees on the sales parcel,"ln(sale price), 2005 USD",log,OLS,4502.0,0.7647,se,"Model 3 difference-in-differences, home sales 2008-2015, ash variable at Parcel; only ash/EAB coefficients printed (controls as Model 1); year and zip-code FE; adjusted R2; 'Sum 1'/'Sum 2' linear combinations not extracted",pct_premium,0.6895666372711551,1.6112392916269578,100*(exp(b - se^2/2) - 1),reported,0.006527530819625936,0.01492007044485928,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4375,4492.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a,51b11fac87d973139852a88a8c12a9cdbf87b57a:T6-c1,6,Parcel,12,Ash,landscaping,C_exterior,binary,binary,0.007,0.016,,,,,,high,Ash_parcel: 1 if ash trees on the sales parcel,"ln(sale price), 2005 USD",log,OLS,4502.0,0.765,se,"Model 4 (Model 3 plus EAB severity within 1 km), home sales 2008-2015, ash variable at Parcel; only ash/EAB coefficients printed (controls as Model 1); year and zip-code FE; adjusted R2; 'Sum 1'/'Sum 2' linear combinations not extracted",pct_premium,0.6895666372711551,1.6112392916269578,100*(exp(b - se^2/2) - 1),reported,0.006527530819625936,0.01492007044485928,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4375,4492.0,binary,,2019.0,United States,North America,High income,2008.0,2015.0,single_family,transaction,journal,True,True,unknown,,2011.5,ols,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c1,7,1,12,AREA,living_area,A_structural,level,ping (1 ping = 3.306 m2),0.023,0.001,,,***,,,high,building transfer area,"ln(PRICE), total price in ten thousand NT$",log,OLS,5124.0,0.797,se,"During construction sample (PSM-matched); OLS; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,0.6957468691390888,0.03024986387561256,100*b/3.3058 (X per pyeong->m2),reported,0.3061771744685008,0.013312051063847863,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.0,5114.0,pyeong,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,ols,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c2,7,2,12,AREA,living_area,A_structural,level,ping (1 ping = 3.306 m2),0.022,0.001,,,***,,,high,building transfer area,"ln(PRICE), total price in ten thousand NT$",log,spatial_lag,5124.0,0.807,se,"During construction sample (PSM-matched); spatial_lag; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,0.6654970052634762,0.03024986387561256,100*b/3.3058 (X per pyeong->m2),reported,0.29403987791369596,0.01336544899607709,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,5114.0,pyeong,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c3,7,3,12,AREA,living_area,A_structural,level,ping (1 ping = 3.306 m2),0.022,0.001,,,***,,,high,building transfer area,"ln(PRICE), total price in ten thousand NT$",log,spatial_error,5124.0,0.813,se,"During construction sample (PSM-matched); spatial_error; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,0.6654970052634762,0.03024986387561256,100*b/3.3058 (X per pyeong->m2),reported,0.29403987791369596,0.01336544899607709,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,5114.0,pyeong,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c4,7,4,12,AREA,living_area,A_structural,level,ping (1 ping = 3.306 m2),0.018,0.001,,,***,,,high,building transfer area,"ln(PRICE), total price in ten thousand NT$",log,OLS,7647.0,0.719,se,"After construction sample (PSM-matched); OLS; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,0.544497549761026,0.03024986387561256,100*b/3.3058 (X per pyeong->m2),reported,0.2017384562323821,0.011207692012910116,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,7637.0,pyeong,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,ols,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c5,7,5,12,AREA,living_area,A_structural,level,ping (1 ping = 3.306 m2),0.017,0.001,,,***,,,high,building transfer area,"ln(PRICE), total price in ten thousand NT$",log,spatial_lag,7647.0,0.746,se,"After construction sample (PSM-matched); spatial_lag; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,0.5142476858854136,0.03024986387561256,100*b/3.3058 (X per pyeong->m2),reported,0.19095097814228348,0.011232410478957853,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.0,7637.0,pyeong,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c6,7,6,12,AREA,living_area,A_structural,level,ping (1 ping = 3.306 m2),0.017,0.001,,,***,,,high,building transfer area,"ln(PRICE), total price in ten thousand NT$",log,spatial_error,7647.0,0.757,se,"After construction sample (PSM-matched); spatial_error; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,0.5142476858854136,0.03024986387561256,100*b/3.3058 (X per pyeong->m2),reported,0.19095097814228348,0.011232410478957853,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.0,7637.0,pyeong,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c1,7,1,12,AGE,age,A_structural,level,years,-0.013,0.001,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,OLS,5124.0,0.797,se,"During construction sample (PSM-matched); OLS; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,-1.3,0.1,100*b/1 (per year),reported,-0.17885580773948248,0.013758139056883268,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.0,5114.0,years,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,ols,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c2,7,2,12,AGE,age,A_structural,level,years,-0.013,0.001,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,spatial_lag,5124.0,0.807,se,"During construction sample (PSM-matched); spatial_lag; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,-1.3,0.1,100*b/1 (per year),reported,-0.17885580773948248,0.013758139056883268,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.0,5114.0,years,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c3,7,3,12,AGE,age,A_structural,level,years,-0.013,0.001,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,spatial_error,5124.0,0.813,se,"During construction sample (PSM-matched); spatial_error; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,-1.3,0.1,100*b/1 (per year),reported,-0.17885580773948248,0.013758139056883268,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.0,5114.0,years,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c4,7,4,12,AGE,age,A_structural,level,years,-0.004,0.001,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,OLS,7647.0,0.719,se,"After construction sample (PSM-matched); OLS; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,-0.4,0.1,100*b/1 (per year),reported,-0.045723991428284164,0.011430997857071041,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,7637.0,years,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,ols,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c5,7,5,12,AGE,age,A_structural,level,years,-0.004,0.001,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,spatial_lag,7647.0,0.746,se,"After construction sample (PSM-matched); spatial_lag; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,-0.4,0.1,100*b/1 (per year),reported,-0.045723991428284164,0.011430997857071041,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,7637.0,years,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c6,7,6,12,AGE,age,A_structural,level,years,-0.004,0.001,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,spatial_error,7647.0,0.757,se,"After construction sample (PSM-matched); spatial_error; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,-0.4,0.1,100*b/1 (per year),reported,-0.045723991428284164,0.011430997857071041,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,7637.0,years,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c1,7,1,12,FLOOR,floor_level,A_structural,dummy,binary (first floor = 1 vs other floors),0.124,0.021,,,***,,,high,residence on 1st floor,"ln(PRICE), total price in ten thousand NT$",log,OLS,5124.0,0.797,se,"During construction sample (PSM-matched); OLS; location fixed effects; DD specification with TIME, TREAT, DD",pct_premium,13.176628901704458,2.377233329098268,100*(exp(b - se^2/2) - 1),reported,0.08228990988664409,0.013936194416286499,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.904761904761904,5114.0,binary,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,ols,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c2,7,2,12,FLOOR,floor_level,A_structural,dummy,binary (first floor = 1 vs other floors),0.126,0.02,,,***,,,high,residence on 1st floor,"ln(PRICE), total price in ten thousand NT$",log,spatial_lag,5124.0,0.807,se,"During construction sample (PSM-matched); spatial_lag; location fixed effects; DD specification with TIME, TREAT, DD",pct_premium,13.405533453349939,2.26856433656605,100*(exp(b - se^2/2) - 1),reported,0.0877569262984512,0.013929670841023997,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.3,5114.0,binary,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c3,7,3,12,FLOOR,floor_level,A_structural,dummy,binary (first floor = 1 vs other floors),0.129,0.02,,,***,,,high,residence on 1st floor,"ln(PRICE), total price in ten thousand NT$",log,spatial_error,5124.0,0.813,se,"During construction sample (PSM-matched); spatial_error; location fixed effects; DD specification with TIME, TREAT, DD",pct_premium,13.746260889318407,2.275380248331463,100*(exp(b - se^2/2) - 1),reported,0.08982971086721732,0.013927086956157722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.45,5114.0,binary,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c4,7,4,12,FLOOR,floor_level,A_structural,dummy,binary (first floor = 1 vs other floors),0.221,0.013,,,***,,,high,residence on 1st floor,"ln(PRICE), total price in ten thousand NT$",log,OLS,7647.0,0.719,se,"After construction sample (PSM-matched); OLS; location fixed effects; DD specification with TIME, TREAT, DD",pct_premium,24.721803618715743,1.6215204597332842,100*(exp(b - se^2/2) - 1),reported,0.19095097814228348,0.011232410478957853,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.0,7637.0,binary,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,ols,journal,True,True,True
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c5,7,5,12,FLOOR,floor_level,A_structural,dummy,binary (first floor = 1 vs other floors),0.219,0.012,,,***,,,high,residence on 1st floor,"ln(PRICE), total price in ten thousand NT$",log,spatial_lag,7647.0,0.746,se,"After construction sample (PSM-matched); spatial_lag; location fixed effects; DD specification with TIME, TREAT, DD",pct_premium,24.474165206213485,1.4937975320250374,100*(exp(b - se^2/2) - 1),reported,0.2044240580388083,0.011201318248701825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.25,7637.0,binary,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c6,7,6,12,FLOOR,floor_level,A_structural,dummy,binary (first floor = 1 vs other floors),0.221,0.012,,,***,,,high,residence on 1st floor,"ln(PRICE), total price in ten thousand NT$",log,spatial_error,7647.0,0.757,se,"After construction sample (PSM-matched); spatial_error; location fixed effects; DD specification with TIME, TREAT, DD",pct_premium,24.723362651004898,1.4967881166768777,100*(exp(b - se^2/2) - 1),reported,0.2062119022244369,0.011197026365127793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.416666666666668,7637.0,binary,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,True
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c1,7,1,12,ROOM,bedrooms,A_structural,level,count,0.085,0.007,,,***,,,high,number of rooms,"ln(PRICE), total price in ten thousand NT$",log,OLS,5124.0,0.797,se,"During construction sample (PSM-matched); OLS; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,8.5,0.7000000000000001,100*b/1 (per unit count),reported,0.16740491472871646,0.013786287095306061,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.142857142857144,5114.0,count,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,ols,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c2,7,2,12,ROOM,bedrooms,A_structural,level,count,0.085,0.007,,,***,,,high,number of rooms,"ln(PRICE), total price in ten thousand NT$",log,spatial_lag,5124.0,0.807,se,"During construction sample (PSM-matched); spatial_lag; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,8.5,0.7000000000000001,100*b/1 (per unit count),reported,0.16740491472871646,0.013786287095306061,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.142857142857144,5114.0,count,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c3,7,3,12,ROOM,bedrooms,A_structural,level,count,0.086,0.007,,,***,,,high,number of rooms,"ln(PRICE), total price in ten thousand NT$",log,spatial_error,5124.0,0.813,se,"During construction sample (PSM-matched); spatial_error; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,8.6,0.7000000000000001,100*b/1 (per unit count),reported,0.16931824120930172,0.013781717307733863,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.285714285714285,5114.0,count,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c4,7,4,12,ROOM,bedrooms,A_structural,level,count,0.082,0.005,,,***,,,high,number of rooms,"ln(PRICE), total price in ten thousand NT$",log,OLS,7647.0,0.719,se,"After construction sample (PSM-matched); OLS; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,8.200000000000001,0.5,100*b/1 (per unit count),reported,0.1844448534689467,0.011246637406643094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.4,7637.0,count,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,ols,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c5,7,5,12,ROOM,bedrooms,A_structural,level,count,0.078,0.005,,,***,,,high,number of rooms,"ln(PRICE), total price in ten thousand NT$",log,spatial_lag,7647.0,0.746,se,"After construction sample (PSM-matched); spatial_lag; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,7.8,0.5,100*b/1 (per unit count),reported,0.17573229038961174,0.011264890409590497,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.6,7637.0,count,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c6,7,6,12,ROOM,bedrooms,A_structural,level,count,0.081,0.005,,,***,,,high,number of rooms,"ln(PRICE), total price in ten thousand NT$",log,spatial_error,7647.0,0.757,se,"After construction sample (PSM-matched); spatial_error; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,8.1,0.5,100*b/1 (per unit count),reported,0.1822707002918571,0.011251277795793648,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.2,7637.0,count,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c1,7,1,12,BATH,bathrooms,A_structural,level,count,0.087,0.01,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,OLS,5124.0,0.797,se,"During construction sample (PSM-matched); OLS; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,8.7,1.0,100*b/1 (per unit count),reported,0.12076707405522506,0.013881272879910927,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.7,5114.0,count,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,ols,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c2,7,2,12,BATH,bathrooms,A_structural,level,count,0.085,0.01,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,spatial_lag,5124.0,0.807,se,"During construction sample (PSM-matched); spatial_lag; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,8.5,1.0,100*b/1 (per unit count),reported,0.11802994419706878,0.013885875787890446,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.5,5114.0,count,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c3,7,3,12,BATH,bathrooms,A_structural,level,count,0.083,0.01,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,spatial_error,5124.0,0.813,se,"During construction sample (PSM-matched); spatial_error; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,8.3,1.0,100*b/1 (per unit count),reported,0.11529012142031876,0.0138903760747372,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.3,5114.0,count,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c4,7,4,12,BATH,bathrooms,A_structural,level,count,0.018,0.007,,,**,,,high,,"ln(PRICE), total price in ten thousand NT$",log,OLS,7647.0,0.719,se,"After construction sample (PSM-matched); OLS; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,1.7999999999999998,0.7000000000000001,100*b/1 (per unit count),reported,0.02941203955374915,0.01143801538201356,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.571428571428571,7637.0,count,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,ols,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c5,7,5,12,BATH,bathrooms,A_structural,level,count,0.017,0.007,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,spatial_lag,7647.0,0.746,se,"After construction sample (PSM-matched); spatial_lag; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,1.7000000000000002,0.7000000000000001,100*b/1 (per unit count),reported,0.027779335358189095,0.011438549853371978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.428571428571429,7637.0,count,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c6,7,6,12,BATH,bathrooms,A_structural,level,count,0.019,0.007,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,spatial_error,7647.0,0.757,se,"After construction sample (PSM-matched); spatial_error; location fixed effects; DD specification with TIME, TREAT, DD",semi_elasticity,1.9,0.7000000000000001,100*b/1 (per unit count),reported,0.031044508366704086,0.011437450450890983,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.714285714285714,7637.0,count,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c1,7,1,12,TYPE,dwelling_type,A_structural,binary,binary (multistoried building = 1 vs apartment house),0.068,0.012,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,OLS,5124.0,0.797,se,"During construction sample (PSM-matched); OLS; location fixed effects; DD specification with TIME, TREAT, DD",pct_premium,7.028824495088415,1.2844383701745292,100*(exp(b - se^2/2) - 1),reported,0.07899290530704707,0.013939924465949483,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.666666666666667,5114.0,binary,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,ols,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c2,7,2,12,TYPE,dwelling_type,A_structural,binary,binary (multistoried building = 1 vs apartment house),0.073,0.012,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,spatial_lag,5124.0,0.807,se,"During construction sample (PSM-matched); spatial_lag; location fixed effects; DD specification with TIME, TREAT, DD",pct_premium,7.565308710427221,1.2908766442976443,100*(exp(b - se^2/2) - 1),reported,0.08476089744982494,0.013933298210930128,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.083333333333333,5114.0,binary,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c3,7,3,12,TYPE,dwelling_type,A_structural,binary,binary (multistoried building = 1 vs apartment house),0.069,0.012,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,spatial_error,5124.0,0.813,se,"During construction sample (PSM-matched); spatial_error; location fixed effects; DD specification with TIME, TREAT, DD",pct_premium,7.135906851838358,1.2857234509780155,100*(exp(b - se^2/2) - 1),reported,0.08014715740629483,0.01393863607065997,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.75,5114.0,binary,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c4,7,4,12,TYPE,dwelling_type,A_structural,binary,binary (multistoried building = 1 vs apartment house),0.272,0.008,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,OLS,7647.0,0.719,se,"After construction sample (PSM-matched); OLS; location fixed effects; DD specification with TIME, TREAT, DD",pct_premium,31.254499919910383,1.0500696010488866,100*(exp(b - se^2/2) - 1),reported,0.3625854566188909,0.010664278135849733,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.0,7637.0,binary,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,ols,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c5,7,5,12,TYPE,dwelling_type,A_structural,binary,binary (multistoried building = 1 vs apartment house),0.255,0.008,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,spatial_lag,7647.0,0.746,se,"After construction sample (PSM-matched); spatial_lag; location fixed effects; DD specification with TIME, TREAT, DD",pct_premium,29.042032676173136,1.032369296698312,100*(exp(b - se^2/2) - 1),reported,0.3426623977331172,0.010750192870058578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),31.875,7637.0,binary,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97,5242a8699dbfd95d3c698daaa18f7bab00d59c97:T7-c6,7,6,12,TYPE,dwelling_type,A_structural,binary,binary (multistoried building = 1 vs apartment house),0.289,0.008,,,***,,,high,,"ln(PRICE), total price in ten thousand NT$",log,spatial_error,7647.0,0.757,se,"After construction sample (PSM-matched); spatial_error; location fixed effects; DD specification with TIME, TREAT, DD",pct_premium,33.504900627675525,1.0680733828228068,100*(exp(b - se^2/2) - 1),reported,0.38202355665162496,0.010575046550910032,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),36.125,7637.0,binary,,2020.0,Taiwan,Asia,High income,2008.0,2014.0,condo_apartment,transaction,journal,False,True,unknown,,2011.0,spatial,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Rooms,bedrooms,A_structural,level,count,0.059,0.031,,,*,,,high,Median number of rooms in block group White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,semi_elasticity,5.8999999999999995,3.1,100*b/1 (per unit count),reported,0.07683157956966678,0.04036913502813001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9032258064516128,610.0,count,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,House Age,age,A_structural,level,years,-0.014,0.003,,,***,,,high,Median house age White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,semi_elasticity,-1.4000000000000001,0.3,100*b/1 (per year),reported,-0.18566267696174743,0.03978485934894588,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.666666666666667,610.0,years,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(Income),income,F_neighbourhood,log,currency,0.42,0.067,,,***,,,high,Log median household income White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,0.42,0.067,b (log-log),reported,0.2460101948235074,0.039244483459940464,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.26865671641791,610.0,currency,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(Pop den),density,F_neighbourhood,log,per_km2,0.0,0.021,,,,,,high,Log population density White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,0.0,0.021,b (log-log),reported,0.0,0.0404888165089458,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0,610.0,per_km2,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(Road),highway_distance,D_location,log,km,0.004,0.014,,,,,,high,Log distance to nearest road White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,0.004,0.014,b (log-log),reported,0.01156745931220217,0.0404861075927076,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2857142857142857,610.0,km,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(Rail),transit_distance,D_location,log,km,0.013,0.013,,,,,,high,"Log distance to nearest railroad (line, not station) White SE.",ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,0.013,0.013,b (log-log),reported,0.04045566970313674,0.04045566970313674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,610.0,km,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(School),school_distance,D_location,log,km,0.0,0.022,,,,,,high,White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,0.0,0.022,b (log-log),reported,0.0,0.0404888165089458,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0,610.0,km,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(Shopping centers),commercial_distance,D_location,log,km,-0.036,0.021,,,*,,,high,White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,-0.036,0.021,b (log-log),reported,-0.06924280582381005,0.040391636730555874,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.714285714285714,610.0,km,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(Hospital),hospital_distance,D_location,log,km,-0.086,0.025,,,***,,,high,White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,-0.086,0.025,b (log-log),reported,-0.1379498873346141,0.04010171143448086,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.4399999999999995,610.0,km,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(Airport),airport_distance,D_location,log,km,0.006,0.026,,,,,,high,White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,0.006,0.026,b (log-log),reported,0.009343165209253849,0.04048704924010001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.23076923076923078,610.0,km,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(Park),green_space,E_environment,log,km,-0.01,0.021,,,,,,high,Log distance to nearest public park White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,-0.01,0.021,b (log-log),reported,-0.019276806230402954,0.04048129308384621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.47619047619047616,610.0,km,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(Bay),water_proximity,E_environment,log,km,-0.059,0.009,,,***,,,high,Log distance to nearest bay White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,-0.059,0.009,b (log-log),reported,-0.2565435632351774,0.03913376388333214,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.555555555555555,610.0,km,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(River),water_proximity,E_environment,log,km,-0.004,0.012,,,,,,high,Log distance to nearest river White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,-0.004,0.012,b (log-log),reported,-0.013495043168856575,0.040485129506569725,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3333333333333333,610.0,km,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(Stream),water_proximity,E_environment,log,km,-0.03,0.017,,,*,,,high,Log distance to nearest stream White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,-0.03,0.017,b (log-log),reported,-0.07126916173107088,0.04038585831427351,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.764705882352941,610.0,km,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(Bayou),water_proximity,E_environment,log,km,0.038,0.018,,,**,,,high,Log distance to nearest bayou White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,0.038,0.018,b (log-log),reported,0.08516583673303921,0.040341712136702776,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.111111111111111,610.0,km,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd:T2-OLS,2,Global Model (OLS),9,Ln(Water),water_proximity,E_environment,log,km,-0.029,0.011,,,***,,,high,Log distance to nearest other water body White SE.,ln(housing value),log,OLS,620.0,0.518,se,all 620 block groups; White SE,elasticity,-0.029,0.011,b (log-log),reported,-0.10614026876872888,0.040260101946759226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6363636363636367,610.0,km,,2021.0,United States,North America,High income,2010.0,2010.0,mixed,appraisal,journal,False,False,robust,,2010.0,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c1,3,Mod. 1,14,BTS_Prox,hazard_site,E_environment,dummy,binary,0.014,0.007,,,*,,,high,Dummy = 1 if apartment within 200 m of a base transceiver station (cell phone tower),ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS proximity dummy,pct_premium,1.4073613830602127,0.7098689212569446,100*(exp(b - se^2/2) - 1),reported,0.04689360772322401,0.02344680386161201,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c1,3,Mod. 1,14,Ln Area,living_area,A_structural,log,m2,0.913,0.017,,,***,,,high,Natural log of usable area in m2,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS proximity dummy,elasticity,0.913,0.017,b (log-log),reported,0.7834373335469489,0.014587551665167722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),53.705882352941174,1815.0,m2,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c1,3,Mod. 1,14,Rooms,bedrooms,A_structural,level,count,0.008,0.006,,,,,,high,Number of rooms (not bedrooms),ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS proximity dummy,semi_elasticity,0.8,0.6,100*b/1 (per unit count),reported,0.03128151887348551,0.023461139155114136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3333333333333333,1815.0,count,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c1,3,Mod. 1,14,Floor2,floor_level,A_structural,dummy,binary,0.014,0.009,,,,,,high,Dummy for 'other floors' (above 2nd); base = ground floor,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS proximity dummy,pct_premium,1.405738878258167,0.9126886130446429,100*(exp(b - se^2/2) - 1),reported,0.03648865911843895,0.023456995147567897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5555555555555558,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c1,3,Mod. 1,14,Floor3,floor_level,A_structural,dummy,binary,0.076,0.01,,,***,,,high,Dummy for first or second floor; base = ground floor,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS proximity dummy,pct_premium,7.890862737725679,1.078962574157284,100*(exp(b - se^2/2) - 1),reported,0.17561941651496862,0.02310781796249587,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.6,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c1,3,Mod. 1,14,School,school_distance,D_location,level,100 m,-0.006,0.001,,,***,,,high,Linear distance to nearest elementary school in 100 m units,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS proximity dummy,semi_elasticity,-5.999999999999999,1.0,100*b/0.1 (X per 100m->km),reported,-0.13945947983338056,0.023243246638896764,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c1,3,Mod. 1,14,Bus,transit_distance,D_location,level,100 m,0.01,0.003,,,***,,,high,Linear distance to nearest public transport stop in 100 m units,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS proximity dummy,semi_elasticity,10.0,2.9999999999999996,100*b/0.1 (X per 100m->km),reported,0.07800368966178357,0.02340110689853507,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3333333333333335,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c2,3,Mod. 2,14,BTS_Dist,hazard_site,E_environment,level,100 m,0.006,0.004,,,,,,high,Linear distance to nearest base transceiver station in 100 m units (Table 2 label is a copy-paste error),ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS distance,semi_elasticity,5.999999999999999,4.0,100*b/0.1 (X per 100m->km),reported,0.03518713605785183,0.023458090705234552,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c2,3,Mod. 2,14,Ln Area,living_area,A_structural,log,m2,0.919,0.017,,,***,,,high,Natural log of usable area in m2,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS distance,elasticity,0.919,0.017,b (log-log),reported,0.7854138594468192,0.014528874440256719,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),54.05882352941176,1815.0,m2,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c2,3,Mod. 2,14,Rooms,bedrooms,A_structural,level,count,0.006,0.006,,,,,,high,Number of rooms (not bedrooms),ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS distance,semi_elasticity,0.6,0.6,100*b/1 (per unit count),reported,0.023466162723196606,0.023466162723196606,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,1815.0,count,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c2,3,Mod. 2,14,Floor2,floor_level,A_structural,dummy,binary,0.015,0.009,,,,,,high,Dummy for 'other floors' (above 2nd); base = ground floor,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS distance,pct_premium,1.507195336911038,0.9136017581541469,100*(exp(b - se^2/2) - 1),reported,0.039091141700047634,0.02345468502002858,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6666666666666667,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c2,3,Mod. 2,14,Floor3,floor_level,A_structural,dummy,binary,0.077,0.01,,,***,,,high,Dummy for first or second floor; base = ground floor,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS distance,pct_premium,7.998807563881072,1.0800420763926004,100*(exp(b - se^2/2) - 1),reported,0.1778575604636294,0.02309838447579603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.7,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c2,3,Mod. 2,14,School,school_distance,D_location,level,100 m,-0.005,0.001,,,***,,,high,Linear distance to nearest elementary school in 100 m units,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS distance,semi_elasticity,-5.0,1.0,100*b/0.1 (X per 100m->km),reported,-0.11656310103003922,0.023312620206007845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c2,3,Mod. 2,14,Bus,transit_distance,D_location,level,100 m,0.009,0.003,,,**,,,high,Linear distance to nearest public transport stop in 100 m units,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; BTS distance,semi_elasticity,8.999999999999998,2.9999999999999996,100*b/0.1 (X per 100m->km),reported,0.07024393586862704,0.02341464528954235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9999999999999996,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c3,3,Mod. 3,14,Ln Area,living_area,A_structural,log,m2,0.912,0.017,,,***,,,high,Natural log of usable area in m2,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; number of BTS,elasticity,0.912,0.017,b (log-log),reported,0.7831055819834641,0.014597362822060188,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),53.64705882352941,1815.0,m2,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c3,3,Mod. 3,14,Rooms,bedrooms,A_structural,level,count,0.008,0.006,,,,,,high,Number of rooms (not bedrooms),ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; number of BTS,semi_elasticity,0.8,0.6,100*b/1 (per unit count),reported,0.03128151887348551,0.023461139155114136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3333333333333333,1815.0,count,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c3,3,Mod. 3,14,Floor2,floor_level,A_structural,dummy,binary,0.014,0.009,,,,,,high,Dummy for 'other floors' (above 2nd); base = ground floor,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; number of BTS,pct_premium,1.405738878258167,0.9126886130446429,100*(exp(b - se^2/2) - 1),reported,0.03648865911843895,0.023456995147567897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5555555555555558,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c3,3,Mod. 3,14,Floor3,floor_level,A_structural,dummy,binary,0.076,0.01,,,***,,,high,Dummy for first or second floor; base = ground floor,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; number of BTS,pct_premium,7.890862737725679,1.078962574157284,100*(exp(b - se^2/2) - 1),reported,0.17561941651496862,0.02310781796249587,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.6,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c3,3,Mod. 3,14,School,school_distance,D_location,level,100 m,-0.006,0.001,,,***,,,high,Linear distance to nearest elementary school in 100 m units,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; number of BTS,semi_elasticity,-5.999999999999999,1.0,100*b/0.1 (X per 100m->km),reported,-0.13945947983338056,0.023243246638896764,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c3,3,Mod. 3,14,Bus,transit_distance,D_location,level,100 m,0.011,0.003,,,***,,,high,Linear distance to nearest public transport stop in 100 m units,ln transaction price (PLN),log,OLS,1825.0,0.883,se,Full sample; number of BTS,semi_elasticity,10.999999999999998,2.9999999999999996,100*b/0.1 (X per 100m->km),reported,0.08574929257125442,0.023386170701251208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6666666666666665,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c4,3,Mod. 4,14,BTS_Prox,hazard_site,E_environment,dummy,binary,-0.001,0.008,,,,,,high,Dummy = 1 if apartment within 200 m of a base transceiver station (cell phone tower),ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS proximity dummy,pct_premium,-0.10314676711368209,0.7992003998667,100*(exp(b - se^2/2) - 1),reported,-0.004354540053299681,0.03483632042639745,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.125,824.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c4,3,Mod. 4,14,Ln Area,living_area,A_structural,log,m2,0.882,0.023,,,***,,,high,Natural log of usable area in m2,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS proximity dummy,elasticity,0.882,0.023,b (log-log),reported,0.8005554908529765,0.02087616359367173,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),38.34782608695652,824.0,m2,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c4,3,Mod. 4,14,Rooms,bedrooms,A_structural,level,count,0.011,0.008,,,,,,high,Number of rooms (not bedrooms),ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS proximity dummy,semi_elasticity,1.0999999999999999,0.8,100*b/1 (per unit count),reported,0.047845536638266684,0.034796753918739404,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.375,824.0,count,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c4,3,Mod. 4,14,Floor2,floor_level,A_structural,dummy,binary,-0.007,0.013,,,,,,high,Dummy for 'other floors' (above 2nd); base = ground floor,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS proximity dummy,pct_premium,-0.7059464087071254,1.2909317758132055,100*(exp(b - se^2/2) - 1),reported,-0.018754897186581333,0.03483052334650818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5384615384615385,824.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c4,3,Mod. 4,14,Floor3,floor_level,A_structural,dummy,binary,0.037,0.013,,,**,,,high,Dummy for first or second floor; base = ground floor,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS proximity dummy,pct_premium,3.760533948248579,1.3490009270896042,100*(exp(b - se^2/2) - 1),reported,0.09866666666666667,0.034666666666666665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8461538461538463,824.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c4,3,Mod. 4,14,School,school_distance,D_location,level,100 m,-0.006,0.002,,,***,,,high,Linear distance to nearest elementary school in 100 m units,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS proximity dummy,semi_elasticity,-5.999999999999999,2.0,100*b/0.1 (X per 100m->km),reported,-0.10394383930128556,0.03464794643376185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,824.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c4,3,Mod. 4,14,Bus,transit_distance,D_location,level,100 m,0.013,0.004,,,***,,,high,Linear distance to nearest public transport stop in 100 m units,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS proximity dummy,semi_elasticity,13.0,4.0,100*b/0.1 (X per 100m->km),reported,0.11250036404577593,0.034615496629469514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.25,824.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c5,3,Mod. 5,14,BTS_Dist,hazard_site,E_environment,level,100 m,0.008,0.005,,,,,,high,Linear distance to nearest base transceiver station in 100 m units (Table 2 label is a copy-paste error),ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS distance,semi_elasticity,8.0,5.0,100*b/0.1 (X per 100m->km),reported,0.055652258075312155,0.03478266129707009,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6,824.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c5,3,Mod. 5,14,Ln Area,living_area,A_structural,log,m2,0.886,0.023,,,***,,,high,Natural log of usable area in m2,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS distance,elasticity,0.886,0.023,b (log-log),reported,0.8018536268449228,0.02081561333796075,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),38.52173913043478,824.0,m2,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c5,3,Mod. 5,14,Rooms,bedrooms,A_structural,level,count,0.01,0.008,,,,,,high,Number of rooms (not bedrooms),ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS distance,semi_elasticity,1.0,0.8,100*b/1 (per unit count),reported,0.04350458540743126,0.03480366832594501,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.25,824.0,count,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c5,3,Mod. 5,14,Floor2,floor_level,A_structural,dummy,binary,-0.007,0.013,,,,,,high,Dummy for 'other floors' (above 2nd); base = ground floor,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS distance,pct_premium,-0.7059464087071254,1.2909317758132055,100*(exp(b - se^2/2) - 1),reported,-0.018754897186581333,0.03483052334650818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5384615384615385,824.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c5,3,Mod. 5,14,Floor3,floor_level,A_structural,dummy,binary,0.037,0.013,,,**,,,high,Dummy for first or second floor; base = ground floor,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS distance,pct_premium,3.760533948248579,1.3490009270896042,100*(exp(b - se^2/2) - 1),reported,0.09866666666666667,0.034666666666666665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8461538461538463,824.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c5,3,Mod. 5,14,School,school_distance,D_location,level,100 m,-0.006,0.002,,,**,,,high,Linear distance to nearest elementary school in 100 m units,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS distance,semi_elasticity,-5.999999999999999,2.0,100*b/0.1 (X per 100m->km),reported,-0.10394383930128556,0.03464794643376185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,824.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c5,3,Mod. 5,14,Bus,transit_distance,D_location,level,100 m,0.011,0.004,,,**,,,high,Linear distance to nearest public transport stop in 100 m units,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; BTS distance,semi_elasticity,10.999999999999998,4.0,100*b/0.1 (X per 100m->km),reported,0.09536417273569421,0.0346778809947979,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.75,824.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c6,3,Mod. 6,14,Ln Area,living_area,A_structural,log,m2,0.88,0.023,,,***,,,high,Natural log of usable area in m2,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; number of BTS,elasticity,0.88,0.023,b (log-log),reported,0.7999021667095436,0.020906533902635797,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),38.26086956521739,824.0,m2,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c6,3,Mod. 6,14,Rooms,bedrooms,A_structural,level,count,0.011,0.008,,,,,,high,Number of rooms (not bedrooms),ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; number of BTS,semi_elasticity,1.0999999999999999,0.8,100*b/1 (per unit count),reported,0.047845536638266684,0.034796753918739404,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.375,824.0,count,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c6,3,Mod. 6,14,Floor2,floor_level,A_structural,dummy,binary,-0.007,0.013,,,,,,high,Dummy for 'other floors' (above 2nd); base = ground floor,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; number of BTS,pct_premium,-0.7059464087071254,1.2909317758132055,100*(exp(b - se^2/2) - 1),reported,-0.018754897186581333,0.03483052334650818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5384615384615385,824.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c6,3,Mod. 6,14,Floor3,floor_level,A_structural,dummy,binary,0.037,0.013,,,**,,,high,Dummy for first or second floor; base = ground floor,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; number of BTS,pct_premium,3.760533948248579,1.3490009270896042,100*(exp(b - se^2/2) - 1),reported,0.09866666666666667,0.034666666666666665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8461538461538463,824.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c6,3,Mod. 6,14,School,school_distance,D_location,level,100 m,-0.006,0.002,,,**,,,high,Linear distance to nearest elementary school in 100 m units,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; number of BTS,semi_elasticity,-5.999999999999999,2.0,100*b/0.1 (X per 100m->km),reported,-0.10394383930128556,0.03464794643376185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,824.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T3-c6,3,Mod. 6,14,Bus,transit_distance,D_location,level,100 m,0.013,0.004,,,***,,,high,Linear distance to nearest public transport stop in 100 m units,ln transaction price (PLN),log,OLS,834.0,0.875,se,CEM-matched sample; number of BTS,semi_elasticity,13.0,4.0,100*b/0.1 (X per 100m->km),reported,0.11250036404577593,0.034615496629469514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.25,824.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,ols,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c1,4,Mod. 7,16,Treatment (BTS_5G*after),hazard_site,E_environment,dummy,binary,-0.021,0.005,,,,,,medium,DiD interaction: within 200 m of a 5G BTS x after May 2020; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences (5G introduction) with BTS proximity dummy; quarterly FE,pct_premium,-2.079327559109634,0.4896094822847298,100*(exp(b - se^2/2) - 1),reported,-0.09810942031813139,0.02335938579003128,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.2,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c1,4,Mod. 7,16,BTS_Prox,hazard_site,E_environment,dummy,binary,0.026,0.005,,,,,,medium,Dummy = 1 if apartment within 200 m of a base transceiver station (cell phone tower); Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences (5G introduction) with BTS proximity dummy; quarterly FE,pct_premium,2.6328119291768814,0.513170474236721,100*(exp(b - se^2/2) - 1),reported,0.12115847973716586,0.023299707641762667,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.199999999999999,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c1,4,Mod. 7,16,Ln Area,living_area,A_structural,log,m2,0.919,0.019,,,*,,,medium,Natural log of usable area in m2; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences (5G introduction) with BTS proximity dummy; quarterly FE,elasticity,0.919,0.019,b (log-log),reported,0.7504163910550959,0.015514593503859437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),48.36842105263158,1815.0,m2,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c1,4,Mod. 7,16,Rooms,bedrooms,A_structural,level,count,0.007,0.009,,,,,,medium,Number of rooms (not bedrooms); Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences (5G introduction) with BTS proximity dummy; quarterly FE,semi_elasticity,0.7000000000000001,0.8999999999999999,100*b/1 (per unit count),reported,0.01825344547675407,0.023468715612969517,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7777777777777779,1815.0,count,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c1,4,Mod. 7,16,Floor2,floor_level,A_structural,dummy,binary,0.015,0.004,,,,,,medium,Dummy for 'other floors' (above 2nd); base = ground floor; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences (5G introduction) with BTS proximity dummy; quarterly FE,pct_premium,1.510494374368565,0.40604522584628755,100*(exp(b - se^2/2) - 1),reported,0.08768332190933387,0.023382219175822366,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.75,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c1,4,Mod. 7,16,Floor3,floor_level,A_structural,dummy,binary,0.077,0.007,,,,,,medium,Dummy for first or second floor; base = ground floor; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences (5G introduction) with BTS proximity dummy; quarterly FE,pct_premium,8.001561568587379,0.7560294534748203,100*(exp(b - se^2/2) - 1),reported,0.25,0.022727272727272728,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.0,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c1,4,Mod. 7,16,Bus,transit_distance,D_location,level,100 m,0.012,0.006,,,,,,medium,Linear distance to nearest public transport stop in 100 m units; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences (5G introduction) with BTS proximity dummy; quarterly FE,semi_elasticity,11.999999999999998,5.999999999999999,100*b/0.1 (X per 100m->km),reported,0.04689360772322401,0.02344680386161201,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c2,4,Mod. 8,16,Treatment (BTS_5G*after),hazard_site,E_environment,dummy,binary,-0.022,0.004,,,,,,medium,DiD interaction: within 200 m of a 5G BTS x after May 2020; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with BTS distance; quarterly FE,pct_premium,-2.1767590839366746,0.39129609402048404,100*(exp(b - se^2/2) - 1),reported,-0.12803687993289598,0.023279432715071994,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.5,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c2,4,Mod. 8,16,BTS_Dist,hazard_site,E_environment,level,100 m,0.01,0.011,,,,,,medium,Linear distance to nearest base transceiver station in 100 m units (Table 2 label is a copy-paste error); Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with BTS distance; quarterly FE,semi_elasticity,10.0,10.999999999999998,100*b/0.1 (X per 100m->km),reported,0.021333894659190798,0.023467284125109875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9090909090909092,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c2,4,Mod. 8,16,Ln Area,living_area,A_structural,log,m2,0.916,0.015,,,*,,,medium,Natural log of usable area in m2; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with BTS distance; quarterly FE,elasticity,0.916,0.015,b (log-log),reported,0.8201385147566828,0.013430215853002449,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),61.06666666666667,1815.0,m2,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c2,4,Mod. 8,16,Rooms,bedrooms,A_structural,level,count,0.007,0.008,,,,,,medium,Number of rooms (not bedrooms); Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with BTS distance; quarterly FE,semi_elasticity,0.7000000000000001,0.8,100*b/1 (per unit count),reported,0.02053421751014348,0.023467677154449692,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.875,1815.0,count,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c2,4,Mod. 8,16,Floor2,floor_level,A_structural,dummy,binary,0.015,0.005,,,,,,medium,Dummy for 'other floors' (above 2nd); base = ground floor; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with BTS distance; quarterly FE,pct_premium,1.5100375781716746,0.5075565323078595,100*(exp(b - se^2/2) - 1),reported,0.07024393586862705,0.02341464528954235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c2,4,Mod. 8,16,Floor3,floor_level,A_structural,dummy,binary,0.077,0.005,,,*,,,medium,Dummy for first or second floor; base = ground floor; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with BTS distance; quarterly FE,pct_premium,8.00285759510233,0.5400210381963002,100*(exp(b - se^2/2) - 1),reported,0.3399500518250425,0.022074678689937823,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.4,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c2,4,Mod. 8,16,School,school_distance,D_location,level,100 m,-0.005,0.001,,,,,,medium,Linear distance to nearest elementary school in 100 m units; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with BTS distance; quarterly FE,semi_elasticity,-5.0,1.0,100*b/0.1 (X per 100m->km),reported,-0.11656310103003922,0.023312620206007845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c2,4,Mod. 8,16,Bus,transit_distance,D_location,level,100 m,0.007,0.006,,,,,,medium,Linear distance to nearest public transport stop in 100 m units; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with BTS distance; quarterly FE,semi_elasticity,7.0,5.999999999999999,100*b/0.1 (X per 100m->km),reported,0.0273744682761948,0.02346382995102411,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1666666666666667,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c3,4,Mod. 9,16,Treatment (BTS_5G*after),hazard_site,E_environment,dummy,binary,-0.022,0.005,,,,,,medium,DiD interaction: within 200 m of a 5G BTS x after May 2020; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with number of BTS; quarterly FE,pct_premium,-2.1771992875303403,0.489120117525605,100*(exp(b - se^2/2) - 1),reported,-0.10273309938750282,0.023348431678977915,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.3999999999999995,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c3,4,Mod. 9,16,Ln Area,living_area,A_structural,log,m2,0.915,0.02,,,*,,,medium,Natural log of usable area in m2; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with number of BTS; quarterly FE,elasticity,0.915,0.02,b (log-log),reported,0.7318302350759097,0.015996289291276715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),45.75,1815.0,m2,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c3,4,Mod. 9,16,Rooms,bedrooms,A_structural,level,count,0.007,0.009,,,,,,medium,Number of rooms (not bedrooms); Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with number of BTS; quarterly FE,semi_elasticity,0.7000000000000001,0.8999999999999999,100*b/1 (per unit count),reported,0.01825344547675407,0.023468715612969517,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7777777777777779,1815.0,count,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c3,4,Mod. 9,16,Floor2,floor_level,A_structural,dummy,binary,0.014,0.005,,,,,,medium,Dummy for 'other floors' (above 2nd); base = ground floor; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with number of BTS; quarterly FE,pct_premium,1.4085782786981804,0.5070492294692461,100*(exp(b - se^2/2) - 1),reported,0.06558186400955365,0.023422094289126304,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c3,4,Mod. 9,16,Floor3,floor_level,A_structural,dummy,binary,0.077,0.006,,,,,,medium,Dummy for first or second floor; base = ground floor; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with number of BTS; quarterly FE,pct_premium,8.002263581019097,0.6480252458355603,100*(exp(b - se^2/2) - 1),reported,0.2884299752006152,0.02247506300264534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.833333333333332,1815.0,binary,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c3,4,Mod. 9,16,School,school_distance,D_location,level,100 m,-0.006,0.001,,,,,,medium,Linear distance to nearest elementary school in 100 m units; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with number of BTS; quarterly FE,semi_elasticity,-5.999999999999999,1.0,100*b/0.1 (X per 100m->km),reported,-0.13945947983338056,0.023243246638896764,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9,52cbefc12720084fe56091430bf37e9fbeba96b9:T4-c3,4,Mod. 9,16,Bus,transit_distance,D_location,level,100 m,0.013,0.005,,,,,,medium,Linear distance to nearest public transport stop in 100 m units; Table 4 stars inconsistent with printed SEs; DiD specification,ln transaction price (PLN),log,other,1825.0,,se,Difference-in-differences with number of BTS; quarterly FE,semi_elasticity,13.0,5.0,100*b/0.1 (X per 100m->km),reported,0.0609154934940191,0.023429035959238117,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5999999999999996,1815.0,100m,,2024.0,Poland,Europe,High income,2016.0,2021.0,condo_apartment,transaction,journal,True,False,unknown,,2018.5,other,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,bathrooms,bathrooms,A_structural,level,count,0.1798,0.0024,,,**,,,high,,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,semi_elasticity,17.98,0.24,100*b/1 (per unit count),reported,0.31204036883855796,0.004165166213640372,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),74.91666666666667,52029.0,count,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,bedrooms,bedrooms,A_structural,level,count,0.0814,0.0021,,,**,,,high,,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,semi_elasticity,8.14,0.21,100*b/1 (per unit count),reported,0.16753303783095905,0.004322105398587395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),38.761904761904766,52029.0,count,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,building_type,dwelling_type,A_structural,dummy,binary,0.0874,0.0057,,,**,,,high,"1 = house, 0 = apartment","ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,pct_premium,9.131539711091087,0.622059881633916,100*(exp(b - se^2/2) - 1),reported,0.06707100172830727,0.004374195764889604,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.333333333333334,52029.0,binary,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,parking_lots,parking,A_structural,level,count,0.0159,0.0013,,,**,,,high,Number of parking lots,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,semi_elasticity,1.59,0.13,100*b/1 (per unit count),reported,0.053543603414987824,0.004377778895565042,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.230769230769232,52029.0,count,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,swimpool,pool,C_exterior,dummy,binary,0.0002,0.0034,,,,,,high,,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,pct_premium,0.019423886192537765,0.34006800680045335,100*(exp(b - se^2/2) - 1),reported,0.000257886331806303,0.004384067640707151,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.05882352941176471,52029.0,binary,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,terrace,terrace_balcony,C_exterior,dummy,binary,0.0582,0.0032,,,**,,,high,,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,pct_premium,5.992153309300052,0.33917662716964564,100*(exp(b - se^2/2) - 1),reported,0.07948296846051685,0.004370197578585119,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.1875,52029.0,binary,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,new_house,age,A_structural,dummy,binary,0.0753,0.0073,,,**,,,high,1 = new construction home,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,pct_premium,7.817883618171129,0.7870915221868603,100*(exp(b - se^2/2) - 1),reported,0.045175790264248776,0.004379591884847491,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.315068493150685,52029.0,binary,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,dist_subway,transit_distance,D_location,level,km,0.0045,0.0011,,,**,,,high,Min geodesic distance to subway,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,semi_elasticity,0.44999999999999996,0.11,100*b/1 (X per km->km),reported,0.01793193902015316,0.004383362871592996,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.09090909090909,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,dist_park,green_space,E_environment,level,km,-0.0019,0.0017,,,,,,high,Min geodesic distance to park,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,semi_elasticity,-0.19,0.16999999999999998,100*b/1 (X per km->km),reported,-0.00489978164955706,0.004384015160130001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1176470588235294,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,dist_hospital,hospital_distance,D_location,level,km,0.0038,0.001,,,**,,,high,Min geodesic distance to hospital or health clinic,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,semi_elasticity,0.38,0.1,100*b/1 (X per km->km),reported,0.01665714625742714,0.004383459541428195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,dist_university,university_distance,D_location,level,km,-0.0176,0.0013,,,**,,,high,,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,semi_elasticity,-1.76,0.13,100*b/1 (X per km->km),reported,-0.05924926197025383,0.0043763659409846575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.53846153846154,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,dist_mall,commercial_distance,D_location,level,km,-0.0039,0.0014,,,**,,,high,Min geodesic distance to mall,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,semi_elasticity,-0.38999999999999996,0.13999999999999999,100*b/1 (X per km->km),reported,-0.012211849588395786,0.0043837408778856675,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.7857142857142856,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,dist_penitentiary,hazard_site,E_environment,level,km,-0.005,0.0006,,,**,,,high,Min geodesic distance to penitentiary,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,semi_elasticity,-0.5,0.06,100*b/1 (X per km->km),reported,-0.03650954123366662,0.004381144948039994,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.333333333333334,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,True
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,dist_industry,hazard_site,E_environment,level,km,0.0096,0.0009,,,**,,,high,Min geodesic distance to industry,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,semi_elasticity,0.96,0.09,100*b/1 (X per km->km),reported,0.04671234199911687,0.004379282062417207,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.666666666666666,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-OLS,8,OLS,20,dist_dump,hazard_site,E_environment,level,km,0.0019,0.0005,,,**,,,high,Min geodesic distance to dump,"ln(listing price, UF)",log,OLS,52039.0,0.8654,se,Full filtered dataset (assumed); SE in separate column,semi_elasticity,0.19,0.05,100*b/1 (X per km->km),reported,0.01665714625742714,0.004383459541428195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,ols,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,bathrooms,bathrooms,A_structural,level,count,0.1712,0.0023,,,**,,,high,,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),semi_elasticity,17.119999999999997,0.22999999999999998,100*b/1 (per unit count),reported,0.310226973864136,0.004167768924576593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),74.43478260869566,52029.0,count,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,bedrooms,bedrooms,A_structural,level,count,0.0752,0.0021,,,**,,,high,,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),semi_elasticity,7.5200000000000005,0.21,100*b/1 (per unit count),reported,0.15509179405278947,0.00433102084455928,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.80952380952381,52029.0,count,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,building_type,dwelling_type,A_structural,dummy,binary,0.0957,0.0055,,,**,,,high,"1 = house, 0 = apartment","ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),pct_premium,10.041224194295717,0.6052358871921919,100*(exp(b - se^2/2) - 1),reported,0.0760617963260054,0.00437136760494284,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.4,52029.0,binary,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,parking_lots,parking,A_structural,level,count,0.0139,0.0012,,,**,,,high,Number of parking lots,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),semi_elasticity,1.39,0.12,100*b/1 (per unit count),reported,0.05071676583760077,0.004378425827706541,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.583333333333334,52029.0,count,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,swimpool,pool,C_exterior,dummy,binary,0.0021,0.0033,,,,,,high,,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),pct_premium,0.20967501126512023,0.3306937281596225,100*(exp(b - se^2/2) - 1),reported,0.0027898504615379797,0.004384050725273968,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6363636363636364,52029.0,binary,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,terrace,terrace_balcony,C_exterior,dummy,binary,0.0465,0.0031,,,**,,,high,,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),pct_premium,4.759304537185738,0.32475540451124546,100*(exp(b - se^2/2) - 1),reported,0.0656192841941052,0.00437461894627368,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.0,52029.0,binary,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,new_house,age,A_structural,dummy,binary,0.0668,0.007,,,**,,,high,1 = new construction home,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),pct_premium,6.905544828411325,0.7483571483244144,100*(exp(b - se^2/2) - 1),reported,0.04179996743742738,0.00438023610871245,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.542857142857143,52029.0,binary,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,dist_subway,transit_distance,D_location,level,km,0.0054,0.001,,,**,,,high,Min geodesic distance to subway,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),semi_elasticity,0.54,0.1,100*b/1 (X per km->km),reported,0.023667334718271392,0.00438283976264285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.4,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,dist_park,green_space,E_environment,level,km,0.0087,0.0016,,,**,,,high,Min geodesic distance to park,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),semi_elasticity,0.8699999999999999,0.16,100*b/1 (X per km->km),reported,0.02383159818561065,0.004382822654824948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.437499999999999,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,dist_hospital,hospital_distance,D_location,level,km,-0.0084,0.0009,,,**,,,high,Min geodesic distance to hospital or health clinic,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),semi_elasticity,-0.84,0.09,100*b/1 (X per km->km),reported,-0.040883754895596695,0.004380402310242504,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.333333333333332,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,dist_university,university_distance,D_location,level,km,-0.0121,0.0011,,,**,,,high,,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),semi_elasticity,-1.21,0.11,100*b/1 (X per km->km),reported,-0.04816876690828824,0.004378978809844386,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.999999999999998,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,dist_mall,commercial_distance,D_location,level,km,0.0052,0.0013,,,**,,,high,Min geodesic distance to mall,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),semi_elasticity,0.52,0.13,100*b/1 (X per km->km),reported,0.01753357538357703,0.0043833938458942585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,dist_penitentiary,hazard_site,E_environment,level,km,-0.0035,0.0006,,,**,,,high,Min geodesic distance to penitentiary,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),semi_elasticity,-0.35000000000000003,0.06,100*b/1 (X per km->km),reported,-0.02556537004553264,0.004382634864948452,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.833333333333334,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,dist_industry,hazard_site,E_environment,level,km,-0.0006,0.0009,,,,,,high,Min geodesic distance to industry,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),semi_elasticity,-0.06,0.09,100*b/1 (X per km->km),reported,-0.0029226993744796174,0.0043840490617194266,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6666666666666666,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d,53d1b6d48e64b056e88ebabd287c3f06ec3b559d:T8-SAR,8,SAR,20,dist_dump,hazard_site,E_environment,level,km,-0.0045,0.0005,,,**,,,high,Min geodesic distance to dump,"ln(listing price, UF)",log,spatial_lag,52039.0,0.8774,se,Full filtered dataset (assumed); KNN spatial weights; rho = 0.4271 (0.0080),semi_elasticity,-0.44999999999999996,0.05,100*b/1 (X per km->km),reported,-0.03942593239325762,0.0043806591548064015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.0,52029.0,km,,2025.0,Chile,South America,High income,2020.0,2020.0,mixed,listing,journal,False,False,unknown,LightGBM (DART) AVM;SHAP / TreeSHAP;CNN (DenseNet201) image classification into 16 photo-feature indicators;Extended Isolation Forest outlier removal,2020.0,spatial,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T6,6,1,15,to be partially renovated,condition,A_structural,binary,binary,0.07,0.04,1.81,0.07,.,,,high,apartment condition dummy (ref: to be completely renovated),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,573.0,0.77,se,"all listings (Model 1, without EPC)",pct_premium,7.165051782032883,4.290032725016866,100*(exp(b - se^2/2) - 1),reported,0.07606142519023683,0.04202288684543471,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.81,563.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T6,6,1,15,good,condition,A_structural,binary,binary,0.17,0.04,4.67,3.73e-06,***,,,high,apartment condition dummy (ref: to be completely renovated),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,573.0,0.77,se,"all listings (Model 1, without EPC)",pct_premium,18.435698663573596,4.741219405281462,100*(exp(b - se^2/2) - 1),reported,0.1931122810927704,0.041351666186888736,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.67,563.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T6,6,1,15,refurbished,condition,A_structural,binary,binary,0.28,0.04,7.25,1.45e-12,***,,,high,apartment condition dummy (ref: to be completely renovated),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,573.0,0.77,se,"all listings (Model 1, without EPC)",pct_premium,32.20717317762225,5.292519249349748,100*(exp(b - se^2/2) - 1),reported,0.2922146122842764,0.040305463763348474,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.25,563.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T6,6,1,15,council housing,condition,A_structural,binary,binary,-0.08,0.05,-1.5,0.13,,,,high,building quality level dummy (ref: economical),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,573.0,0.77,se,"all listings (Model 1, without EPC)",pct_premium,-7.803682816210166,4.615581731933179,100*(exp(b - se^2/2) - 1),reported,-0.06309151753013043,0.042061011686753615,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5,563.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T6,6,1,15,medium-level,condition,A_structural,binary,binary,0.11,0.02,4.46,1.01e-05,***,,,high,building quality level dummy (ref: economical),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,573.0,0.77,se,"all listings (Model 1, without EPC)",pct_premium,11.605483716885256,2.2325561409177426,100*(exp(b - se^2/2) - 1),reported,0.18473150155107676,0.04141961918185577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.46,563.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T6,6,1,15,distinguished,condition,A_structural,binary,binary,0.25,0.03,7.17,2.59e-12,***,,,high,building quality level dummy (ref: economical),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,573.0,0.77,se,"all listings (Model 1, without EPC)",pct_premium,28.344773523830646,3.852076250063224,100*(exp(b - se^2/2) - 1),reported,0.28926134860420927,0.04034328432415749,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.17,563.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T6,6,1,15,classy,condition,A_structural,binary,binary,0.46,0.07,6.2,1.15e-09,***,,,high,building quality level dummy (ref: economical),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,573.0,0.77,se,"all listings (Model 1, without EPC)",pct_premium,58.019775405307136,11.088517894961374,100*(exp(b - se^2/2) - 1),reported,0.2528107489944396,0.04077592725716768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.2,563.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T7,7,1,17,to be partially renovated,condition,A_structural,binary,binary,0.08,0.04,1.76,0.08,.,,,high,apartment condition dummy (ref: to be completely renovated),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.79,se,listings with EPC level (Model 2),pct_premium,8.242078458025826,4.3331482706998345,100*(exp(b - se^2/2) - 1),reported,0.08117431843183974,0.046121771836272585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.76,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T7,7,1,17,good,condition,A_structural,binary,binary,0.16,0.04,3.98,8.09e-05,***,,,high,apartment condition dummy (ref: to be completely renovated),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.79,se,listings with EPC level (Model 2),pct_premium,17.257243771837594,4.694043483967241,100*(exp(b - se^2/2) - 1),reported,0.1811261982373892,0.04550909503451989,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.98,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T7,7,1,17,refurbished,condition,A_structural,binary,binary,0.26,0.05,5.78,1.48e-08,***,,,high,apartment condition dummy (ref: to be completely renovated),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.79,se,listings with EPC level (Model 2),pct_premium,29.5309936862024,6.484650433328859,100*(exp(b - se^2/2) - 1),reported,0.2583839557306619,0.044703106527796174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.78,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T7,7,1,17,council housing,condition,A_structural,binary,binary,-0.06,0.06,-0.95,0.34,,,,high,building quality level dummy (ref: economical),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.79,se,listings with EPC level (Model 2),pct_premium,-5.992911783264187,5.650587201505492,100*(exp(b - se^2/2) - 1),reported,-0.0439183405999402,0.046229832210463374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.95,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T7,7,1,17,medium-level,condition,A_structural,binary,binary,0.1,0.03,3.74,0.0,***,,,high,building quality level dummy (ref: economical),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.79,se,listings with EPC level (Model 2),pct_premium,10.467370304428613,3.3155127542269427,100*(exp(b - se^2/2) - 1),reported,0.17053151960129123,0.04559666299499766,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.74,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T7,7,1,17,distinguished,condition,A_structural,binary,binary,0.24,0.04,6.05,3.21e-09,***,,,high,building quality level dummy (ref: economical),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.79,se,listings with EPC level (Model 2),pct_premium,27.02325576924174,5.084996601285619,100*(exp(b - se^2/2) - 1),reported,0.2695947533059062,0.04456111624891012,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.05,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T7,7,1,17,classy,condition,A_structural,binary,binary,0.49,0.08,5.85,9.77e-09,***,,,high,building quality level dummy (ref: economical),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.79,se,listings with EPC level (Model 2),pct_premium,62.71011566030722,13.058529759643031,100*(exp(b - se^2/2) - 1),reported,0.26130070827104634,0.044666787738640405,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.85,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T7,7,1,17,C,energy_efficiency,A_structural,binary,binary,-0.03,0.07,-0.41,0.68,,,,high,EPC level dummy (ref: B),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.79,se,listings with EPC level (Model 2),pct_premium,-3.1929147836154192,6.793118734839558,100*(exp(b - se^2/2) - 1),reported,-0.018969123619803577,0.046266155170252635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.41,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T7,7,1,17,D,energy_efficiency,A_structural,binary,binary,-0.1,0.067,-1.42,0.15,,,,high,EPC level dummy (ref: B),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.79,se,listings with EPC level (Model 2),pct_premium,-9.719121206703974,6.062410700840929,100*(exp(b - se^2/2) - 1),reported,-0.06556836132085773,0.0461749023386322,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.42,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T7,7,1,17,E,energy_efficiency,A_structural,binary,binary,-0.06,0.07,-0.92,0.36,,,,high,EPC level dummy (ref: B),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.79,se,listings with EPC level (Model 2),pct_premium,-6.053996535909767,6.592351735089741,100*(exp(b - se^2/2) - 1),reported,-0.04253399555447309,0.04623260386355771,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.92,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T7,7,1,17,F,energy_efficiency,A_structural,binary,binary,-0.14,0.07,-2.01,0.04,*,,,high,EPC level dummy (ref: B),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.79,se,listings with EPC level (Model 2),pct_premium,-13.276908524602792,6.085507647791641,100*(exp(b - se^2/2) - 1),reported,-0.09261196887921094,0.04607560640756764,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.01,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,True
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T7,7,1,17,G,energy_efficiency,A_structural,binary,binary,-0.1,0.07,-1.45,0.15,,,,high,EPC level dummy (ref: B),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.79,se,listings with EPC level (Model 2),pct_premium,-9.737672021134525,6.333861926251717,100*(exp(b - se^2/2) - 1),reported,-0.0669474637102453,0.04617066462775539,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.45,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T8,8,1,18,to be completely renovated,condition,A_structural,binary,binary,0.21,0.13,1.63,0.1,,,,medium,apartment condition dummy; reference category unclear in Table 8,log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.78,se,"listings with EPC level (Model 2, EPC grouped)",pct_premium,22.32974004037336,16.03781477943766,100*(exp(b - se^2/2) - 1),reported,0.07521375148565196,0.046143405819418386,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.63,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T8,8,1,18,to be partially renovated,condition,A_structural,binary,binary,0.07,0.04,1.75,0.08,.,,,medium,apartment condition dummy (ref: to be completely renovated),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.78,se,"listings with EPC level (Model 2, EPC grouped)",pct_premium,7.165051782032883,4.290032725016866,100*(exp(b - se^2/2) - 1),reported,0.08071611411802512,0.046123493781728635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.75,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T8,8,1,18,good,condition,A_structural,binary,binary,0.16,0.04,3.9,0.0,***,,,medium,apartment condition dummy (ref: to be completely renovated),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.78,se,"listings with EPC level (Model 2, EPC grouped)",pct_premium,17.257243771837594,4.694043483967241,100*(exp(b - se^2/2) - 1),reported,0.17760144738413128,0.04553883266259776,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T8,8,1,18,refurbished,condition,A_structural,binary,binary,0.26,0.04,5.66,2.72e-08,***,,,medium,apartment condition dummy (ref: to be completely renovated),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.78,se,"listings with EPC level (Model 2, EPC grouped)",pct_premium,29.58929575034177,5.187720346663087,100*(exp(b - se^2/2) - 1),reported,0.2533673604735399,0.04476455132041341,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.66,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T8,8,1,18,medium-level,condition,A_structural,binary,binary,0.1,0.03,3.77,0.0,***,,,medium,building quality level dummy (ref: economical),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.78,se,"listings with EPC level (Model 2, EPC grouped)",pct_premium,10.467370304428613,3.3155127542269427,100*(exp(b - se^2/2) - 1),reported,0.17185917381878166,0.045585987750339965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.77,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T8,8,1,18,council housing,condition,A_structural,binary,binary,-0.05,0.06,-0.91,0.36,,,,medium,building quality level dummy (ref: economical),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.78,se,"listings with EPC level (Model 2, EPC grouped)",pct_premium,-5.048124839589862,5.7073765470042845,100*(exp(b - se^2/2) - 1),reported,-0.042072492365109654,0.046233508093527095,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.91,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T8,8,1,18,classy,condition,A_structural,binary,binary,0.49,0.08,5.91,6.82e-09,***,,,medium,building quality level dummy (ref: economical),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.78,se,"listings with EPC level (Model 2, EPC grouped)",pct_premium,62.71011566030722,13.058529759643031,100*(exp(b - se^2/2) - 1),reported,0.26379510100141085,0.044635380880103354,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.91,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T8,8,1,18,distinguished,condition,A_structural,binary,binary,0.24,0.04,6.08,2.61e-09,***,,,medium,building quality level dummy (ref: economical),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.78,se,"listings with EPC level (Model 2, EPC grouped)",pct_premium,27.02325576924174,5.084996601285619,100*(exp(b - se^2/2) - 1),reported,0.27083375308016094,0.04454502517765805,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.08,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T8,8,1,18,DE,energy_efficiency,A_structural,binary,binary,-0.06,0.03,-1.77,0.08,.,,,medium,EPC cluster dummy (ref: B-C),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.78,se,"listings with EPC level (Model 2, EPC grouped)",pct_premium,-5.86591651165066,2.825293600752746,100*(exp(b - se^2/2) - 1),reported,-0.08163247128437198,0.04612004027365649,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.77,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a,53f863bd54970307af93c0ba10a947b3b65b890a:T8,8,1,18,FG,energy_efficiency,A_structural,binary,binary,-0.09,0.03,-2.65,0.01,**,,,medium,EPC cluster dummy (ref: B-C),log listing price per m2 (text says 'log listing price'; intercepts 7.95-8.04 and absence of size regressor imply price per m2; intercepts of Tables 6-7 misprinted as 785.08 / 79620.42),log,OLS,477.0,0.78,se,"listings with EPC level (Model 2, EPC grouped)",pct_premium,-8.647999124049011,2.741793555813685,100*(exp(b - se^2/2) - 1),reported,-0.12171564243992926,0.04593043110940727,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.65,467.0,binary,,2014.0,Italy,Europe,High income,2012.0,2012.0,condo_apartment,listing,journal,False,True,OLS,,2012.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c1,3,1,14,PM2.5,air_pollution,E_environment,level,ug/m3,-0.00074,5.64e-05,,,***,,,high,"Quarterly mean PM2.5 concentration, kriged to community; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.458,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",semi_elasticity,-0.074,0.00564,100*b/1 (per ug/m3),reported,-0.07147212642992243,0.00544733504141571,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.120567375886525,33528.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c2,3,2,14,PM2.5,air_pollution,E_environment,level,ug/m3,-0.000104,1.83e-05,,,***,,,high,"Quarterly mean PM2.5 concentration, kriged to community; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",semi_elasticity,-0.0104,0.00183,100*b/1 (per ug/m3),reported,-0.031021968367700405,0.005458673280085745,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.683060109289617,33528.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c3,3,3,14,PM2.5,air_pollution,E_environment,level,ug/m3,-0.000852,4.89e-05,,,***,,,high,"Quarterly mean PM2.5 concentration, kriged to community; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.83,se,"(4) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",semi_elasticity,-0.0852,0.00489,100*b/1 (per ug/m3),reported,-0.09472609793992734,0.005436744353594422,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.42331288343558,33528.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c1,3,1,14,School,school_distance,D_location,log,m,0.00109,0.00152,,,,,,high,"log distance (m) to nearest school; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.458,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.00109,0.00152,b (log-log),reported,0.003916298223133659,0.005461259907489139,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7171052631578947,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c2,3,2,14,School,school_distance,D_location,log,m,-0.0005,0.000621,,,,,,high,"log distance (m) to nearest school; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.0005,0.000621,b (log-log),reported,-0.004397140895118323,0.005461248991736957,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8051529790660226,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c3,3,3,14,School,school_distance,D_location,log,m,-0.000619,0.000639,,,,,,high,"log distance (m) to nearest school; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.83,se,"(4) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.000619,0.000639,b (log-log),reported,-0.005290294993490464,0.005461225364847184,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9687010954616587,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c1,3,1,14,Hospital,hospital_distance,D_location,log,m,0.00259,0.00193,,,,,,high,"log distance (m) to nearest hospital; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.458,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.00259,0.00193,b (log-log),reported,0.007328700399422827,0.0054611551238942305,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3419689119170983,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c2,3,2,14,Hospital,hospital_distance,D_location,log,m,9.56e-06,0.00149,,,,,,high,"log distance (m) to nearest hospital; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,9.56e-06,0.00149,b (log-log),reported,3.504029870338062e-05,0.005461301785359533,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.006416107382550336,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c3,3,3,14,Hospital,hospital_distance,D_location,log,m,-9.38e-05,0.00153,,,,,,high,"log distance (m) to nearest hospital; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.83,se,"(4) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-9.38e-05,0.00153,b (log-log),reported,-0.00033481704514238154,0.005461301482599613,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.06130718954248367,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c1,3,1,14,Park,green_space,E_environment,log,m,-0.00214,0.00207,,,,,,high,"log distance (m) to nearest city park; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.458,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.00214,0.00207,b (log-log),reported,-0.005645893504989894,0.005461214745480877,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.033816425120773,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c2,3,2,14,Park,green_space,E_environment,log,m,-0.000844,0.00128,,,,,,high,"log distance (m) to nearest city park; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.000844,0.00128,b (log-log),reported,-0.003601022518821679,0.005461266379255627,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6593749999999999,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c3,3,3,14,Park,green_space,E_environment,log,m,-0.000768,0.00132,,,,,,high,"log distance (m) to nearest city park; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.83,se,"(4) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.000768,0.00132,b (log-log),reported,-0.003177468636598186,0.0054612742191531335,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5818181818181818,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c1,3,1,14,Shopping mall,commercial_distance,D_location,log,m,0.00255,0.00236,,,,,,high,"log distance (m) to nearest shopping mall; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.458,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.00255,0.00236,b (log-log),reported,0.0059008801267764555,0.005461206705565661,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0805084745762712,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c2,3,2,14,Shopping mall,commercial_distance,D_location,log,m,-0.000897,0.00117,,,,,,high,"log distance (m) to nearest shopping mall; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.000897,0.00117,b (log-log),reported,-0.004186961337463291,0.00546125391843038,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7666666666666666,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c3,3,3,14,Shopping mall,commercial_distance,D_location,log,m,-0.000798,0.0012,,,,,,high,"log distance (m) to nearest shopping mall; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.83,se,"(4) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.000798,0.0012,b (log-log),reported,-0.0036317417387406498,0.00546126577254233,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.665,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c1,3,1,14,Farmer’s market,commercial_distance,D_location,log,m,0.00031,0.00185,,,,,,high,"log distance (m) to nearest farmers' market; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.458,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.00031,0.00185,b (log-log),reported,0.0009151366732845805,0.005461299501859594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.16756756756756755,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c2,3,2,14,Farmer’s market,commercial_distance,D_location,log,m,0.000366,0.000826,,,,,,high,"log distance (m) to nearest farmers' market; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.000366,0.000826,b (log-log),reported,0.0024198917702067052,0.005461285798335352,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4430992736077482,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c3,3,3,14,Farmer’s market,commercial_distance,D_location,log,m,0.000478,0.00085,,,,,,high,"log distance (m) to nearest farmers' market; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.83,se,"(4) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.000478,0.00085,b (log-log),reported,0.003071164639739549,0.0054612760330096585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5623529411764706,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c1,3,1,14,Leisure facilities,neighbourhood_amenities,F_neighbourhood,log,count,0.0113,0.00195,,,***,,,high,"log number of sport/leisure facilities within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.458,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.0113,0.00195,b (log-log),reported,0.03163170702576583,0.005458568911525961,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.794871794871795,33528.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c2,3,2,14,Leisure facilities,neighbourhood_amenities,F_neighbourhood,log,count,-0.00154,0.000812,,,*,,,high,"log number of sport/leisure facilities within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.00154,0.000812,b (log-log),reported,-0.010357085780438022,0.005461008866049139,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8965517241379308,33528.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c3,3,3,14,Leisure facilities,neighbourhood_amenities,F_neighbourhood,log,count,-0.00136,0.000834,,,,,,high,"log number of sport/leisure facilities within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.83,se,"(4) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.00136,0.000834,b (log-log),reported,-0.008905366799678157,0.005461085228626163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.630695443645084,33528.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c1,3,1,14,Basic services,neighbourhood_amenities,F_neighbourhood,log,count,0.00384,0.00185,,,**,,,high,"log number of basic services (restaurant, post office...) within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.458,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.00384,0.00185,b (log-log),reported,0.011335163005747976,0.005460950927248374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.075675675675676,33528.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c2,3,2,14,Basic services,neighbourhood_amenities,F_neighbourhood,log,count,0.000859,0.000733,,,,,,high,"log number of basic services (restaurant, post office...) within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.000859,0.000733,b (log-log),reported,0.006399948376672974,0.005461189941910699,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1718963165075034,33528.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c3,3,3,14,Basic services,neighbourhood_amenities,F_neighbourhood,log,count,0.000895,0.000753,,,,,,high,"log number of basic services (restaurant, post office...) within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.83,se,"(4) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.000895,0.000753,b (log-log),reported,0.006491051962491488,0.005461186734923006,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1885790172642763,33528.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c1,3,1,14,Population,density,F_neighbourhood,log,per_km2,0.19,0.00186,,,***,,,high,"log population density (people/km2); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.458,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.19,0.00186,b (log-log),reported,0.48718994730158693,0.004769333168320799,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),102.1505376344086,33528.0,per_km2,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c2,3,2,14,Population,density,F_neighbourhood,log,per_km2,-0.00397,0.00439,,,,,,high,"log population density (people/km2); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.00397,0.00439,b (log-log),reported,-0.004938747991329998,0.005461235184367429,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9043280182232346,33528.0,per_km2,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c3,3,3,14,Population,density,F_neighbourhood,log,per_km2,-0.0041,0.00452,,,,,,high,"log population density (people/km2); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.83,se,"(4) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.0041,0.00452,b (log-log),reported,-0.004953774909646831,0.00546123477843992,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9070796460176993,33528.0,per_km2,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c1,3,1,14,D_Bus stop,transit_distance,D_location,log,m,0.00146,0.00195,,,,,,high,"log distance (m) to nearest bus stop; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.458,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.00146,0.00195,b (log-log),reported,0.004088940489759693,0.005461256133583152,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7487179487179487,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c2,3,2,14,D_Bus stop,transit_distance,D_location,log,m,-0.00187,0.00108,,,*,,,high,"log distance (m) to nearest bus stop; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.00187,0.00108,b (log-log),reported,-0.009455720162574455,0.0054610576340002204,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7314814814814814,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c3,3,3,14,D_Bus stop,transit_distance,D_location,log,m,-0.002,0.00111,,,*,,,high,"log distance (m) to nearest bus stop; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.83,se,"(4) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.002,0.00111,b (log-log),reported,-0.009839707029090443,0.005461037401145197,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8018018018018016,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c1,3,1,14,D_Metro station,transit_distance,D_location,log,m,0.00111,0.00239,,,,,,high,"log distance (m) to nearest metro station; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.458,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,0.00111,0.00239,b (log-log),reported,0.002536412337111685,0.005461284221348583,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.46443514644351463,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c2,3,2,14,D_Metro station,transit_distance,D_location,log,m,-0.000214,0.00229,,,,,,high,"log distance (m) to nearest metro station; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.000214,0.00229,b (log-log),reported,-0.0005103573932661442,0.00546130107747416,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.09344978165938865,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c3,3,3,14,D_Metro station,transit_distance,D_location,log,m,-0.00012,0.00235,,,,,,high,"log distance (m) to nearest metro station; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.83,se,"(4) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.00012,0.00235,b (log-log),reported,-0.0002788749741112926,0.005461301576346147,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.05106382978723404,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T3-c1,3,1,14,D_CBD,cbd_distance,D_location,log,m,-0.0162,0.00241,,,***,,,high,"log distance (m) to nearest urban centre/subcentre (time-invariant; dropped in FE models); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.458,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); main models; year FE in all, community FE in FE/FE2sls (PM2.5 instrumented by thermal inversions); adjusted R2; SE clustered at community level",elasticity,-0.0162,0.00241,b (log-log),reported,-0.03668611296855124,0.005457625447790648,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.721991701244813,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c1,9,1,19,School,school_distance,D_location,log,m,0.00111,0.00152,,,,,,high,"log distance (m) to nearest school; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.455,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.00111,0.00152,b (log-log),reported,0.0039881557734834094,0.005461258356481786,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7302631578947368,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c2,9,2,19,School,school_distance,D_location,log,m,-0.000475,0.000621,,,,,,high,"log distance (m) to nearest school; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.000475,0.000621,b (log-log),reported,-0.004177287787766464,0.0054612541393746815,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7648953301127214,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c3,9,3,19,School,school_distance,D_location,log,m,-0.000552,0.000659,,,,,,high,"log distance (m) to nearest school; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.819,se,"(3) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.000552,0.000659,b (log-log),reported,-0.004574517518548244,0.005461244646237849,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8376327769347496,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c1,9,1,19,Hospital,hospital_distance,D_location,log,m,0.00262,0.00193,,,,,,high,"log distance (m) to nearest hospital; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.455,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.00262,0.00193,b (log-log),reported,0.007413584182175502,0.005461151706717068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3575129533678756,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c2,9,2,19,Hospital,hospital_distance,D_location,log,m,2.64e-05,0.00149,,,,,,high,"log distance (m) to nearest hospital; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,2.64e-05,0.00149,b (log-log),reported,9.676400439396894e-05,0.005461301763144459,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.01771812080536913,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c3,9,3,19,Hospital,hospital_distance,D_location,log,m,-0.000113,0.00158,,,,,,high,"log distance (m) to nearest hospital; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.819,se,"(3) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.000113,0.00158,b (log-log),reported,-0.0003905867437029412,0.0054613013721296205,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.07151898734177214,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c1,9,1,19,Park,green_space,E_environment,log,m,-0.00224,0.00208,,,,,,high,"log distance (m) to nearest city park; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.455,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.00224,0.00208,b (log-log),reported,-0.005881300207484963,0.005461207335521752,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0769230769230769,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c2,9,2,19,Park,green_space,E_environment,log,m,-0.000873,0.00128,,,,,,high,"log distance (m) to nearest city park; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.000873,0.00128,b (log-log),reported,-0.003724752647110178,0.00546126390412489,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6820312499999999,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c3,9,3,19,Park,green_space,E_environment,log,m,-0.00077,0.00136,,,,,,high,"log distance (m) to nearest city park; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.819,se,"(3) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.00077,0.00136,b (log-log),reported,-0.00309204579031033,0.005461275681587077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5661764705882352,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c1,9,1,19,Shopping mall,commercial_distance,D_location,log,m,0.00244,0.00237,,,,,,high,"log distance (m) to nearest shopping mall; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.455,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.00244,0.00237,b (log-log),reported,0.005622517187372376,0.005461215464783825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0295358649789028,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c2,9,2,19,Shopping mall,commercial_distance,D_location,log,m,-0.000918,0.00117,,,,,,high,"log distance (m) to nearest shopping mall; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.000918,0.00117,b (log-log),reported,-0.004284982064478862,0.005461251650806393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7846153846153846,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c3,9,3,19,Shopping mall,commercial_distance,D_location,log,m,-0.000873,0.00124,,,,,,high,"log distance (m) to nearest shopping mall; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.819,se,"(3) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.000873,0.00124,b (log-log),reported,-0.0038449042097999124,0.00546126142056345,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7040322580645161,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c1,9,1,19,Farmer’s market,commercial_distance,D_location,log,m,0.000272,0.00185,,,,,,high,"log distance (m) to nearest farmers' market; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.455,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.000272,0.00185,b (log-log),reported,0.0008029587068407511,0.005461300028144814,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.14702702702702702,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c2,9,2,19,Farmer’s market,commercial_distance,D_location,log,m,0.000334,0.000825,,,,,,high,"log distance (m) to nearest farmers' market; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.000334,0.000825,b (log-log),reported,0.002210994350222139,0.005461288439919953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.40484848484848485,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c3,9,3,19,Farmer’s market,commercial_distance,D_location,log,m,0.000444,0.000877,,,,,,high,"log distance (m) to nearest farmers' market; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.819,se,"(3) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.000444,0.000877,b (log-log),reported,0.0027648902232234487,0.00546128091388956,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5062713797035348,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c1,9,1,19,Leisure facilities,neighbourhood_amenities,F_neighbourhood,log,count,0.0112,0.00196,,,***,,,high,"log number of sport/leisure facilities within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.455,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.0112,0.00196,b (log-log),reported,0.031192253355195897,0.005458644337159281,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.714285714285714,33528.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c2,9,2,19,Leisure facilities,neighbourhood_amenities,F_neighbourhood,log,count,-0.00157,0.000811,,,*,,,high,"log number of sport/leisure facilities within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.00157,0.000811,b (log-log),reported,-0.010571842971123485,0.005460996592089902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.935881627620222,33528.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c3,9,3,19,Leisure facilities,neighbourhood_amenities,F_neighbourhood,log,count,-0.00145,0.00086,,,*,,,high,"log number of sport/leisure facilities within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.819,se,"(3) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.00145,0.00086,b (log-log),reported,-0.009207618492940729,0.005461070278571743,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6860465116279069,33528.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c1,9,1,19,Basic services,neighbourhood_amenities,F_neighbourhood,log,count,0.00372,0.00185,,,**,,,high,"log number of basic services (restaurant, post office...) within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.455,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.00372,0.00185,b (log-log),reported,0.010980982563663902,0.005460972511499521,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0108108108108107,33528.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c2,9,2,19,Basic services,neighbourhood_amenities,F_neighbourhood,log,count,0.000822,0.000732,,,,,,high,"log number of basic services (restaurant, post office...) within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.000822,0.000732,b (log-log),reported,0.0061326579937760846,0.005461199089348046,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1229508196721312,33528.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c3,9,3,19,Basic services,neighbourhood_amenities,F_neighbourhood,log,count,0.000985,0.000776,,,,,,high,"log number of basic services (restaurant, post office...) within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.819,se,"(3) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.000985,0.000776,b (log-log),reported,0.006932027078096067,0.0054611705711700995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2693298969072164,33528.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c1,9,1,19,Population,density,F_neighbourhood,log,per_km2,0.191,0.00187,,,***,,,high,"log population density (people/km2); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.455,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.191,0.00187,b (log-log),reported,0.4871481157974418,0.004769460610163435,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),102.13903743315508,33528.0,per_km2,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c2,9,2,19,Population,density,F_neighbourhood,log,per_km2,-0.00392,0.00439,,,,,,high,"log population density (people/km2); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.00392,0.00439,b (log-log),reported,-0.0048765486236308974,0.005461236851464194,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8929384965831435,33528.0,per_km2,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c3,9,3,19,Population,density,F_neighbourhood,log,per_km2,-0.00387,0.00466,,,,,,high,"log population density (people/km2); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.819,se,"(3) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.00387,0.00466,b (log-log),reported,-0.004535412134262931,0.005461245619034949,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8304721030042919,33528.0,per_km2,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c1,9,1,19,D_Bus stop,transit_distance,D_location,log,m,0.00143,0.00196,,,,,,high,"log distance (m) to nearest bus stop; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.455,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.00143,0.00196,b (log-log),reported,0.0039844895734211135,0.00546125843629747,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.729591836734694,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c2,9,2,19,D_Bus stop,transit_distance,D_location,log,m,-0.00182,0.00108,,,*,,,high,"log distance (m) to nearest bus stop; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.00182,0.00108,b (log-log),reported,-0.009202915127184982,0.005461070515032846,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6851851851851851,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c3,9,3,19,D_Bus stop,transit_distance,D_location,log,m,-0.00196,0.00114,,,*,,,high,"log distance (m) to nearest bus stop; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.819,se,"(3) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.00196,0.00114,b (log-log),reported,-0.009389192695490184,0.005461061057581025,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.719298245614035,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c1,9,1,19,D_Metro station,transit_distance,D_location,log,m,0.00106,0.0024,,,,,,high,"log distance (m) to nearest metro station; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.455,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,0.00106,0.0024,b (log-log),reported,0.0024120679398584766,0.005461285901566361,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4416666666666667,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c2,9,2,19,D_Metro station,transit_distance,D_location,log,m,-0.00022,0.00229,,,,,,high,"log distance (m) to nearest metro station; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,33538.0,0.839,se,"(2) FE; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.00022,0.00229,b (log-log),reported,-0.0005246664751734333,0.005461301037032556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.09606986899563319,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c3,9,3,19,D_Metro station,transit_distance,D_location,log,m,-0.000283,0.00242,,,,,,high,"log distance (m) to nearest metro station; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,0.819,se,"(3) FE2sls; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.000283,0.00242,b (log-log),reported,-0.0006386562359524883,0.005461300674929405,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.11694214876033059,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T9-c1,9,1,19,D_CBD,cbd_distance,D_location,log,m,-0.0162,0.00241,,,***,,,high,"log distance (m) to nearest urban centre/subcentre (time-invariant; dropped in FE models); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,33538.0,0.455,se,"(1) OLS; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); robustness with AQI instead of PM2.5; SE clustered at community level",elasticity,-0.0162,0.00241,b (log-log),reported,-0.03668611296855124,0.005457625447790648,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.721991701244813,33528.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c1,10,1,20,PM2.5,air_pollution,E_environment,level,ug/m3,-0.000717,8.53e-05,,,***,,,high,"Quarterly mean PM2.5 concentration, kriged to community; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,15656.0,0.45,se,"(1) OLS PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",semi_elasticity,-0.0717,0.00853,100*b/1 (per ug/m3),reported,-0.06704865502671037,0.007976639154502644,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.405627198124266,15646.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c2,10,2,20,PM2.5,air_pollution,E_environment,level,ug/m3,-9.75e-05,2.57e-05,,,***,,,high,"Quarterly mean PM2.5 concentration, kriged to community; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,15656.0,0.852,se,"(2) FE PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",semi_elasticity,-0.00975,0.0025700000000000002,100*b/1 (per ug/m3),reported,-0.030315879204702665,0.007990954826265216,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.7937743190661477,15646.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,True
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c3,10,3,20,PM2.5,air_pollution,E_environment,level,ug/m3,-0.000832,7.29e-05,,,***,,,high,"Quarterly mean PM2.5 concentration, kriged to community; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.843,se,"(3) FE2sls PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",semi_elasticity,-0.0832,0.00729,100*b/1 (per ug/m3),reported,-0.09086441834661471,0.007961557809456987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.412894375857338,15646.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c1,10,1,20,School,school_distance,D_location,log,m,-0.00165,0.0023,,,,,,high,"log distance (m) to nearest school; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,15656.0,0.45,se,"(1) OLS PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00165,0.0023,b (log-log),reported,-0.005735183298240244,0.00799449793088034,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.717391304347826,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c2,10,2,20,School,school_distance,D_location,log,m,-0.0018,0.000885,,,**,,,high,"log distance (m) to nearest school; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,15656.0,0.852,se,"(2) FE PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.0018,0.000885,b (log-log),reported,-0.01625811406335697,0.007993572747817177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0338983050847457,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c3,10,3,20,School,school_distance,D_location,log,m,-0.00175,0.000911,,,*,,,high,"log distance (m) to nearest school; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.843,se,"(3) FE2sls PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00175,0.000911,b (log-log),reported,-0.015355600353716314,0.007993686812706036,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.920965971459934,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c4,10,4,20,School,school_distance,D_location,log,m,-0.00172,0.000939,,,*,,,high,"log distance (m) to nearest school; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.833,se,"(4) FE2sls AQI; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00172,0.000939,b (log-log),reported,-0.014642479674435256,0.007993772333892271,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8317358892438764,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c1,10,1,20,Hospital,hospital_distance,D_location,log,m,0.00256,0.00286,,,,,,high,"log distance (m) to nearest hospital; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,15656.0,0.45,se,"(1) OLS PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,0.00256,0.00286,b (log-log),reported,0.007155848703235944,0.007994424723146406,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8951048951048951,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c2,10,2,20,Hospital,hospital_distance,D_location,log,m,-0.000151,0.00229,,,,,,high,"log distance (m) to nearest hospital; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,15656.0,0.852,se,"(2) FE PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.000151,0.00229,b (log-log),reported,-0.0005271567133709142,0.007994628302115189,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.06593886462882097,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c3,10,3,20,Hospital,hospital_distance,D_location,log,m,-7.01e-05,0.00236,,,,,,high,"log distance (m) to nearest hospital; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.843,se,"(3) FE2sls PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-7.01e-05,0.00236,b (log-log),reported,-0.00023746758730767894,0.007994629187533844,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.02970338983050847,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c4,10,4,20,Hospital,hospital_distance,D_location,log,m,2.55e-05,0.00243,,,,,,high,"log distance (m) to nearest hospital; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.833,se,"(4) FE2sls AQI; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,2.55e-05,0.00243,b (log-log),reported,8.389425897641962e-05,0.007994629384811753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.010493827160493827,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c1,10,1,20,Park,green_space,E_environment,log,m,-0.00305,0.00289,,,,,,high,"log distance (m) to nearest city park; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,15656.0,0.45,se,"(1) OLS PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00305,0.00289,b (log-log),reported,-0.008436938358996116,0.007994344871311072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.055363321799308,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c2,10,2,20,Park,green_space,E_environment,log,m,-0.000518,0.0017,,,,,,high,"log distance (m) to nearest city park; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,15656.0,0.852,se,"(2) FE PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.000518,0.0017,b (log-log),reported,-0.002436003381565243,0.007994605692395584,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3047058823529412,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c3,10,3,20,Park,green_space,E_environment,log,m,-0.0003,0.00175,,,,,,high,"log distance (m) to nearest city park; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.843,se,"(3) FE2sls PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.0003,0.00175,b (log-log),reported,-0.0013705066122570123,0.007994621904832572,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.1714285714285714,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c4,10,4,20,Park,green_space,E_environment,log,m,-0.000374,0.0018,,,,,,high,"log distance (m) to nearest city park; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.833,se,"(4) FE2sls AQI; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.000374,0.0018,b (log-log),reported,-0.0016611040418595218,0.00799461838328112,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.20777777777777778,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c1,10,1,20,Shopping mall,commercial_distance,D_location,log,m,-0.0026,0.00355,,,,,,high,"log distance (m) to nearest shopping mall; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,15656.0,0.45,se,"(1) OLS PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.0026,0.00355,b (log-log),reported,-0.005855121175363372,0.007994492374053835,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.732394366197183,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c2,10,2,20,Shopping mall,commercial_distance,D_location,log,m,-0.00185,0.00163,,,,,,high,"log distance (m) to nearest shopping mall; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,15656.0,0.852,se,"(2) FE PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00185,0.00163,b (log-log),reported,-0.009073285649692292,0.007994300329188343,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1349693251533743,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c3,10,3,20,Shopping mall,commercial_distance,D_location,log,m,-0.00171,0.00168,,,,,,high,"log distance (m) to nearest shopping mall; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.843,se,"(3) FE2sls PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00171,0.00168,b (log-log),reported,-0.008137121248528383,0.007994364735396307,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0178571428571428,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c4,10,4,20,Shopping mall,commercial_distance,D_location,log,m,-0.00181,0.00173,,,,,,high,"log distance (m) to nearest shopping mall; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.833,se,"(4) FE2sls AQI; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00181,0.00173,b (log-log),reported,-0.008364030681994376,0.007994349767873077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.046242774566474,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c1,10,1,20,Farmer’s market,commercial_distance,D_location,log,m,-0.00509,0.00267,,,*,,,high,"log distance (m) to nearest farmers' market; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,15656.0,0.45,se,"(1) OLS PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00509,0.00267,b (log-log),reported,-0.015238928281631025,0.00799370108289879,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9063670411985019,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c2,10,2,20,Farmer’s market,commercial_distance,D_location,log,m,-0.000803,0.00115,,,,,,high,"log distance (m) to nearest farmers' market; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,15656.0,0.852,se,"(2) FE PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.000803,0.00115,b (log-log),reported,-0.005582249908023022,0.007994504849597106,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6982608695652174,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c3,10,3,20,Farmer’s market,commercial_distance,D_location,log,m,-0.000657,0.00119,,,,,,high,"log distance (m) to nearest farmers' market; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.843,se,"(3) FE2sls PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.000657,0.00119,b (log-log),reported,-0.004413798622465208,0.007994551538407302,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5521008403361345,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c4,10,4,20,Farmer’s market,commercial_distance,D_location,log,m,-0.00075,0.00123,,,,,,high,"log distance (m) to nearest farmers' market; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.833,se,"(4) FE2sls AQI; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00075,0.00123,b (log-log),reported,-0.004874716112660408,0.00799453442476307,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6097560975609756,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c1,10,1,20,Leisure facilities,neighbourhood_amenities,F_neighbourhood,log,count,0.00914,0.00299,,,***,,,high,"log number of sport/leisure facilities within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,15656.0,0.45,se,"(1) OLS PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,0.00914,0.00299,b (log-log),reported,0.024431137885561973,0.007992243137618194,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.05685618729097,15646.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c2,10,2,20,Leisure facilities,neighbourhood_amenities,F_neighbourhood,log,count,-0.0017,0.00119,,,,,,high,"log number of sport/leisure facilities within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,15656.0,0.852,se,"(2) FE PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.0017,0.00119,b (log-log),reported,-0.011420154380654662,0.007994108066458264,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4285714285714284,15646.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c3,10,3,20,Leisure facilities,neighbourhood_amenities,F_neighbourhood,log,count,-0.00172,0.00123,,,,,,high,"log number of sport/leisure facilities within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.843,se,"(3) FE2sls PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00172,0.00123,b (log-log),reported,-0.011178783235822307,0.007994129872128743,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3983739837398375,15646.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c4,10,4,20,Leisure facilities,neighbourhood_amenities,F_neighbourhood,log,count,-0.00174,0.00127,,,,,,high,"log number of sport/leisure facilities within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.833,se,"(4) FE2sls AQI; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00174,0.00127,b (log-log),reported,-0.010952614798423282,0.007994149881607798,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3700787401574803,15646.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c1,10,1,20,Basic services,neighbourhood_amenities,F_neighbourhood,log,count,0.0141,0.0028,,,***,,,high,"log number of basic services (restaurant, post office...) within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,15656.0,0.45,se,"(1) OLS PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,0.0141,0.0028,b (log-log),reported,0.04022608431789729,0.007988158587951235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.035714285714286,15646.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c2,10,2,20,Basic services,neighbourhood_amenities,F_neighbourhood,log,count,0.00156,0.00107,,,,,,high,"log number of basic services (restaurant, post office...) within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,15656.0,0.852,se,"(2) FE PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,0.00156,0.00107,b (log-log),reported,0.011654929718846196,0.00799408640972143,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4579439252336448,15646.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c3,10,3,20,Basic services,neighbourhood_amenities,F_neighbourhood,log,count,0.00134,0.0011,,,,,,high,"log number of basic services (restaurant, post office...) within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.843,se,"(3) FE2sls PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,0.00134,0.0011,b (log-log),reported,0.009738450376370287,0.007994250308960683,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2181818181818183,15646.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c4,10,4,20,Basic services,neighbourhood_amenities,F_neighbourhood,log,count,0.00149,0.00113,,,,,,high,"log number of basic services (restaurant, post office...) within 1 km; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.833,se,"(4) FE2sls AQI; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,0.00149,0.00113,b (log-log),reported,0.010541005326751276,0.00799418524780466,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3185840707964602,15646.0,count,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c1,10,1,20,Population,density,F_neighbourhood,log,per_km2,0.233,0.00326,,,***,,,high,"log population density (people/km2); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,15656.0,0.45,se,"(1) OLS PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,0.233,0.00326,b (log-log),reported,0.4961171560387903,0.006941381668182215,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),71.47239263803682,15646.0,per_km2,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,True
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c2,10,2,20,Population,density,F_neighbourhood,log,per_km2,0.00111,0.00624,,,,,,high,"log population density (people/km2); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,15656.0,0.852,se,"(2) FE PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,0.00111,0.00624,b (log-log),reported,0.0014221201401960679,0.007994621328669786,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.1778846153846154,15646.0,per_km2,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c3,10,3,20,Population,density,F_neighbourhood,log,per_km2,2.2e-05,0.00642,,,,,,high,"log population density (people/km2); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.843,se,"(3) FE2sls PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,2.2e-05,0.00642,b (log-log),reported,2.7395926326916754e-05,0.007994629409945709,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0034267912772585666,15646.0,per_km2,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c4,10,4,20,Population,density,F_neighbourhood,log,per_km2,0.00131,0.00662,,,,,,high,"log population density (people/km2); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.833,se,"(4) FE2sls AQI; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,0.00131,0.00662,b (log-log),reported,0.0015820168316015312,0.00799461940855125,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.19788519637462235,15646.0,per_km2,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c1,10,1,20,D_Bus stop,transit_distance,D_location,log,m,-0.00194,0.00301,,,,,,high,"log distance (m) to nearest bus stop; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,15656.0,0.45,se,"(1) OLS PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00194,0.00301,b (log-log),reported,-0.005152616336971844,0.007994523285714046,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6445182724252492,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c2,10,2,20,D_Bus stop,transit_distance,D_location,log,m,-0.00205,0.00154,,,,,,high,"log distance (m) to nearest bus stop; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,15656.0,0.852,se,"(2) FE PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00205,0.00154,b (log-log),reported,-0.010641598893450385,0.007994176729713948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3311688311688314,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c3,10,3,20,D_Bus stop,transit_distance,D_location,log,m,-0.00243,0.00158,,,,,,high,"log distance (m) to nearest bus stop; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.843,se,"(3) FE2sls PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00243,0.00158,b (log-log),reported,-0.012294608325596678,0.007994025166437347,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5379746835443038,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c4,10,4,20,D_Bus stop,transit_distance,D_location,log,m,-0.00232,0.00163,,,,,,high,"log distance (m) to nearest bus stop; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.833,se,"(4) FE2sls AQI; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00232,0.00163,b (log-log),reported,-0.011378122454847633,0.007994111897155879,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4233128834355828,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c1,10,1,20,D_Metro station,transit_distance,D_location,log,m,0.0333,0.00361,,,***,,,high,"log distance (m) to nearest metro station; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,15656.0,0.45,se,"(1) OLS PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,0.0333,0.00361,b (log-log),reported,0.07354575925546761,0.007972978706073214,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.22437673130194,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c2,10,2,20,D_Metro station,transit_distance,D_location,log,m,-0.000692,0.00311,,,,,,high,"log distance (m) to nearest metro station; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,FE_panel,15656.0,0.852,se,"(2) FE PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.000692,0.00311,b (log-log),reported,-0.0017788664953911845,0.00799461676396905,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.222508038585209,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,panel,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c3,10,3,20,D_Metro station,transit_distance,D_location,log,m,-0.000271,0.00319,,,,,,high,"log distance (m) to nearest metro station; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.843,se,"(3) FE2sls PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.000271,0.00319,b (log-log),reported,-0.0006791674204479646,0.007994627569110728,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.08495297805642632,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c4,10,4,20,D_Metro station,transit_distance,D_location,log,m,-0.00028,0.00329,,,,,,high,"log distance (m) to nearest metro station; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,15656.0,0.833,se,"(4) FE2sls AQI; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.00028,0.00329,b (log-log),reported,-0.0006803938351017584,0.00799462756244566,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.0851063829787234,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T10-c1,10,1,20,D_CBD,cbd_distance,D_location,log,m,-0.0287,0.00362,,,***,,,high,"log distance (m) to nearest urban centre/subcentre (time-invariant; dropped in FE models); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,OLS,15656.0,0.45,se,"(1) OLS PM2.5; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); subsample of communities within 3 km of an air monitoring station; column 4 uses AQI; parentheses = standard errors (clustering not stated in this table note)",elasticity,-0.0287,0.00362,b (log-log),reported,-0.063255901142112,0.007978618889701932,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.928176795580111,15646.0,m,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T4-c1,4,1,15,PM2.5,air_pollution,E_environment,level,ug/m3,-0.0141,0.00039,,,***,,,high,"Quarterly mean PM2.5; IV quantile regression (magnitude much larger than Table 3; printed as is); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,quantile,33538.0,,se,"IV quantile regression, quantile Q25; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); other variables controlled but not reported",semi_elasticity,-1.41,0.039,100*b/1 (per ug/m3),reported,-0.19370729260341393,0.005357861284775279,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-36.15384615384615,33528.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,quantile,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T4-c2,4,2,15,PM2.5,air_pollution,E_environment,level,ug/m3,-0.0151,0.00033,,,***,,,high,"Quarterly mean PM2.5; IV quantile regression (magnitude much larger than Table 3; printed as is); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,quantile,33538.0,,se,"IV quantile regression, quantile Q50; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); other variables controlled but not reported",semi_elasticity,-1.51,0.033,100*b/1 (per ug/m3),reported,-0.24244059810367466,0.00529837068703395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-45.75757575757576,33528.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,quantile,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T4-c3,4,3,15,PM2.5,air_pollution,E_environment,level,ug/m3,-0.0168,0.00028,,,***,,,high,"Quarterly mean PM2.5; IV quantile regression (magnitude much larger than Table 3; printed as is); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,quantile,33538.0,,se,"IV quantile regression, quantile Q75; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); other variables controlled but not reported",semi_elasticity,-1.68,0.027999999999999997,100*b/1 (per ug/m3),reported,-0.3113869966259735,0.005189783277099558,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-60.0,33528.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,quantile,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T4-c4,4,4,15,PM2.5,air_pollution,E_environment,level,ug/m3,-0.0189,0.00031,,,***,,,high,"Quarterly mean PM2.5; IV quantile regression (magnitude much larger than Table 3; printed as is); stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,quantile,33538.0,,se,"IV quantile regression, quantile Q90; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); other variables controlled but not reported",semi_elasticity,-1.8900000000000001,0.031,100*b/1 (per ug/m3),reported,-0.3159117205383836,0.005181620813063435,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-60.96774193548387,33528.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,quantile,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T5-c1,5,1,15,PM2.5,air_pollution,E_environment,level,ug/m3,-0.00111,0.000176,,,***,,,high,"Quarterly mean PM2.5; communities within Ring2; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,333269.0,,se,"FE2sls stratified by ring road (Ring2); AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); N per ring not printed",semi_elasticity,-0.11100000000000002,0.0176,100*b/1 (per ug/m3),reported,-0.010924295812211325,0.001732140597251525,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.3068181818181825,333259.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T5-c2,5,2,15,PM2.5,air_pollution,E_environment,level,ug/m3,-0.000867,9.32e-05,,,***,,,high,"Quarterly mean PM2.5; communities within Ring3; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,333269.0,,se,"FE2sls stratified by ring road (Ring3); AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); N per ring not printed",semi_elasticity,-0.0867,0.00932,100*b/1 (per ug/m3),reported,-0.016112237765354708,0.001732019100035823,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.302575107296137,333259.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T5-c3,5,3,15,PM2.5,air_pollution,E_environment,level,ug/m3,-0.00104,0.000106,,,***,,,high,"Quarterly mean PM2.5; communities within Ring4; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,333269.0,,se,"FE2sls stratified by ring road (Ring4); AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); N per ring not printed",semi_elasticity,-0.104,0.0106,100*b/1 (per ug/m3),reported,-0.01699314708974906,0.0017319938379936545,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.81132075471698,333259.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T5-c4,5,4,15,PM2.5,air_pollution,E_environment,level,ug/m3,-0.000774,0.000124,,,***,,,high,"Quarterly mean PM2.5; communities within Ring5; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,333269.0,,se,"FE2sls stratified by ring road (Ring5); AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); N per ring not printed",semi_elasticity,-0.0774,0.012400000000000001,100*b/1 (per ug/m3),reported,-0.010811923062967776,0.0017321427129302384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.241935483870967,333259.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T5-c5,5,5,15,PM2.5,air_pollution,E_environment,level,ug/m3,-0.000622,8.09e-05,,,***,,,high,"Quarterly mean PM2.5; communities within Ring6; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,333269.0,,se,"FE2sls stratified by ring road (Ring6); AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5); N per ring not printed",semi_elasticity,-0.062200000000000005,0.00809,100*b/1 (per ug/m3),reported,-0.013317184166885305,0.0017320903522524457,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.688504326328801,333259.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46,54da27518406c538ad01d44349b80f8a974bfe46:T6-c1,6,1,16,PM2.5 (2013 baseline),air_pollution,E_environment,level,ug/m3,-0.00232,4.1e-05,,,***,,,high,"Base-year 2013 PM2.5 coefficient; stars: * p<0.1, ** p<0.05, *** p<0.01","ln community price index (lnCP, community x quarter)",log,IV,33538.0,,se,"Dynamic-effects model (Eq. 6) with PM2.5 x year interactions, 2013 base; AGGREGATE second stage: unit of analysis = community x quarter panel (N=33,538), dependent variable is the community-quarter log price index (lnCP) from the first-stage hedonic; accessibility/neighbourhood variables enter in logs (Eqs. 2-5)",semi_elasticity,-0.232,0.0041,100*b/1 (per ug/m3),reported,-0.2952529419867577,0.005217832164421149,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-56.58536585365854,33528.0,ug/m3,,2024.0,China,Asia,Upper middle income,2013.0,2019.0,condo_apartment,transaction,journal,True,True,clustered,,2016.0,iv,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c1,2,1,10,Area,living_area,A_structural,level,m2,0.01,,59.16,,***,,,high,Gross floor area; printed significance letter 'a',ln(price),log,OLS,1250.0,0.801,t,Semi-log model; adjusted R2,semi_elasticity,1.0,0.016903313049357677,100*b/1 (X per m2->m2),|b/t|,0.8592970466477441,0.014524966981875323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),59.16,1240.0,m2,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c2,2,2,10,Area,living_area,A_structural,log,m2,1.008,,70.7,,***,,,high,Gross floor area; printed significance letter 'a',ln(price),log,OLS,1250.0,0.85,t,Double-log model (continuous regressors in logs); adjusted R2,elasticity,1.008,0.014257425742574256,b (log-log),|b/t|,0.8951167255988607,0.012660774053732119,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),70.7,1240.0,m2,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c1,2,1,10,Age,age,A_structural,level,years,-0.011,,-7.65,,***,,,high,2015 minus year of occupation permit; printed significance letter 'a',ln(price),log,OLS,1250.0,0.801,t,Semi-log model; adjusted R2,semi_elasticity,-1.0999999999999999,0.1437908496732026,100*b/1 (per year),|b/t|,-0.21229349921710175,0.027750784211385847,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.65,1240.0,years,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c2,2,2,10,Age,age,A_structural,log,years,-0.153,,-11.26,,***,,,high,2015 minus year of occupation permit; printed significance letter 'a',ln(price),log,OLS,1250.0,0.85,t,Double-log model (continuous regressors in logs); adjusted R2,elasticity,-0.153,0.013587921847246892,b (log-log),|b/t|,-0.3045705275000428,0.027048892317943413,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.26,1240.0,years,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c1,2,1,10,School,school_quality,F_neighbourhood,binary,binary,0.089,,4.0,,***,,,high,Property within attendance zone of a provincial-level demonstration elementary school (xuequfang); printed significance letter 'a',ln(price),log,OLS,1250.0,0.801,t,Semi-log model; adjusted R2,pct_premium,9.281011818982176,2.4321044603260846,100*(exp(b - se^2/2) - 1),|b/t|,0.11286652959662007,0.028216632399155017,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,1240.0,binary,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c2,2,2,10,School,school_quality,F_neighbourhood,binary,binary,0.108,,5.45,,***,,,high,Property within attendance zone of a provincial-level demonstration elementary school (xuequfang); printed significance letter 'a',ln(price),log,OLS,1250.0,0.85,t,Double-log model (continuous regressors in logs); adjusted R2,pct_premium,11.382902680564634,2.207654247738321,100*(exp(b - se^2/2) - 1),|b/t|,0.15294860311998618,0.028063963875226826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.45,1240.0,binary,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c1,2,1,10,Kindergarten,school_distance,D_location,binary,binary,0.009,,0.47,,,,,high,At least one kindergarten within 500 m; printed significance letter 'c',ln(price),log,OLS,1250.0,0.801,t,Semi-log model; adjusted R2,pct_premium,0.8855640337954274,1.9322054459499598,100*(exp(b - se^2/2) - 1),|b/t|,0.013345914402707128,0.02839556255895134,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.47,1240.0,binary,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c2,2,2,10,Kindergarten,school_distance,D_location,binary,binary,-0.011,,-0.68,,,,,high,At least one kindergarten within 500 m; printed significance letter 'c',ln(price),log,OLS,1250.0,0.85,t,Double-log model (continuous regressors in logs); adjusted R2,pct_premium,-1.1069120516266184,1.599950450960155,100*(exp(b - se^2/2) - 1),|b/t|,-0.019307102859467042,0.02839279832274565,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.68,1240.0,binary,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c1,2,1,10,Middle school,school_distance,D_location,binary,binary,-0.001,,-0.06,,,,,high,"At least one middle school within 1,000 m; printed significance letter 'c'",ln(price),log,OLS,1250.0,0.801,t,Semi-log model; adjusted R2,pct_premium,-0.11382406010709278,1.665000833055625,100*(exp(b - se^2/2) - 1),|b/t|,-0.0017038830293643983,0.028398050489406645,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.06,1240.0,binary,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c2,2,2,10,Middle school,school_distance,D_location,binary,binary,0.032,,1.91,,,,,high,"At least one middle school within 1,000 m; printed significance letter 'c'",ln(price),log,OLS,1250.0,0.85,t,Double-log model (continuous regressors in logs); adjusted R2,pct_premium,3.23726047082884,1.7298722601970569,100*(exp(b - se^2/2) - 1),|b/t|,0.05416074279338552,0.02835640983946886,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.91,1240.0,binary,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c1,2,1,10,Xiamen University,university_distance,D_location,binary,binary,0.206,,3.45,,***,,,high,"Xiamen University within 1,000 m; printed significance letter 'a'",ln(price),log,OLS,1250.0,0.801,t,Semi-log model; adjusted R2,pct_premium,22.656471746470007,7.336903189073456,100*(exp(b - se^2/2) - 1),|b/t|,0.09750656152300757,0.028262771455944222,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.45,1240.0,binary,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c2,2,2,10,Xiamen University,university_distance,D_location,binary,binary,0.144,,3.04,,***,,,high,"Xiamen University within 1,000 m; printed significance letter 'a'",ln(price),log,OLS,1250.0,0.85,t,Double-log model (continuous regressors in logs); adjusted R2,pct_premium,15.358918942849996,5.470503671960116,100*(exp(b - se^2/2) - 1),|b/t|,0.08601028062986361,0.02829285547034987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.04,1240.0,binary,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c1,2,1,10,BRT,transit_distance,D_location,binary,binary,0.077,,4.72,,***,,,high,BRT station within 800 m; printed significance letter 'a',ln(price),log,OLS,1250.0,0.801,t,Semi-log model; adjusted R2,pct_premium,7.989836895757829,1.7619330483523354,100*(exp(b - se^2/2) - 1),|b/t|,0.13285087626533462,0.028146372090113267,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.72,1240.0,binary,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c2,2,2,10,BRT,transit_distance,D_location,binary,binary,0.1,,6.85,,***,,,high,BRT station within 800 m; printed significance letter 'a',ln(price),log,OLS,1250.0,0.85,t,Double-log model (continuous regressors in logs); adjusted R2,pct_premium,10.505315878773814,1.6133882015702887,100*(exp(b - se^2/2) - 1),|b/t|,0.1909476749063951,0.02787557297903578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.85,1240.0,binary,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c1,2,1,10,Distance to hospital,hospital_distance,D_location,level,km,0.047,,4.41,,***,,,high,Euclidean distance to nearest Class 2A/3A hospital; printed significance letter 'a',ln(price),log,OLS,1250.0,0.801,t,Semi-log model; adjusted R2,semi_elasticity,4.7,1.0657596371882085,100*b/1 (X per km->km),|b/t|,0.12426489342378419,0.02817798036820503,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.41,1240.0,km,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c2,2,2,10,Distance to hospital,hospital_distance,D_location,log,km,0.018,,2.13,,**,,,high,Euclidean distance to nearest Class 2A/3A hospital; printed significance letter 'b',ln(price),log,OLS,1250.0,0.85,t,Double-log model (continuous regressors in logs); adjusted R2,elasticity,0.018,0.008450704225352112,b (log-log),|b/t|,0.06037758173944477,0.028346282506781582,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.13,1240.0,km,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c2,2,2,10,Distance to cultural/sports center,neighbourhood_amenities,F_neighbourhood,log,km,-0.049,,-5.25,,***,,,high,Euclidean distance to nearest cultural/sports centre; printed significance letter 'a',ln(price),log,OLS,1250.0,0.85,t,Double-log model (continuous regressors in logs); adjusted R2,elasticity,-0.049,0.009333333333333334,b (log-log),|b/t|,-0.1474601299221955,0.028087643794703906,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.25,1240.0,km,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c1,2,1,10,Distance to city center,cbd_distance,D_location,level,km,-0.021,,-6.04,,***,,,high,Euclidean distance to Zhongshan Road; printed significance letter 'a',ln(price),log,OLS,1250.0,0.801,t,Semi-log model; adjusted R2,semi_elasticity,-2.1,0.34768211920529807,100*b/1 (X per km->km),|b/t|,-0.169055638028726,0.027989344044491063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.04,1240.0,km,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c2,2,2,10,Distance to city center,cbd_distance,D_location,log,km,-0.077,,-6.36,,***,,,high,Euclidean distance to Zhongshan Road; printed significance letter 'a',ln(price),log,OLS,1250.0,0.85,t,Double-log model (continuous regressors in logs); adjusted R2,elasticity,-0.077,0.01210691823899371,b (log-log),|b/t|,-0.17773619203308624,0.027945942143567017,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.36,1240.0,km,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c1,2,1,10,Distance to lake,water_proximity,E_environment,level,km,-0.072,,-6.06,,***,,,high,Euclidean distance to nearest lake; printed significance letter 'a',ln(price),log,OLS,1250.0,0.801,t,Semi-log model; adjusted R2,semi_elasticity,-7.199999999999999,1.188118811881188,100*b/1 (X per km->km),|b/t|,-0.16959934904241158,0.027986691261124026,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.06,1240.0,km,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955,58a9ab2513035056fdc6d56cafc04ae9d61a0955:T2-c2,2,2,10,Distance to lake,water_proximity,E_environment,log,km,-0.051,,-5.95,,***,,,high,Euclidean distance to nearest lake; printed significance letter 'a',ln(price),log,OLS,1250.0,0.85,t,Double-log model (continuous regressors in logs); adjusted R2,elasticity,-0.051,0.00857142857142857,b (log-log),|b/t|,-0.16660703429748522,0.028001182234871462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.95,1240.0,km,,2018.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,listing,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109:T3-res,3,Residential model (Martinez and Viegas 2009),7,Bedrooms,bedrooms,A_structural,level,count,0.0427,0.003,,,***,,,high,,ln(asking price),log,spatial_lag,8742.0,0.795,se,"residential properties, Lisbon; pseudo R2",semi_elasticity,4.2700000000000005,0.3,100*b/1 (per unit count),reported,0.1505807168675525,0.010579441466104391,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.233333333333334,8732.0,count,,2012.0,Portugal,Europe,High income,2007.0,2007.0,mixed,listing,journal,False,False,unknown,,2007.0,spatial,journal,True,True,False
5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109:T3-res,3,Residential model (Martinez and Viegas 2009),7,House,dwelling_type,A_structural,binary,binary,0.1685,0.0154,,,***,,,high,House (vs apartment),ln(asking price),log,spatial_lag,8742.0,0.795,se,"residential properties, Lisbon; pseudo R2",pct_premium,18.33878923883139,1.8226334693410822,100*(exp(b - se^2/2) - 1),reported,0.11629616855779301,0.010628848639703337,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.941558441558442,8732.0,binary,,2012.0,Portugal,Europe,High income,2007.0,2007.0,mixed,listing,journal,False,False,unknown,,2007.0,spatial,journal,True,True,False
5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109:T3-res,3,Residential model (Martinez and Viegas 2009),7,Floor,floor_level,A_structural,level,count,0.0155,0.0009,,,***,,,high,,ln(asking price),log,spatial_lag,8742.0,0.795,se,"residential properties, Lisbon; pseudo R2",semi_elasticity,1.55,0.09,100*b/1 (per unit count),reported,0.18125035407861786,0.010524214107790716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.22222222222222,8732.0,count,,2012.0,Portugal,Europe,High income,2007.0,2007.0,mixed,listing,journal,False,False,unknown,,2007.0,spatial,journal,True,True,False
5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109:T3-res,3,Residential model (Martinez and Viegas 2009),7,Area,living_area,A_structural,level,m2,0.0064,0.0001,,,***,,,high,,ln(asking price),log,spatial_lag,8742.0,0.795,se,"residential properties, Lisbon; pseudo R2",semi_elasticity,0.64,0.01,100*b/1 (X per m2->m2),reported,0.5650677197537494,0.008829183121152336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),64.0,8732.0,m2,,2012.0,Portugal,Europe,High income,2007.0,2007.0,mixed,listing,journal,False,False,unknown,,2007.0,spatial,journal,True,True,False
5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109:T3-res,3,Residential model (Martinez and Viegas 2009),7,Age2,age,A_structural,dummy,binary,-0.1034,0.0063,,,***,,,high,Building age class 2 (class bounds not printed),ln(asking price),log,spatial_lag,8742.0,0.795,se,"residential properties, Lisbon; pseudo R2",pct_premium,-9.82517005199094,0.5681127027571758,100*(exp(b - se^2/2) - 1),reported,-0.17299180159095368,0.010540119439294083,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.412698412698415,8732.0,binary,,2012.0,Portugal,Europe,High income,2007.0,2007.0,mixed,listing,journal,False,False,unknown,,2007.0,spatial,journal,True,True,False
5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109:T3-res,3,Residential model (Martinez and Viegas 2009),7,Age3,age,A_structural,dummy,binary,-0.0729,0.0068,,,***,,,high,Building age class 3 (class bounds not printed),ln(asking price),log,spatial_lag,8742.0,0.795,se,"residential properties, Lisbon; pseudo R2",pct_premium,-7.032769951510565,0.6321917804347289,100*(exp(b - se^2/2) - 1),reported,-0.11397833153010199,0.01063172365438537,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.72058823529412,8732.0,binary,,2012.0,Portugal,Europe,High income,2007.0,2007.0,mixed,listing,journal,False,False,unknown,,2007.0,spatial,journal,True,True,False
5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,5cf7ffdc50779ba179e5d6c37bf66eba2f4f8109:T3-res,3,Residential model (Martinez and Viegas 2009),7,Garage,garage,A_structural,binary,binary,0.1126,0.0059,,,***,,,high,Off-street parking inside property,ln(asking price),log,spatial_lag,8742.0,0.795,se,"residential properties, Lisbon; pseudo R2",pct_premium,11.91646905030639,0.6603186601430716,100*(exp(b - se^2/2) - 1),reported,0.2001039776244937,0.010485021918157308,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.084745762711865,8732.0,binary,,2012.0,Portugal,Europe,High income,2007.0,2007.0,mixed,listing,journal,False,False,unknown,,2007.0,spatial,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T4-c1,4,1,12,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),-0.0457,0.0037,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,833282.0,0.1683,se,"All transactions within 3 km of a station opened 2010-2018; no controls, no FE",pct_premium,-4.467802144076549,0.35347155157140653,100*(exp(b - se^2/2) - 1),reported,-0.013529487005321044,0.0010953851623564084,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.35135135135135,833272.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T4-c2,4,2,12,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0122,0.0022,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,833282.0,0.7155,se,Region (3-digit postal code) FE + quarter FE; no structural controls,pct_premium,1.227227386477936,0.2227004391846622,100*(exp(b - se^2/2) - 1),reported,0.0060748525593663305,0.0010954652156234365,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.545454545454546,833272.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T4-c3,4,3,12,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.018,0.0021,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,833282.0,0.742,se,Region + quarter FE; age and area linear,pct_premium,1.8160731342905967,0.21381422504185665,100*(exp(b - se^2/2) - 1),reported,0.009389461186873168,0.0010954371384685364,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.571428571428571,833272.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T4-c4,4,4,12,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0228,0.0021,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,833281.0,0.7466,se,"Region + quarter + frame-type FE; age, area and squares",pct_premium,2.305965085425732,0.21484300040768764,100*(exp(b - se^2/2) - 1),reported,0.011893007759743597,0.0010954086094500683,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.857142857142858,833271.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T4-c5,4,5,12,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0139,0.0021,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,833281.0,0.7524,se,"Full specification: region + quarter + frame FE (region x quarter per eq. 2), age, area and squares; baseline model (identical to T5 c1, T7 c2, T8 c2, T9 c1, not re-extracted)",pct_premium,1.3994818301882317,0.21293938137421356,100*(exp(b - se^2/2) - 1),reported,0.007250883959285077,0.0010954572888128534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.619047619047619,833271.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T5-c2,5,2,13,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0164,0.0023,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,725519.0,0.7542,se,41 stations (4 stations re-opened for a second time removed); full specification,pct_premium,1.653252944929573,0.23380310018172012,100*(exp(b - se^2/2) - 1),reported,0.008371039532865573,0.0011739872515604158,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.130434782608696,725509.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T5-c3,5,3,13,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),-0.0178,0.0058,,,**,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,107762.0,0.7396,se,Only the 4 stations opened for a second time (junction stations); full specification,pct_premium,-1.7659038904621949,0.5697673408413955,100*(exp(b - se^2/2) - 1),reported,-0.009348896652378948,0.0030462696957189827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0689655172413794,107752.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T6-c1,6,1,15,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),-0.1403,0.0392,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,80423.0,0.641,se,Station cluster: North (region without prior BRT line); full specification,pct_premium,-13.157002146526342,3.406862070817948,100*(exp(b - se^2/2) - 1),reported,-0.012620422164878794,0.0035261621444280023,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5790816326530615,80413.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T6-c2,6,2,15,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),-0.1193,0.0094,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,55045.0,0.5066,se,Station cluster: South (region without prior BRT line); full specification,pct_premium,-11.24977123481492,0.8342890084669331,100*(exp(b - se^2/2) - 1),reported,-0.05402048715767053,0.004256434025834895,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.691489361702127,55035.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T6-c3,6,3,15,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),-0.0323,0.0101,,,**,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,88720.0,0.7257,se,Station cluster: West (region without prior BRT line); full specification,pct_premium,-3.183330891843561,0.9778982344198422,100*(exp(b - se^2/2) - 1),reported,-0.010736675454727533,0.0033572886096826025,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.198019801980198,88710.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T6-c4,6,4,15,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),-0.0819,0.0075,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,71263.0,0.7436,se,Station cluster: Sayyad (region without prior BRT line); full specification,pct_premium,-7.866182250191034,0.6910230678740487,100*(exp(b - se^2/2) - 1),reported,-0.04087501784773232,0.0037431335025395903,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.92,71253.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T6-c5,6,5,15,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0569,0.0062,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,284352.0,0.7222,se,Station cluster: Azadi-Enghelab (region with pre-existing BRT line); full specification,pct_premium,5.8529604973039495,0.6563009690666892,100*(exp(b - se^2/2) - 1),reported,0.0172082124148905,0.0018750600522376292,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.17741935483871,284342.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T6-c6,6,6,15,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0516,0.0052,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,87913.0,0.7417,se,Station cluster: Valiasr (region with pre-existing BRT line); full specification,pct_premium,5.294024062689662,0.5475363277670956,100*(exp(b - se^2/2) - 1),reported,0.03345040658157967,0.003370971205895625,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.923076923076923,87903.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T6-c7,6,7,15,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0071,0.0029,,,*,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,81984.0,0.7136,se,Station cluster: Navvab (region with pre-existing BRT line); full specification,pct_premium,0.7121029805031487,0.2920663267797811,100*(exp(b - se^2/2) - 1),reported,0.008550793325637357,0.0034925775555420184,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4482758620689657,81974.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T10-c2,10,2,21,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0513,0.0032,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,759057.0,0.4435,se,"Region FE only; lnAge, lnArea (log-form robustness; sample smaller because ln(age) drops age=0)",pct_premium,5.263324801442804,0.33684436400334555,100*(exp(b - se^2/2) - 1),reported,0.018397530968404793,0.0011476042709336323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.03125,759047.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T10-c2,10,2,21,lnAge,age,A_structural,log,years (log of building age),-0.1259,0.0006,,,***,,,high,Log of building age in years (elasticity),"ln nominal transaction price of the property (total price, Tomans)",log,OLS,759057.0,0.4435,se,"Region FE only; lnAge, lnArea (log-form robustness; sample smaller because ln(age) drops age=0)",elasticity,-0.1259,0.0006,b (log-log),reported,-0.23415092524624476,0.0011158900329447724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-209.83333333333337,759047.0,years,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T10-c2,10,2,21,lnArea,living_area,A_structural,log,m2 (log of surface area),0.0883,0.0019,,,***,,,high,Log of dwelling surface area in m2 (elasticity),"ln nominal transaction price of the property (total price, Tomans)",log,OLS,759057.0,0.4435,se,"Region FE only; lnAge, lnArea (log-form robustness; sample smaller because ln(age) drops age=0)",elasticity,0.0883,0.0019,b (log-log),reported,0.05326669754847317,0.0011461690299218463,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),46.473684210526315,759047.0,m2,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T10-c3,10,3,21,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),-0.0413,0.0027,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,759057.0,0.5708,se,"Quarter FE only; lnAge, lnArea (log-form robustness; sample smaller because ln(age) drops age=0)",pct_premium,-4.0462273124582175,0.2590761305871378,100*(exp(b - se^2/2) - 1),reported,-0.017554361110645848,0.0011476216706717624,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.296296296296298,759047.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T10-c3,10,3,21,lnAge,age,A_structural,log,years (log of building age),-0.0785,0.0005,,,***,,,high,Log of building age in years (elasticity),"ln nominal transaction price of the property (total price, Tomans)",log,OLS,759057.0,0.5708,se,"Quarter FE only; lnAge, lnArea (log-form robustness; sample smaller because ln(age) drops age=0)",elasticity,-0.0785,0.0005,b (log-log),reported,-0.17734781303859223,0.0011296039047044091,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-157.0,759047.0,years,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T10-c3,10,3,21,lnArea,living_area,A_structural,log,m2 (log of surface area),0.5667,0.0013,,,***,,,high,Log of dwelling surface area in m2 (elasticity),"ln nominal transaction price of the property (total price, Tomans)",log,OLS,759057.0,0.5708,se,"Quarter FE only; lnAge, lnArea (log-form robustness; sample smaller because ln(age) drops age=0)",elasticity,0.5667,0.0013,b (log-log),reported,0.4474653192172142,0.001026477704221596,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),435.9230769230769,759047.0,m2,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T10-c4,10,4,21,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0211,0.0022,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,759057.0,0.7296,se,"Region + quarter FE; lnAge, lnArea (log-form robustness; sample smaller because ln(age) drops age=0)",pct_premium,2.1321707347450536,0.22469131936877404,100*(exp(b - se^2/2) - 1),reported,0.01100776442886614,0.0011477289925831996,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.59090909090909,759047.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T10-c4,10,4,21,lnAge,age,A_structural,log,years (log of building age),-0.1069,0.0004,,,***,,,high,Log of building age in years (elasticity),"ln nominal transaction price of the property (total price, Tomans)",log,OLS,759057.0,0.7296,se,"Region + quarter FE; lnAge, lnArea (log-form robustness; sample smaller because ln(age) drops age=0)",elasticity,-0.1069,0.0004,b (log-log),reported,-0.29326204181834953,0.0010973322425382583,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-267.25,759047.0,years,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T10-c4,10,4,21,lnArea,living_area,A_structural,log,m2 (log of surface area),0.1081,0.0013,,,***,,,high,Log of dwelling surface area in m2 (elasticity),"ln nominal transaction price of the property (total price, Tomans)",log,OLS,759057.0,0.7296,se,"Region + quarter FE; lnAge, lnArea (log-form robustness; sample smaller because ln(age) drops age=0)",elasticity,0.1081,0.0013,b (log-log),reported,0.09501208608171699,0.0011426060305849406,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),83.15384615384616,759047.0,m2,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T10-c5,10,5,21,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0127,0.0022,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,759056.0,0.736,se,"Region + quarter + region x quarter + frame FE; lnAge, lnArea (log-form robustness; sample smaller because ln(age) drops age=0)",pct_premium,1.2778536556837583,0.22281181724644963,100*(exp(b - se^2/2) - 1),reported,0.006625786824444806,0.0011477740955731159,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.7727272727272725,759046.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T10-c5,10,5,21,lnAge,age,A_structural,log,years (log of building age),-0.1049,0.0005,,,***,,,high,Log of building age in years (elasticity),"ln nominal transaction price of the property (total price, Tomans)",log,OLS,759056.0,0.736,se,"Region + quarter + region x quarter + frame FE; lnAge, lnArea (log-form robustness; sample smaller because ln(age) drops age=0)",elasticity,-0.1049,0.0005,b (log-log),reported,-0.23411591356754177,0.00111590044598447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-209.79999999999998,759046.0,years,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T10-c5,10,5,21,lnArea,living_area,A_structural,log,m2 (log of surface area),0.1076,0.0013,,,***,,,high,Log of dwelling surface area in m2 (elasticity),"ln nominal transaction price of the property (total price, Tomans)",log,OLS,759056.0,0.736,se,"Region + quarter + region x quarter + frame FE; lnAge, lnArea (log-form robustness; sample smaller because ln(age) drops age=0)",elasticity,0.1076,0.0013,b (log-log),reported,0.09457662390101962,0.0011426543779862965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),82.76923076923077,759046.0,m2,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T11-c2,11,2,22,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0504,0.003,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,833282.0,0.4667,se,Region FE; age and area decile FE (categorised age/area robustness; decile FE not extracted),pct_premium,5.168695632552511,0.31550750667824307,100*(exp(b - se^2/2) - 1),reported,0.01840103914645345,0.0010952999491936578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.8,833272.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T11-c3,11,3,22,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),-0.0419,0.0026,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,833282.0,0.5759,se,Quarter FE; age and area decile FE (categorised age/area robustness; decile FE not extracted),pct_premium,-4.103756895344423,0.2493310748097131,100*(exp(b - se^2/2) - 1),reported,-0.017651418547080983,0.0010953147547114693,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.115384615384617,833272.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T11-c4,11,4,22,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0227,0.0021,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,833282.0,0.7444,se,Region + quarter FE; age and area decile FE (categorised age/area robustness; decile FE not extracted),pct_premium,2.295735000429966,0.21482151718182607,100*(exp(b - se^2/2) - 1),reported,0.011840845670532769,0.001095408630313604,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.80952380952381,833272.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab,602e1fb4b1e820fd13056357b14a38759c9354ab:T11-c5,11,5,22,M=1,transit_distance,D_location,binary,binary (within 400 m of metro station),0.0141,0.0021,,,***,,,high,M=1: property within 400 m of nearest (newly opened) metro station vs 400 m-3 km control ring,"ln nominal transaction price of the property (total price, Tomans)",log,OLS,833281.0,0.7504,se,Region + quarter + region x quarter + frame FE; age and area decile FE (categorised age/area robustness; decile FE not extracted),pct_premium,1.4197637546791153,0.21298197350955997,100*(exp(b - se^2/2) - 1),reported,0.0073552076207961704,0.0010954564541611317,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.714285714285714,833271.0,binary,,2021.0,Iran,Asia,Lower middle income,2010.0,2018.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c1,2,1,42,No of Bedrooms,bedrooms,A_structural,level,count,0.014671,,15.866329,0.0,,,,high,t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,OLS,326744.0,0.591,t,"Full sample; year dummies (2010 omitted), county dummies, lat/lon quadratic included; t and p in separate columns",semi_elasticity,1.4671,0.09246625353602587,100*b/1 (per unit count),|b/t|,0.027746745360949617,0.0017487816722412358,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.866329,326734.0,count,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,ols,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c2,2,2,42,No of Bedrooms,bedrooms,A_structural,level,count,0.017519,,19.144798,0.0,,,,high,t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,other,326744.0,,t,"Robinson's semi-parametric (partially linear) method, location handled non-parametrically; county dummies included; t and p in separate columns",semi_elasticity,1.7519,0.09150788637205781,100*b/1 (per unit count),|b/t|,0.033474197097174904,0.0017484748126971566,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.144798,326734.0,count,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,other,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c1,2,1,42,No of Full Baths,bathrooms,A_structural,level,count (full bathrooms),0.164688,,152.781209,0.0,,,,high,t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,OLS,326744.0,0.591,t,"Full sample; year dummies (2010 omitted), county dummies, lat/lon quadratic included; t and p in separate columns",semi_elasticity,16.4688,0.10779336089688885,100*b/1 (per unit count),|b/t|,0.25821930785876646,0.0016901247839894136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),152.781209,326734.0,count,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,ols,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c2,2,2,42,No of Full Baths,bathrooms,A_structural,level,count (full bathrooms),0.146963,,136.717485,0.0,,,,high,t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,other,326744.0,,t,"Robinson's semi-parametric (partially linear) method, location handled non-parametrically; county dummies included; t and p in separate columns",semi_elasticity,14.6963,0.10749393173813868,100*b/1 (per unit count),|b/t|,0.2326198417364866,0.001701463728187266,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),136.717485,326734.0,count,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,other,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c1,2,1,42,No of Half Baths,bathrooms,A_structural,level,count (half bathrooms),0.151836,,91.099069,0.0,,,,high,t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,OLS,326744.0,0.591,t,"Full sample; year dummies (2010 omitted), county dummies, lat/lon quadratic included; t and p in separate columns",semi_elasticity,15.1836,0.16667129715672505,100*b/1 (per unit count),|b/t|,0.1573874574059269,0.0017276516558684802,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),91.099069,326734.0,count,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,ols,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c2,2,2,42,No of Half Baths,bathrooms,A_structural,level,count (half bathrooms),0.132745,,79.822351,0.0,,,,high,t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,other,326744.0,,t,"Robinson's semi-parametric (partially linear) method, location handled non-parametrically; county dummies included; t and p in separate columns",semi_elasticity,13.2745,0.166300539055784,100*b/1 (per unit count),|b/t|,0.13830361849786582,0.0017326427593928652,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),79.822351,326734.0,count,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,other,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c1,2,1,42,No of Fireplaces,fireplace,B_interior,level,count,0.170455,,161.09964,0.0,,,,high,t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,OLS,326744.0,0.591,t,"Full sample; year dummies (2010 omitted), county dummies, lat/lon quadratic included; t and p in separate columns",semi_elasticity,17.0455,0.10580718864424526,100*b/1 (per unit count),|b/t|,0.271268762437529,0.0016838570367849921,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),161.09964,326734.0,count,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,ols,other,True,True,True
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c2,2,2,42,No of Fireplaces,fireplace,B_interior,level,count,0.145072,,137.00185,0.0,,,,high,t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,other,326744.0,,t,"Robinson's semi-parametric (partially linear) method, location handled non-parametrically; county dummies included; t and p in separate columns",semi_elasticity,14.507200000000001,0.10589054089415584,100*b/1 (per unit count),|b/t|,0.23307741979798047,0.0017012720616399008,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),137.00185,326734.0,count,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,other,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c1,2,1,42,Garage Dummy,garage,A_structural,binary,binary,0.170616,,71.760975,0.0,,,,high,t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,OLS,326744.0,0.591,t,"Full sample; year dummies (2010 omitted), county dummies, lat/lon quadratic included; t and p in separate columns",pct_premium,18.60318718412024,0.2819869515218971,100*(exp(b - se^2/2) - 1),|b/t|,0.12456482150188128,0.0017358295578046602,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),71.760975,326734.0,binary,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,ols,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c2,2,2,42,Garage Dummy,garage,A_structural,binary,binary,0.170824,,72.495021,0.0,,,,high,t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,other,326744.0,,t,"Robinson's semi-parametric (partially linear) method, location handled non-parametrically; county dummies included; t and p in separate columns",pct_premium,18.627865166874045,0.27953013073405475,100*(exp(b - se^2/2) - 1),|b/t|,0.12581893000096803,0.0017355527078331083,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),72.495021,326734.0,binary,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,other,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c1,2,1,42,Basement Dummy,basement,A_structural,binary,binary,0.138199,,80.941398,0.0,,,,high,t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,OLS,326744.0,0.591,t,"Full sample; year dummies (2010 omitted), county dummies, lat/lon quadratic included; t and p in separate columns",pct_premium,14.820234651955344,0.19604386790974618,100*(exp(b - se^2/2) - 1),|b/t|,0.14020467173343504,0.0017321750698379957,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),80.941398,326734.0,binary,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,ols,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c2,2,2,42,Basement Dummy,basement,A_structural,binary,binary,0.128803,,75.68174,0.0,,,,high,t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,other,326744.0,,t,"Robinson's semi-parametric (partially linear) method, location handled non-parametrically; county dummies included; t and p in separate columns",pct_premium,13.746437396654287,0.1935857129338164,100*(exp(b - se^2/2) - 1),|b/t|,0.13125633723647367,0.0017343197611005463,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),75.68174,326734.0,binary,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,other,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c1,2,1,42,Stories Dummy,storeys,A_structural,binary,binary (multi-storey dummy; definition not printed),0.014131,,8.167266,0.0,,,,high,Dummy for number of stories (mean 0.48); exact definition not printed; t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,OLS,326744.0,0.591,t,"Full sample; year dummies (2010 omitted), county dummies, lat/lon quadratic included; t and p in separate columns",pct_premium,1.4229796442986942,0.17548225692346803,100*(exp(b - se^2/2) - 1),|b/t|,0.014286808006754073,0.00174927668656244,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.167266,326734.0,binary,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,ols,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c2,2,2,42,Stories Dummy,storeys,A_structural,binary,binary (multi-storey dummy; definition not printed),0.026279,,15.247442,0.0,,,,high,Dummy for number of stories (mean 0.48); exact definition not printed; t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,other,326744.0,,t,"Robinson's semi-parametric (partially linear) method, location handled non-parametrically; county dummies included; t and p in separate columns",pct_premium,2.6625812770961987,0.1769394486197117,100*(exp(b - se^2/2) - 1),|b/t|,0.0266652322759925,0.0017488331666382138,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.247442,326734.0,binary,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,other,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c1,2,1,42,Age,age,A_structural,level,years,-0.014724,,-160.94147,0.0,,,,high,Enters with Age Squared; t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,OLS,326744.0,0.591,t,"Full sample; year dummies (2010 omitted), county dummies, lat/lon quadratic included; t and p in separate columns",semi_elasticity,-1.4724,0.009148667524908278,100*b/1 (per year),|b/t|,-0.27102199880989125,0.001683978646460053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-160.94147,326734.0,years,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,ols,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c2,2,2,42,Age,age,A_structural,level,years,-0.01629,,-164.96856,0.0,,,,high,Enters with Age Squared; t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,other,326744.0,,t,"Robinson's semi-parametric (partially linear) method, location handled non-parametrically; county dummies included; t and p in separate columns",semi_elasticity,-1.629,0.009874608834556112,100*b/1 (per year),|b/t|,-0.277287995472513,0.0016808535849043784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-164.96856,326734.0,years,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,other,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c1,2,1,42,Land Sq Feet (Log),lot_size,A_structural,log,sqft,0.183304,,159.507617,0.0,,,,high,Log of land square feet; Robinson column printed as .235341; t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,OLS,326744.0,0.591,t,"Full sample; year dummies (2010 omitted), county dummies, lat/lon quadratic included; t and p in separate columns",elasticity,0.183304,0.001149186499350686,b (log-log),|b/t|,0.2687825868496196,0.0016850768126616773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),159.507617,326734.0,sqft,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,ols,other,True,True,False
617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232,617738a89ff272112e6f8804b981aa1981f5a232:T2-c2,2,2,42,Land Sq Feet (Log),lot_size,A_structural,log,sqft,0.235341,,196.40403,0.0,,,,high,Log of land square feet; Robinson column printed as .235341; t-value and p-value printed in separate columns; p printed as 0.00; no stars used,log sale price,log,other,326744.0,,t,"Robinson's semi-parametric (partially linear) method, location handled non-parametrically; county dummies included; t and p in separate columns",elasticity,0.235341,0.0011982493434579728,b (log-log),|b/t|,0.3249529474124439,0.0016545126258989894,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),196.40403,326734.0,sqft,,2014.0,United States,North America,High income,2003.0,2010.0,single_family,transaction,working_paper,True,True,unknown,,2006.5,other,other,True,True,False
620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b:T4-c1,4,OLS,9,AREALOT,lot_size,A_structural,level,sqft,3.787e-06,,,0.003,**,,,high,"land area in square feet; stars: ** 99% level, * 95% level; p-value printed (SE not printed)","ln(MKTVALU), 2009 appraised market value of land and improvements (USD)",log,OLS,1607.0,,p,p-values in parentheses,semi_elasticity,0.004076292874807971,0.0013735353246660147,100*b/0.092903 (X per sqft->m2),|b/z(p)| (two-sided normal),0.0740591647932815,0.024954752291596768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9677379253417837,1597.0,sqft,,2012.0,United States,North America,High income,2009.0,2009.0,single_family,appraisal,journal,False,False,unknown,,2009.0,ols,journal,True,True,False
620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b:T4-c2,4,SAR,9,AREALOT,lot_size,A_structural,level,sqft,3.3899e-06,,,0.007,**,,,high,"land area in square feet; stars: ** 99% level, * 95% level; p-value printed (SE not printed)","ln(MKTVALU), 2009 appraised market value of land and improvements (USD)",log,spatial_lag,1607.0,,p,"spatial autoregressive (ML), rho 0.01007; p-values in parentheses; Table 5 total impacts not extracted",semi_elasticity,0.0036488579921604286,0.0013530102739311742,100*b/0.092903 (X per sqft->m2),|b/z(p)| (two-sided normal),0.06733125885025346,0.024966684145242248,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6968442608781262,1597.0,sqft,,2012.0,United States,North America,High income,2009.0,2009.0,single_family,appraisal,journal,False,False,unknown,,2009.0,spatial,journal,True,True,False
620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b:T4-c3,4,SEM,9,AREALOT,lot_size,A_structural,level,sqft,4.82604e-06,,,0.001,**,,,high,"land area in square feet; stars: ** 99% level, * 95% level; p-value printed (SE not printed)","ln(MKTVALU), 2009 appraised market value of land and improvements (USD)",log,spatial_error,1607.0,,p,"spatial error model (ML), lambda 0.32641; p-values in parentheses",semi_elasticity,0.005194706222745779,0.0015786853129105404,100*b/0.092903 (X per sqft->m2),|b/z(p)| (two-sided normal),0.08206267849670865,0.02493907060876609,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,1597.0,sqft,,2012.0,United States,North America,High income,2009.0,2009.0,single_family,appraisal,journal,False,False,unknown,,2009.0,spatial,journal,True,True,False
620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b:T4-c1,4,OLS,9,HALFBATHS,bathrooms,A_structural,level,count,0.1048,,,0.002,**,,,high,"number of half baths; stars: ** 99% level, * 95% level; p-value printed (SE not printed)","ln(MKTVALU), 2009 appraised market value of land and improvements (USD)",log,OLS,1607.0,,p,p-values in parentheses,semi_elasticity,10.48,3.391330800303558,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.07709816968086972,0.024948988309710252,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.090232306167813,1597.0,count,,2012.0,United States,North America,High income,2009.0,2009.0,single_family,appraisal,journal,False,False,unknown,,2009.0,ols,journal,True,True,False
620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b:T4-c3,4,SEM,9,HALFBATHS,bathrooms,A_structural,level,count,0.10348,,,0.001,**,,,high,"number of half baths; stars: ** 99% level, * 95% level; p-value printed (SE not printed)","ln(MKTVALU), 2009 appraised market value of land and improvements (USD)",log,spatial_error,1607.0,,p,"spatial error model (ML), lambda 0.32641; p-values in parentheses",semi_elasticity,10.348,3.144785271295551,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.08206267849670865,0.02493907060876609,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,1597.0,count,,2012.0,United States,North America,High income,2009.0,2009.0,single_family,appraisal,journal,False,False,unknown,,2009.0,spatial,journal,True,True,False
620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b:T4-c1,4,OLS,9,HEATING,heating,A_structural,binary,binary,0.31162,,,0.062,,,,high,"presence of a heating system (mean 0.99); stars: ** 99% level, * 95% level; p-value printed (SE not printed)","ln(MKTVALU), 2009 appraised market value of land and improvements (USD)",log,OLS,1607.0,,p,p-values in parentheses,pct_premium,34.67308970933223,22.802355073629485,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.046650351958594155,0.02499622694962295,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.866295743458108,1597.0,binary,,2012.0,United States,North America,High income,2009.0,2009.0,single_family,appraisal,journal,False,False,unknown,,2009.0,ols,journal,True,True,True
620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b:T4-c2,4,SAR,9,HEATING,heating,A_structural,binary,binary,0.26759,,,0.107,,,,high,"presence of a heating system (mean 0.99); stars: ** 99% level, * 95% level; p-value printed (SE not printed)","ln(MKTVALU), 2009 appraised market value of land and improvements (USD)",log,spatial_lag,1607.0,,p,"spatial autoregressive (ML), rho 0.01007; p-values in parentheses; Table 5 total impacts not extracted",pct_premium,28.892587448099462,21.695258031999728,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04030069137018994,0.025003141371515908,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6118251211466297,1597.0,binary,,2012.0,United States,North America,High income,2009.0,2009.0,single_family,appraisal,journal,False,False,unknown,,2009.0,spatial,journal,True,True,False
620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b:T4-c3,4,SEM,9,HEATING,heating,A_structural,binary,binary,0.31981,,,0.035,*,,,high,"presence of a heating system (mean 0.99); stars: ** 99% level, * 95% level; p-value printed (SE not printed)","ln(MKTVALU), 2009 appraised market value of land and improvements (USD)",log,spatial_error,1607.0,,p,"spatial error model (ML), lambda 0.32641; p-values in parentheses",pct_premium,36.11168382513961,20.885232737523197,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.05268517181817334,0.024988717211901088,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.108358399169109,1597.0,binary,,2012.0,United States,North America,High income,2009.0,2009.0,single_family,appraisal,journal,False,False,unknown,,2009.0,spatial,journal,True,True,True
620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b:T4-c1,4,OLS,9,DISTHW,highway_distance,D_location,level,feet,-6.6047e-06,,,0.017,*,,,high,"Euclidean distance to closest highway exit in feet; stars: ** 99% level, * 95% level; p-value printed (SE not printed)","ln(MKTVALU), 2009 appraised market value of land and improvements (USD)",log,OLS,1607.0,,p,p-values in parentheses,semi_elasticity,-2.1668963254593177,0.9079018323625219,100*b/0.0003048 (X per ft->km),|b/z(p)| (two-sided normal),-0.059617479817791794,0.024978961167390214,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3867077344922505,1597.0,ft,,2012.0,United States,North America,High income,2009.0,2009.0,single_family,appraisal,journal,False,False,unknown,,2009.0,ols,journal,True,True,False
620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b:T4-c2,4,SAR,9,DISTHW,highway_distance,D_location,level,feet,-5.6457e-06,,,0.041,*,,,high,"Euclidean distance to closest highway exit in feet; stars: ** 99% level, * 95% level; p-value printed (SE not printed)","ln(MKTVALU), 2009 appraised market value of land and improvements (USD)",log,spatial_lag,1607.0,,p,"spatial autoregressive (ML), rho 0.01007; p-values in parentheses; Table 5 total impacts not extracted",semi_elasticity,-1.8522637795275592,0.9064040032610451,100*b/0.0003048 (X per ft->km),|b/z(p)| (two-sided normal),-0.051069485359920175,0.024990817445299105,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0435300074398564,1597.0,ft,,2012.0,United States,North America,High income,2009.0,2009.0,single_family,appraisal,journal,False,False,unknown,,2009.0,spatial,journal,True,True,False
620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b,620cbd7217ca28bcea726920009e42496a17ea8b:T4-c3,4,SEM,9,DISTHW,highway_distance,D_location,level,feet,-6.7431e-06,,,0.029,*,,,high,"Euclidean distance to closest highway exit in feet; stars: ** 99% level, * 95% level; p-value printed (SE not printed)","ln(MKTVALU), 2009 appraised market value of land and improvements (USD)",log,spatial_error,1607.0,,p,"spatial error model (ML), lambda 0.32641; p-values in parentheses",semi_elasticity,-2.2123031496062993,1.0131975266300586,100*b/0.0003048 (X per ft->km),|b/z(p)| (two-sided normal),-0.05455703534770206,0.024986201951752177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1834865280065587,1597.0,ft,,2012.0,United States,North America,High income,2009.0,2009.0,single_family,appraisal,journal,False,False,unknown,,2009.0,spatial,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T3-c1,3,ATE,31,Treatment (home sales within 1.5 miles),hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs within 1.5 miles of non-impacted site),-0.6223,0.0946,,,***,,,high,sale within 1.5 miles of a hurricane-impacted Superfund site (pre-Harvey level effect in DiD),"log(sale price), nominal US$",log,OLS,2409.0,0.6394,se,"DID without matching (transactions within 1.5 miles of impacted or non-impacted Superfund sites); specification ATE; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-46.56875934001226,5.07726323454315,100*(exp(b - se^2/2) - 1),reported,-0.13311026792472427,0.020234985289537072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.578224101479915,2399.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,True
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T3-c2,3,Zones,31,Treatment (home sales within 1.5 miles),hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs within 1.5 miles of non-impacted site),-0.4958,0.1071,,,***,,,high,sale within 1.5 miles of a hurricane-impacted Superfund site (pre-Harvey level effect in DiD),"log(sale price), nominal US$",log,OLS,2409.0,0.642,se,"DID without matching (transactions within 1.5 miles of impacted or non-impacted Superfund sites); specification Zones; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-39.43997748022095,6.523283702174183,100*(exp(b - se^2/2) - 1),reported,-0.09409590751530952,0.02032608248263342,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.629318394024277,2399.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T3-c3,3,Exponential,31,Treatment (home sales within 1.5 miles),hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs within 1.5 miles of non-impacted site),-0.5678,0.0888,,,***,,,high,sale within 1.5 miles of a hurricane-impacted Superfund site (pre-Harvey level effect in DiD),"log(sale price), nominal US$",log,OLS,2409.0,0.6393,se,"DID without matching (transactions within 1.5 miles of impacted or non-impacted Superfund sites); specification Exponential; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-43.545925552062194,5.032926162454833,100*(exp(b - se^2/2) - 1),reported,-0.129448712956592,0.02024488501328878,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.394144144144144,2399.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T3-c4,3,Gaussian,31,Treatment (home sales within 1.5 miles),hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs within 1.5 miles of non-impacted site),-0.5686,0.0887,,,***,,,high,sale within 1.5 miles of a hurricane-impacted Superfund site (pre-Harvey level effect in DiD),"log(sale price), nominal US$",log,OLS,2409.0,0.6394,se,"DID without matching (transactions within 1.5 miles of impacted or non-impacted Superfund sites); specification Gaussian; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-43.59057011966455,5.023238254343976,100*(exp(b - se^2/2) - 1),reported,-0.12977171903265064,0.020244023000696644,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.410372040586245,2399.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T4-c1,4,ATE,32,Treatment (home sales within 1.5 miles),hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs within 1.5 miles of non-impacted site),-0.6067,0.1013,,,***,,,high,sale within 1.5 miles of a hurricane-impacted Superfund site (pre-Harvey level effect in DiD); matched sample,"log(sale price), nominal US$",log,OLS,1963.0,0.65,se,"DID with propensity-score matching; specification ATE; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-45.76430120486249,5.522337982986996,100*(exp(b - se^2/2) - 1),reported,-0.1342954725300279,0.022423160321891917,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.989141164856861,1953.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T4-c2,4,Zones,32,Treatment (home sales within 1.5 miles),hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs within 1.5 miles of non-impacted site),-0.4861,0.1117,,,***,,,high,sale within 1.5 miles of a hurricane-impacted Superfund site (pre-Harvey level effect in DiD); matched sample,"log(sale price), nominal US$",log,OLS,1963.0,0.6527,se,"DID with propensity-score matching; specification Zones; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-38.8804525228698,6.86977677566452,100*(exp(b - se^2/2) - 1),reported,-0.0979999305965116,0.022519218777268764,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.35183527305282,1953.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T4-c3,4,Exponential,32,Treatment (home sales within 1.5 miles),hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs within 1.5 miles of non-impacted site),-0.5566,0.0907,,,***,,,high,sale within 1.5 miles of a hurricane-impacted Superfund site (pre-Harvey level effect in DiD); matched sample,"log(sale price), nominal US$",log,OLS,1963.0,0.65,se,"DID with propensity-score matching; specification Exponential; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-42.91982029021777,5.198511133593405,100*(exp(b - se^2/2) - 1),reported,-0.1375426698661734,0.022413079692529515,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.136714443219404,1953.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T4-c4,4,Gaussian,32,Treatment (home sales within 1.5 miles),hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs within 1.5 miles of non-impacted site),-0.558,0.0906,,,***,,,high,sale within 1.5 miles of a hurricane-impacted Superfund site (pre-Harvey level effect in DiD); matched sample,"log(sale price), nominal US$",log,OLS,1963.0,0.6502,se,"DID with propensity-score matching; specification Gaussian; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-42.99915991905755,5.185514783919097,100*(exp(b - se^2/2) - 1),reported,-0.138031347628971,0.02241154138922002,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.158940397350994,1953.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T5-c1,5,ATE,33,Treatment,hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs 1.5-3 miles),-0.1283,0.052,,,**,,,high,DDD: pre-Harvey level effect of proximity to impacted site; reference 1.5-3 miles from impacted site,"log(sale price), nominal US$",log,OLS,5162.0,0.6832,se,"DDD without matching (adds control group 1.5-3 miles from impacted sites); specification ATE; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-12.159893869287552,4.573865206145785,100*(exp(b - se^2/2) - 1),reported,-0.03435413007455108,0.013923731596856241,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4673076923076924,5152.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T5-c2,5,Zones,33,Treatment,hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs 1.5-3 miles),-0.0691,0.051,,,,,,high,DDD: pre-Harvey level effect of proximity to impacted site; reference 1.5-3 miles from impacted site,"log(sale price), nominal US$",log,OLS,5162.0,0.6846,se,"DDD without matching (adds control group 1.5-3 miles from impacted sites); specification Zones; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-6.797952905080507,4.759490095591027,100*(exp(b - se^2/2) - 1),reported,-0.018873071448491614,0.013929473862128398,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3549019607843138,5152.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T5-c3,5,Exponential,33,Treatment,hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs 1.5-3 miles),-0.1027,0.0527,,,*,,,high,DDD: pre-Harvey level effect of proximity to impacted site; reference 1.5-3 miles from impacted site,"log(sale price), nominal US$",log,OLS,5162.0,0.6832,se,"DDD without matching (adds control group 1.5-3 miles from impacted sites); specification Exponential; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-9.885458815450443,4.755635626953473,100*(exp(b - se^2/2) - 1),reported,-0.027140128184829276,0.013926823323666043,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.94876660341556,5152.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T5-c4,5,Gaussian,33,Treatment,hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs 1.5-3 miles),-0.102,0.0524,,,*,,,high,DDD: pre-Harvey level effect of proximity to impacted site; reference 1.5-3 miles from impacted site,"log(sale price), nominal US$",log,OLS,5162.0,0.6831,se,"DDD without matching (adds control group 1.5-3 miles from impacted sites); specification Gaussian; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-9.820934891651056,4.731874850744914,100*(exp(b - se^2/2) - 1),reported,-0.02710948779603058,0.013926834906980415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.946564885496183,5152.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T5-c1,5,ATE,33,Control,hazard_site,E_environment,dummy,binary (within 1.5 miles of non-impacted Superfund site vs 1.5-3 miles from impacted site),0.2878,0.1435,,,**,,,high,DDD: level effect of proximity to a non-flooded Superfund site,"log(sale price), nominal US$",log,OLS,5162.0,0.6832,se,"DDD without matching (adds control group 1.5-3 miles from impacted sites); specification ATE; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,31.98312334798794,19.135589813470563,100*(exp(b - se^2/2) - 1),reported,0.027930679007349107,0.013926519935908953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.005574912891986,5152.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T5-c2,5,Zones,33,Control,hazard_site,E_environment,dummy,binary (within 1.5 miles of non-impacted Superfund site vs 1.5-3 miles from impacted site),0.2474,0.1428,,,*,,,high,DDD: level effect of proximity to a non-flooded Superfund site,"log(sale price), nominal US$",log,OLS,5162.0,0.6846,se,"DDD without matching (adds control group 1.5-3 miles from impacted sites); specification Zones; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,26.769980355399838,18.28827157623752,100*(exp(b - se^2/2) - 1),reported,0.024129987032068905,0.0139278987396097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7324929971988794,5152.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T5-c3,5,Exponential,33,Control,hazard_site,E_environment,dummy,binary (within 1.5 miles of non-impacted Superfund site vs 1.5-3 miles from impacted site),0.2794,0.1413,,,*,,,high,DDD: level effect of proximity to a non-flooded Superfund site,"log(sale price), nominal US$",log,OLS,5162.0,0.6832,se,"DDD without matching (adds control group 1.5-3 miles from impacted sites); specification Exponential; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,30.92011669626322,18.684610118354406,100*(exp(b - se^2/2) - 1),reported,0.027537948230310316,0.013926671742816208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9773531493276713,5152.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T5-c4,5,Gaussian,33,Control,hazard_site,E_environment,dummy,binary (within 1.5 miles of non-impacted Superfund site vs 1.5-3 miles from impacted site),0.2789,0.1421,,,*,,,high,DDD: level effect of proximity to a non-flooded Superfund site,"log(sale price), nominal US$",log,OLS,5162.0,0.6831,se,"DDD without matching (adds control group 1.5-3 miles from impacted sites); specification Gaussian; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,30.839840155212748,18.78100416206179,100*(exp(b - se^2/2) - 1),reported,0.02733406398685257,0.013926749704308895,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9627023223082334,5152.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T6-c1,6,ATE,34,Treatment,hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs 1.5-3 miles),-0.1727,0.0653,,,***,,,high,DDD matched: pre-Harvey level effect of proximity to impacted site,"log(sale price), nominal US$",log,OLS,4444.0,0.6944,se,"DDD with propensity-score matching; specification ATE; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-16.040197638613442,5.494276660715877,100*(exp(b - se^2/2) - 1),reported,-0.03968615619659654,0.015005825128186186,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.644716692189893,4434.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T6-c2,6,Zones,34,Treatment,hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs 1.5-3 miles),-0.1164,0.0614,,,*,,,high,DDD matched: pre-Harvey level effect of proximity to impacted site,"log(sale price), nominal US$",log,OLS,4444.0,0.6958,se,"DDD with propensity-score matching; specification Zones; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-11.155717190278146,5.465331301241179,100*(exp(b - se^2/2) - 1),reported,-0.028458422972404526,0.015011573629773522,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8957654723127035,4434.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T6-c3,6,Exponential,34,Treatment,hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs 1.5-3 miles),-0.1483,0.0633,,,**,,,high,DDD matched: pre-Harvey level effect of proximity to impacted site,"log(sale price), nominal US$",log,OLS,4444.0,0.6944,se,"DDD with propensity-score matching; specification Exponential; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-13.955316148434827,5.457551446534811,100*(exp(b - se^2/2) - 1),reported,-0.03516178873739154,0.015008369703822551,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3428120063191153,4434.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T6-c4,6,Gaussian,34,Treatment,hazard_site,E_environment,dummy,binary (within 1.5 miles of impacted Superfund site vs 1.5-3 miles),-0.1476,0.0628,,,**,,,high,DDD matched: pre-Harvey level effect of proximity to impacted site,"log(sale price), nominal US$",log,OLS,4444.0,0.6944,se,"DDD with propensity-score matching; specification Gaussian; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,-13.892349282970128,5.418234262139949,100*(exp(b - se^2/2) - 1),reported,-0.035274308583150456,0.015008310155974583,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3503184713375798,4434.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T6-c1,6,ATE,34,Control,hazard_site,E_environment,dummy,binary (within 1.5 miles of non-impacted Superfund site vs 1.5-3 miles from impacted site),0.2995,0.1424,,,**,,,high,DDD matched: level effect of proximity to a non-flooded Superfund site,"log(sale price), nominal US$",log,OLS,4444.0,0.6944,se,"DDD with propensity-score matching; specification ATE; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,33.557394391708485,19.212380827520615,100*(exp(b - se^2/2) - 1),reported,0.03156984605925037,0.0150101705470359,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1032303370786516,4434.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,True
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T6-c2,6,Zones,34,Control,hazard_site,E_environment,dummy,binary (within 1.5 miles of non-impacted Superfund site vs 1.5-3 miles from impacted site),0.2656,0.1401,,,*,,,high,DDD matched: level effect of proximity to a non-flooded Superfund site,"log(sale price), nominal US$",log,OLS,4444.0,0.6958,se,"DDD with propensity-score matching; specification Zones; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,29.147631597498737,18.272027899087075,100*(exp(b - se^2/2) - 1),reported,0.028458771709249205,0.01501157348066948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.895788722341185,4434.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T6-c3,6,Exponential,34,Control,hazard_site,E_environment,dummy,binary (within 1.5 miles of non-impacted Superfund site vs 1.5-3 miles from impacted site),0.2917,0.1398,,,**,,,high,DDD matched: level effect of proximity to a non-flooded Superfund site,"log(sale price), nominal US$",log,OLS,4444.0,0.6944,se,"DDD with propensity-score matching; specification Exponential; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,32.56832408416239,18.71504483088682,100*(exp(b - se^2/2) - 1),reported,0.03131975118633932,0.015010288707062861,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.086552217453505,4434.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b,63065c2cad027c9578aace5fb84b3bd4ba000e2b:T6-c4,6,Gaussian,34,Control,hazard_site,E_environment,dummy,binary (within 1.5 miles of non-impacted Superfund site vs 1.5-3 miles from impacted site),0.2907,0.1408,,,**,,,high,DDD matched: level effect of proximity to a non-flooded Superfund site,"log(sale price), nominal US$",log,OLS,4444.0,0.6944,se,"DDD with propensity-score matching; specification Gaussian; structural and spatial controls, year FE, parallel-trend terms and census-tract FE included but not reported",pct_premium,32.41724257969973,18.830075471936777,100*(exp(b - se^2/2) - 1),reported,0.03099102031620059,0.01501044258865168,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0646306818181817,4434.0,binary,,2024.0,United States,North America,High income,2013.0,2019.0,single_family,transaction,journal,True,True,clustered,,2016.0,ols,journal,True,True,False
66b74975968370c75371207845d963de2413a23e,66b74975968370c75371207845d963de2413a23e,66b74975968370c75371207845d963de2413a23e:T3-m14,3,Model 14,7,Area (Sq. M.),living_area,A_structural,level,m2,0.018,0.001,23.435,0.0,,,,high,Floor area of flat in m2 (quadratic specification with Area^2),"ln asking (listing) price of flat, euros",log,OLS,3479.0,0.653,se,"Final model (14) after stepwise family of models and Mahalanobis outlier removal; only variables significant at 95% retained; adjusted R2 0.652; SE, standardized beta, t and Sig. in separate columns",semi_elasticity,1.7999999999999998,0.1,100*b/1 (X per m2->m2),reported,0.36969980804382985,0.015775541200931508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.435,3469.0,m2,,2017.0,Spain,Europe,High income,2014.0,2014.0,condo_apartment,listing,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
66b74975968370c75371207845d963de2413a23e,66b74975968370c75371207845d963de2413a23e,66b74975968370c75371207845d963de2413a23e:T3-m14,3,Model 14,7,AC,air_conditioning,A_structural,binary,binary,0.101,0.013,7.503,0.0,,,,high,Air conditioning dummy,"ln asking (listing) price of flat, euros",log,OLS,3479.0,0.653,se,"Final model (14) after stepwise family of models and Mahalanobis outlier removal; only variables significant at 95% retained; adjusted R2 0.652; SE, standardized beta, t and Sig. in separate columns",pct_premium,10.61831653366292,1.4381596342924505,100*(exp(b - se^2/2) - 1),reported,0.12636802948431225,0.016842333664442523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.503,3469.0,binary,,2017.0,Spain,Europe,High income,2014.0,2014.0,condo_apartment,listing,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
66b74975968370c75371207845d963de2413a23e,66b74975968370c75371207845d963de2413a23e,66b74975968370c75371207845d963de2413a23e:T3-m14,3,Model 14,7,Swiming pool,pool,C_exterior,binary,binary,0.136,0.026,5.204,0.0,,,,high,Condominium swimming pool dummy,"ln asking (listing) price of flat, euros",log,OLS,3479.0,0.653,se,"Final model (14) after stepwise family of models and Mahalanobis outlier removal; only variables significant at 95% retained; adjusted R2 0.652; SE, standardized beta, t and Sig. in separate columns",pct_premium,14.52947185510951,2.9787729233466407,100*(exp(b - se^2/2) - 1),reported,0.08801293555441606,0.016912554872101474,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.204,3469.0,binary,,2017.0,Spain,Europe,High income,2014.0,2014.0,condo_apartment,listing,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
66b74975968370c75371207845d963de2413a23e,66b74975968370c75371207845d963de2413a23e,66b74975968370c75371207845d963de2413a23e:T3-m14,3,Model 14,7,Number of baths,bathrooms,A_structural,level,count,0.062,0.012,5.189,0.0,,,,high,Number of bathrooms,"ln asking (listing) price of flat, euros",log,OLS,3479.0,0.653,se,"Final model (14) after stepwise family of models and Mahalanobis outlier removal; only variables significant at 95% retained; adjusted R2 0.652; SE, standardized beta, t and Sig. in separate columns",semi_elasticity,6.2,1.2,100*b/1 (per unit count),reported,0.08776120394844175,0.01691293196154206,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.189,3469.0,count,,2017.0,Spain,Europe,High income,2014.0,2014.0,condo_apartment,listing,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
66b74975968370c75371207845d963de2413a23e,66b74975968370c75371207845d963de2413a23e,66b74975968370c75371207845d963de2413a23e:T3-m14,3,Model 14,7,Heating,heating,A_structural,binary,binary,0.046,0.013,3.453,0.001,,,,high,Heating dummy,"ln asking (listing) price of flat, euros",log,OLS,3479.0,0.653,se,"Final model (14) after stepwise family of models and Mahalanobis outlier removal; only variables significant at 95% retained; adjusted R2 0.652; SE, standardized beta, t and Sig. in separate columns",pct_premium,4.698593690729247,1.3611967342440183,100*(exp(b - se^2/2) - 1),reported,0.0585260692760948,0.0169493394949594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.453,3469.0,binary,,2017.0,Spain,Europe,High income,2014.0,2014.0,condo_apartment,listing,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
66b74975968370c75371207845d963de2413a23e,66b74975968370c75371207845d963de2413a23e,66b74975968370c75371207845d963de2413a23e:T3-m14,3,Model 14,7,Renewal,renovation,A_structural,binary,binary,0.043,0.017,2.512,0.012,,,,high,Renewed/renovated flat dummy,"ln asking (listing) price of flat, euros",log,OLS,3479.0,0.653,se,"Final model (14) after stepwise family of models and Mahalanobis outlier removal; only variables significant at 95% retained; adjusted R2 0.652; SE, standardized beta, t and Sig. in separate columns",pct_premium,4.378705672312377,1.7746944212460416,100*(exp(b - se^2/2) - 1),reported,0.04261111034721558,0.016963021635038048,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.512,3469.0,binary,,2017.0,Spain,Europe,High income,2014.0,2014.0,condo_apartment,listing,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c1,2,1,19,"DISTi,STN 5 min",transit_distance,D_location,dummy,minutes,0.0015,0.0279,,,,,,high,Dummy: house within 5 min walking distance of a train station (reference: beyond 20 min / beyond 40 min in restricted samples); pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,129521.0,0.4541,se,"(1) full sample, no neighbourhood controls; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,0.11114121612580963,2.794188140319964,100*(exp(b - se^2/2) - 1),reported,0.00014939419503944283,0.0027787320277336365,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.053763440860215055,129511.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c1,2,1,19,"DISTi,STN 5−10 min",transit_distance,D_location,dummy,minutes,-0.0064,0.0162,,,,,,high,Dummy: 5-10 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,129521.0,0.4541,se,"(1) full sample, no neighbourhood controls; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-0.6509937940466504,1.6096651069342212,100*(exp(b - se^2/2) - 1),reported,-0.0010977700284121328,0.002778730384418211,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.39506172839506176,129511.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c1,2,1,19,"DISTi,STN 10−15 min",transit_distance,D_location,dummy,minutes,-0.0123,0.0142,,,,,,high,Dummy: 10-15 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,129521.0,0.4541,se,"(1) full sample, no neighbourhood controls; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-1.2324246682465345,1.4026409768457313,100*(exp(b - se^2/2) - 1),reported,-0.002406922909851461,0.002778724009747215,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8661971830985915,129511.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c1,2,1,19,"DISTi,STN 15−20 min",transit_distance,D_location,dummy,minutes,-0.0141,0.0208,,,,,,high,Dummy: 15-20 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,129521.0,0.4541,se,"(1) full sample, no neighbourhood controls; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-1.4214328783897834,2.0508777940326186,100*(exp(b - se^2/2) - 1),reported,-0.0018836563711302414,0.0027787271290431927,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6778846153846154,129511.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c2,2,2,19,"DISTi,STN 5 min",transit_distance,D_location,dummy,minutes,0.009,0.028,,,,,,high,Dummy: house within 5 min walking distance of a train station (reference: beyond 20 min / beyond 40 min in restricted samples); pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,129521.0,0.4558,se,"(2) full sample + neighbourhood controls; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,0.8645155366612256,2.82531374096683,100*(exp(b - se^2/2) - 1),reported,0.0008931635197675098,0.0027787309503878085,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3214285714285714,129511.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c2,2,2,19,"DISTi,STN 5−10 min",transit_distance,D_location,dummy,minutes,-0.0005,0.0171,,,,,,high,Dummy: 5-10 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,129521.0,0.4558,se,"(2) full sample + neighbourhood controls; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-0.06459962545155573,1.7091452137143797,100*(exp(b - se^2/2) - 1),reported,-8.12494751336406e-05,0.0027787320495705086,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.029239766081871343,129511.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c2,2,2,19,"DISTi,STN 10−15 min",transit_distance,D_location,dummy,minutes,-0.0071,0.0143,,,,,,high,Dummy: 10-15 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,129521.0,0.4558,se,"(2) full sample + neighbourhood controls; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-0.7176370987735714,1.4198829579990748,100*(exp(b - se^2/2) - 1),reported,-0.0013796488699768577,0.0027787294141787414,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4965034965034965,129511.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c2,2,2,19,"DISTi,STN 15−20 min",transit_distance,D_location,dummy,minutes,-0.0106,0.0217,,,,,,high,Dummy: 15-20 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,129521.0,0.4558,se,"(2) full sample + neighbourhood controls; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-1.077695301866366,2.147119480988287,100*(exp(b - se^2/2) - 1),reported,-0.0013573517368230942,0.0027787294989680324,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.48847926267281105,129511.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c2,2,2,19,"DISTi,MOT 10 min",highway_distance,D_location,dummy,minutes,-0.0551,0.0194,,,***,,,high,Dummy: within 10 min driving distance of a motorway access point; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,129521.0,0.4558,se,"(2) full sample + neighbourhood controls; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-5.378757083851527,1.8359975780916555,100*(exp(b - se^2/2) - 1),reported,-0.007891926205348832,0.0027786455242063035,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.8402061855670104,129511.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c3,2,3,19,"DISTi,STN 5 min",transit_distance,D_location,dummy,minutes,0.0077,0.0296,,,,,,high,Dummy: house within 5 min walking distance of a train station (reference: beyond 20 min / beyond 40 min in restricted samples); pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,90745.0,0.4738,se,"(3) walking distance to station <= 40 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,0.7288351683896632,2.9828799748571697,100*(exp(b - se^2/2) - 1),reported,0.0008635976072683602,0.0033198037889796703,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.26013513513513514,90735.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c3,2,3,19,"DISTi,STN 5−10 min",transit_distance,D_location,dummy,minutes,-0.006,0.0168,,,,,,high,Dummy: 5-10 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,90745.0,0.4738,se,"(3) walking distance to station <= 40 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-0.6122301863756063,1.669950179610611,100*(exp(b - se^2/2) - 1),reported,-0.0011856438191163174,0.0033198026935256893,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.35714285714285715,90735.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c3,2,3,19,"DISTi,STN 10−15 min",transit_distance,D_location,dummy,minutes,-0.0066,0.0144,,,,,,high,Dummy: 10-15 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,90745.0,0.4738,se,"(3) walking distance to station <= 40 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-0.6681260463003547,1.4305272943146583,100*(exp(b - se^2/2) - 1),reported,-0.0015215755426396735,0.0033198011839411052,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.45833333333333337,90735.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c3,2,3,19,"DISTi,STN 15−20 min",transit_distance,D_location,dummy,minutes,-0.016,0.0187,,,,,,high,Dummy: 15-20 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,90745.0,0.4738,se,"(3) walking distance to station <= 40 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-1.6044734644099723,1.8403180885033832,100*(exp(b - se^2/2) - 1),reported,-0.0028404634305284693,0.003319791634430149,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8556149732620321,90735.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c3,2,3,19,"DISTi,MOT 10 min",highway_distance,D_location,dummy,minutes,-0.0659,0.0235,,,***,,,high,Dummy: within 10 min driving distance of a motorway access point; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,90745.0,0.4738,se,"(3) walking distance to station <= 40 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-6.403399723830983,2.200127532838317,100*(exp(b - se^2/2) - 1),reported,-0.009309177508785614,0.0033196611753636106,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.804255319148936,90735.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c4,2,4,19,"DISTi,STN 5 min",transit_distance,D_location,dummy,minutes,0.0261,0.0797,,,,,,high,Dummy: house within 5 min walking distance of a train station (reference: beyond 20 min / beyond 40 min in restricted samples); pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,13283.0,0.4458,se,"(4) <= 40 min walk & commuting 60-40 min to Berlin; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,2.318872820183704,8.180755393970315,100*(exp(b - se^2/2) - 1),reported,0.002842469964100446,0.008679879545548105,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.32747804265997493,13273.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c4,2,4,19,"DISTi,STN 5−10 min",transit_distance,D_location,dummy,minutes,-0.0167,0.0306,,,,,,high,Dummy: 5-10 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,13283.0,0.4458,se,"(4) <= 40 min walk & commuting 60-40 min to Berlin; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-1.7021646566881765,3.0093223362777426,100*(exp(b - se^2/2) - 1),reported,-0.004737024432872705,0.008679817224305674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5457516339869282,13273.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c4,2,4,19,"DISTi,STN 10−15 min",transit_distance,D_location,dummy,minutes,0.0356,0.0348,,,,,,high,Dummy: 10-15 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,13283.0,0.4458,se,"(4) <= 40 min walk & commuting 60-40 min to Berlin; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,3.561399219460859,3.6061196094166097,100*(exp(b - se^2/2) - 1),reported,0.008879102849681849,0.008679572448565404,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0229885057471264,13273.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c4,2,4,19,"DISTi,STN 15−20 min",transit_distance,D_location,dummy,minutes,-0.0055,0.0493,,,,,,high,Dummy: 15-20 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,13283.0,0.4458,se,"(4) <= 40 min walk & commuting 60-40 min to Berlin; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-0.6692748127798742,4.902959429732971,100*(exp(b - se^2/2) - 1),reported,-0.0009683470177955147,0.008679910541330705,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.11156186612576065,13273.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c4,2,4,19,"DISTi,MOT 10 min",highway_distance,D_location,dummy,minutes,-0.0586,0.0555,,,,,,high,Dummy: within 10 min driving distance of a motorway access point; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,13283.0,0.4458,se,"(4) <= 40 min walk & commuting 60-40 min to Berlin; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-5.836742192567101,5.234115796467052,100*(exp(b - se^2/2) - 1),reported,-0.00916435381012495,0.008679550110271925,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0558558558558557,13273.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c5,2,5,19,"DISTi,STN 5 min",transit_distance,D_location,dummy,minutes,0.048,0.0289,,,,,,high,Dummy: house within 5 min walking distance of a train station (reference: beyond 20 min / beyond 40 min in restricted samples); pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,34930.0,0.5127,se,"(5) <= 40 min walk & commuting 40-30 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,4.873260788472034,3.0321031938877203,100*(exp(b - se^2/2) - 1),reported,0.008887694616586282,0.00535113280040299,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6608996539792389,34920.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c5,2,5,19,"DISTi,STN 5−10 min",transit_distance,D_location,dummy,minutes,-0.0036,0.0233,,,,,,high,Dummy: 5-10 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,34930.0,0.5127,se,"(5) <= 40 min walk & commuting 40-30 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-0.3863960618378459,2.3216270802982146,100*(exp(b - se^2/2) - 1),reported,-0.0008268168406465103,0.005351342329739914,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.15450643776824033,34920.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c5,2,5,19,"DISTi,STN 10−15 min",transit_distance,D_location,dummy,minutes,-0.0069,0.0208,,,,,,high,Dummy: 10-15 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,34930.0,0.5127,se,"(5) <= 40 min walk & commuting 40-30 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-0.7091058952247042,2.0656974007130575,100*(exp(b - se^2/2) - 1),reported,-0.001775202717105866,0.005351335726927828,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3317307692307692,34920.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c5,2,5,19,"DISTi,STN 15−20 min",transit_distance,D_location,dummy,minutes,-0.009,0.0204,,,,,,high,Dummy: 15-20 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,34930.0,0.5127,se,"(5) <= 40 min walk & commuting 40-30 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-0.9165815455939863,2.021722372696683,100*(exp(b - se^2/2) - 1),reported,-0.0023608805494115216,0.005351329245332783,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4411764705882352,34920.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c5,2,5,19,"DISTi,MOT 10 min",highway_distance,D_location,dummy,minutes,-0.0561,0.0392,,,,,,high,Dummy: within 10 min driving distance of a motorway access point; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,34930.0,0.5127,se,"(5) <= 40 min walk & commuting 40-30 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-5.5281538296610755,3.7061427798810334,100*(exp(b - se^2/2) - 1),reported,-0.007658204178609713,0.005351187233538338,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4311224489795917,34920.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c6,2,6,19,"DISTi,STN 5 min",transit_distance,D_location,dummy,minutes,-0.0735,0.0578,,,,,,high,Dummy: house within 5 min walking distance of a train station (reference: beyond 20 min / beyond 40 min in restricted samples); pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,36117.0,0.5258,se,"(6) <= 40 min walk & commuting <= 30 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-7.241460624493645,5.370406922674981,100*(exp(b - se^2/2) - 1),reported,-0.006691971351515163,0.005262529851939815,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2716262975778547,36107.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c6,2,6,19,"DISTi,STN 5−10 min",transit_distance,D_location,dummy,minutes,-0.0139,0.0236,,,,,,high,Dummy: 5-10 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,36117.0,0.5258,se,"(6) <= 40 min walk & commuting <= 30 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-1.4078438721649378,2.3274229351171387,100*(exp(b - se^2/2) - 1),reported,-0.003099595402491436,0.00526262240998546,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5889830508474576,36107.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c6,2,6,19,"DISTi,STN 10−15 min",transit_distance,D_location,dummy,minutes,-0.0284,0.0202,,,,,,high,Dummy: 10-15 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,36117.0,0.5258,se,"(6) <= 40 min walk & commuting <= 30 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-2.819879787261348,1.9634389682551536,100*(exp(b - se^2/2) - 1),reported,-0.007398767501167915,0.005262503645196897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.405940594059406,36107.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c6,2,6,19,"DISTi,STN 15−20 min",transit_distance,D_location,dummy,minutes,-0.0269,0.0232,,,,,,high,Dummy: 15-20 min walking distance to train station; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,36117.0,0.5258,se,"(6) <= 40 min walk & commuting <= 30 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-2.6803359409782512,2.2584239114358615,100*(exp(b - se^2/2) - 1),reported,-0.006101835665632111,0.005262549719058177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1594827586206897,36107.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T2-c6,2,6,19,"DISTi,MOT 10 min",highway_distance,D_location,dummy,minutes,-0.0527,0.0329,,,,,,high,Dummy: within 10 min driving distance of a motorway access point; pre-LEZ level effect of distance band (DiD base term); POST x DIST interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,36117.0,0.5258,se,"(6) <= 40 min walk & commuting <= 30 min; municipality and quarter FE; SE clustered at municipality level; within R2; property characteristics (living space, base area, rooms, age, under construction, detached) included but NOT printed",pct_premium,-5.184871393252621,3.1211064325607834,100*(exp(b - se^2/2) - 1),reported,-0.008429534333651942,0.005262460713038879,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6018237082066868,36107.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c1,6,1,42,"DISTi,STN 5 min",transit_distance,D_location,dummy,minutes,-0.0844,0.0583,,,,,,high,Dummy: house within 5 min walking distance of a train station (reference: beyond 20 min / beyond 40 min in restricted samples); pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,48450.0,0.5337,se,"(1) commuting <= 30 min, semi-annual post effects; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-8.24970144011371,5.35814053811093,100*(exp(b - se^2/2) - 1),reported,-0.006577523824300619,0.004543479134558366,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4476843910806176,48440.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c1,6,1,42,"DISTi,STN 5−10 min",transit_distance,D_location,dummy,minutes,-0.028,0.0253,,,,,,high,Dummy: 5-10 min walking distance to train station; pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,48450.0,0.5337,se,"(1) commuting <= 30 min, semi-annual post effects; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-2.7922791438630634,2.4601425680071545,100*(exp(b - se^2/2) - 1),reported,-0.005028401558607443,0.0045435199797417255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1067193675889329,48440.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c1,6,1,42,"DISTi,STN 10−15 min",transit_distance,D_location,dummy,minutes,-0.0385,0.0212,,,*,,,high,Dummy: 10-15 min walking distance to train station; pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,48450.0,0.5337,se,"(1) commuting <= 30 min, semi-annual post effects; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-3.798450367478423,2.0399312140484134,100*(exp(b - se^2/2) - 1),reported,-0.00825102717684776,0.004543422757121365,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8160377358490565,48440.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c1,6,1,42,"DISTi,STN 15−20 min",transit_distance,D_location,dummy,minutes,-0.0297,0.0222,,,,,,high,Dummy: 15-20 min walking distance to train station; pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,48450.0,0.5337,se,"(1) commuting <= 30 min, semi-annual post effects; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-2.950246858679395,2.155035498160236,100*(exp(b - se^2/2) - 1),reported,-0.006078457498676391,0.004543493483859121,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3378378378378377,48440.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c2,6,2,42,"DISTi,STN 5 min",transit_distance,D_location,dummy,minutes,-0.1693,0.1056,,,,,,high,Dummy: house within 5 min walking distance of a train station (reference: beyond 20 min / beyond 40 min in restricted samples); pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,48450.0,0.5336,se,"(2) commuting <= 30 min, with linear trend; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-16.043861144660355,8.915339016821099,100*(exp(b - se^2/2) - 1),reported,-0.007284159564731708,0.004543456881486523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.603219696969697,48440.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c2,6,2,42,"DISTi,STN 5−10 min",transit_distance,D_location,dummy,minutes,-0.1354,0.0416,,,***,,,high,Dummy: 5-10 min walking distance to train station; pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,48450.0,0.5336,se,"(2) commuting <= 30 min, with linear trend; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-12.73888844950568,3.6332046200790638,100*(exp(b - se^2/2) - 1),reported,-0.014786853897625173,0.0045430806657400825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.254807692307692,48440.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c2,6,2,42,"DISTi,STN 10−15 min",transit_distance,D_location,dummy,minutes,-0.0708,0.0375,,,*,,,high,Dummy: 10-15 min walking distance to train station; pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,48450.0,0.5336,se,"(2) commuting <= 30 min, with linear trend; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-6.900663176395982,3.493680761761865,100*(exp(b - se^2/2) - 1),reported,-0.008577958566104407,0.004543410257470555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8880000000000001,48440.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c2,6,2,42,"DISTi,STN 15−20 min",transit_distance,D_location,dummy,minutes,-0.0928,0.05,,,*,,,high,Dummy: 15-20 min walking distance to train station; pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,48450.0,0.5336,se,"(2) commuting <= 30 min, with linear trend; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-8.976275075951056,4.556878786106425,100*(exp(b - se^2/2) - 1),reported,-0.008432579865371692,0.004543415875739058,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8559999999999999,48440.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c3,6,3,42,"DISTi,STN 5 min",transit_distance,D_location,dummy,minutes,0.0474,0.0286,,,*,,,high,Dummy: house within 5 min walking distance of a train station (reference: beyond 20 min / beyond 40 min in restricted samples); pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,47949.0,0.5355,se,"(3) commuting > 30-40 min, semi-annual post effects; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,4.811259698627457,2.9988282373884956,100*(exp(b - se^2/2) - 1),reported,0.007569294132673923,0.004567126839545869,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6573426573426573,47939.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c3,6,3,42,"DISTi,STN 5−10 min",transit_distance,D_location,dummy,minutes,-0.007,0.0249,,,,,,high,Dummy: 5-10 min walking distance to train station; pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,47949.0,0.5355,se,"(3) commuting > 30-40 min, semi-annual post effects; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-0.728335189776308,2.4726308629037552,100*(exp(b - se^2/2) - 1),reported,-0.0012839669641721856,0.004567253915412488,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.28112449799196787,47939.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c3,6,3,42,"DISTi,STN 10−15 min",transit_distance,D_location,dummy,minutes,-0.009,0.0208,,,,,,high,Dummy: 10-15 min walking distance to train station; pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,47949.0,0.5355,se,"(3) commuting > 30-40 min, semi-annual post effects; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-0.9173979895983009,2.061363987847598,100*(exp(b - se^2/2) - 1),reported,-0.00197621340646221,0.004567248761601552,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.43269230769230765,47939.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c3,6,3,42,"DISTi,STN 15−20 min",transit_distance,D_location,dummy,minutes,-0.0101,0.0211,,,,,,high,Dummy: 15-20 min walking distance to train station; pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,47949.0,0.5355,se,"(3) commuting > 30-40 min, semi-annual post effects; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-1.0269509763771945,2.0887962591405014,100*(exp(b - se^2/2) - 1),reported,-0.0021862176460033422,0.004567246765412924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.47867298578199047,47939.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c4,6,4,42,"DISTi,STN 5 min",transit_distance,D_location,dummy,minutes,0.0495,0.0594,,,,,,high,Dummy: house within 5 min walking distance of a train station (reference: beyond 20 min / beyond 40 min in restricted samples); pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,47949.0,0.5359,se,"(4) commuting > 30-40 min, with linear trend; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,4.889352202889574,6.241428817756057,100*(exp(b - se^2/2) - 1),reported,0.00380602049987201,0.004567224599846412,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8333333333333334,47939.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c4,6,4,42,"DISTi,STN 5−10 min",transit_distance,D_location,dummy,minutes,-0.0742,0.0416,,,*,,,high,Dummy: 5-10 min walking distance to train station; pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,47949.0,0.5359,se,"(4) commuting > 30-40 min, with linear trend; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-7.231707478949822,3.862501668790813,100*(exp(b - se^2/2) - 1),reported,-0.008146136427174542,0.004567106137068207,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7836538461538463,47939.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c4,6,4,42,"DISTi,STN 10−15 min",transit_distance,D_location,dummy,minutes,-0.1258,0.0403,,,***,,,high,Dummy: 10-15 min walking distance to train station; pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted,"log nominal posted (listing) house price, EUR",log,OLS,47949.0,0.5359,se,"(4) commuting > 30-40 min, with linear trend; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-11.892457608311036,3.5536184851665684,100*(exp(b - se^2/2) - 1),reported,-0.01425564841293555,0.004566793569485713,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.1215880893300243,47939.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa,670518142f78514470ad2ea85cc37f0ccb4483aa:T6-c4,6,4,42,"DISTi,STN 15−20 min",transit_distance,D_location,dummy,minutes,-0.0044,0.0394,,,*,,,high,"Dummy: 15-20 min walking distance to train station; pre-LEZ level effect of distance band; POST x DIST and trend interactions not extracted; star placement for this cell ambiguous in flattened text (0.0044 (0.0394) *) - likely a transcription artefact, beta/se=0.11","log nominal posted (listing) house price, EUR",log,OLS,47949.0,0.5359,se,"(4) commuting > 30-40 min, with linear trend; extended post period to end 2012; walking distance <= 40 min; bootstrapped SEs (500 reps); municipality and quarter FE; property and neighbourhood controls included but not printed",pct_premium,-0.5162806664517294,3.922702083323984,100*(exp(b - se^2/2) - 1),reported,-0.0005100490146860797,0.0045672570860526215,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.11167512690355332,47939.0,minutes,,2022.0,Germany,Europe,High income,2008.0,2011.0,single_family,listing,journal,True,True,clustered,,2009.5,ols,journal,True,True,False
67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb:T4-c1,4,1,13,DCBD,cbd_distance,D_location,level,km,-0.326,,-55.863,0.0,***,,,high,Distance to CBD (Citizen Centre) in km; p-value printed as .000; *** significant at 1%,ln(price) of new housing unit,log,OLS,25323.0,0.724,t,"Global hedonic price model (HPM), semi-log OLS; 25,323 new-housing transactions, Shenzhen, July-December 2015; t-ratio and p-value printed in separate columns (no parentheses); only variables significant at 1% listed",semi_elasticity,-32.6,0.5835705207382347,100*b/1 (X per km->km),|b/t|,-0.3312895668415053,0.005930393406038081,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-55.863,25313.0,km,,2016.0,China,Asia,Upper middle income,2015.0,2015.0,condo_apartment,transaction,journal,False,False,unknown,social media check-in hot-spot analysis (Getis-Ord Gi*),2015.0,ols,journal,True,True,True
67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb:T4-c1,4,1,13,DPark,green_space,E_environment,level,km,-0.111,,-27.376,0.0,***,,,high,Distance to nearest park (km); p-value printed as .000; *** significant at 1%,ln(price) of new housing unit,log,OLS,25323.0,0.724,t,"Global hedonic price model (HPM), semi-log OLS; 25,323 new-housing transactions, Shenzhen, July-December 2015; t-ratio and p-value printed in separate columns (no parentheses); only variables significant at 1% listed",semi_elasticity,-11.1,0.40546464056107534,100*b/1 (X per km->km),|b/t|,-0.16957522858264115,0.0061943026221011515,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-27.376,25313.0,km,,2016.0,China,Asia,Upper middle income,2015.0,2015.0,condo_apartment,transaction,journal,False,False,unknown,social media check-in hot-spot analysis (Getis-Ord Gi*),2015.0,ols,journal,True,True,False
67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb:T4-c1,4,1,13,NumWash,bathrooms,A_structural,level,count,0.094,,21.743,0.0,***,,,high,Number of bathrooms; p-value printed as .000; *** significant at 1%,ln(price) of new housing unit,log,OLS,25323.0,0.724,t,"Global hedonic price model (HPM), semi-log OLS; 25,323 new-housing transactions, Shenzhen, July-December 2015; t-ratio and p-value printed in separate columns (no parentheses); only variables significant at 1% listed",semi_elasticity,9.4,0.43232304649772346,100*b/1 (per unit count),|b/t|,0.13540338270148036,0.006227447118680972,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.743,25313.0,count,,2016.0,China,Asia,Upper middle income,2015.0,2015.0,condo_apartment,transaction,journal,False,False,unknown,social media check-in hot-spot analysis (Getis-Ord Gi*),2015.0,ols,journal,True,True,False
67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb:T4-c1,4,1,13,DHospital,hospital_distance,D_location,level,km,-0.094,,-24.942,0.0,***,,,high,Distance to nearest hospital (km); p-value printed as .000; *** significant at 1%,ln(price) of new housing unit,log,OLS,25323.0,0.724,t,"Global hedonic price model (HPM), semi-log OLS; 25,323 new-housing transactions, Shenzhen, July-December 2015; t-ratio and p-value printed in separate columns (no parentheses); only variables significant at 1% listed",semi_elasticity,-9.4,0.3768743484884933,100*b/1 (X per km->km),|b/t|,-0.15487712681873642,0.006209491092083089,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-24.942,25313.0,km,,2016.0,China,Asia,Upper middle income,2015.0,2015.0,condo_apartment,transaction,journal,False,False,unknown,social media check-in hot-spot analysis (Getis-Ord Gi*),2015.0,ols,journal,True,True,False
67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb:T4-c1,4,1,13,SPrimary,school_distance,D_location,level,km,0.08,,21.966,0.0,***,,,high,Distance to nearest primary school (km); printed as SPrimary (DSprimary in Table 1); p-value printed as .000; *** significant at 1%,ln(price) of new housing unit,log,OLS,25323.0,0.724,t,"Global hedonic price model (HPM), semi-log OLS; 25,323 new-housing transactions, Shenzhen, July-December 2015; t-ratio and p-value printed in separate columns (no parentheses); only variables significant at 1% listed",semi_elasticity,8.0,0.3641992169716835,100*b/1 (X per km->km),|b/t|,0.13676625678881987,0.0062262704538295485,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.966,25313.0,km,,2016.0,China,Asia,Upper middle income,2015.0,2015.0,condo_apartment,transaction,journal,False,False,unknown,social media check-in hot-spot analysis (Getis-Ord Gi*),2015.0,ols,journal,True,True,False
67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb:T4-c1,4,1,13,Floor,floor_level,A_structural,level,count,0.063,,20.077,0.0,***,,,high,Floor on which the unit is situated; p-value printed as .000; *** significant at 1%,ln(price) of new housing unit,log,OLS,25323.0,0.724,t,"Global hedonic price model (HPM), semi-log OLS; 25,323 new-housing transactions, Shenzhen, July-December 2015; t-ratio and p-value printed in separate columns (no parentheses); only variables significant at 1% listed",semi_elasticity,6.3,0.31379190118045525,100*b/1 (per unit count),|b/t|,0.12519770989125328,0.006235877366700866,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.077,25313.0,count,,2016.0,China,Asia,Upper middle income,2015.0,2015.0,condo_apartment,transaction,journal,False,False,unknown,social media check-in hot-spot analysis (Getis-Ord Gi*),2015.0,ols,journal,True,True,True
67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb:T4-c1,4,1,13,DBus,transit_distance,D_location,level,km,-0.049,,-14.273,0.0,***,,,high,Distance to nearest bus station (km); p-value printed as .000; *** significant at 1%,ln(price) of new housing unit,log,OLS,25323.0,0.724,t,"Global hedonic price model (HPM), semi-log OLS; 25,323 new-housing transactions, Shenzhen, July-December 2015; t-ratio and p-value printed in separate columns (no parentheses); only variables significant at 1% listed",semi_elasticity,-4.9,0.34330554193231977,100*b/1 (X per km->km),|b/t|,-0.0893517070991853,0.006260191066992594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.273,25313.0,km,,2016.0,China,Asia,Upper middle income,2015.0,2015.0,condo_apartment,transaction,journal,False,False,unknown,social media check-in hot-spot analysis (Getis-Ord Gi*),2015.0,ols,journal,True,True,False
67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb:T4-c1,4,1,13,DSub,transit_distance,D_location,level,km,-0.049,,-11.417,0.0,***,,,high,Distance to nearest metro station (km); p-value printed as .000; *** significant at 1%,ln(price) of new housing unit,log,OLS,25323.0,0.724,t,"Global hedonic price model (HPM), semi-log OLS; 25,323 new-housing transactions, Shenzhen, July-December 2015; t-ratio and p-value printed in separate columns (no parentheses); only variables significant at 1% listed",semi_elasticity,-4.9,0.4291845493562232,100*b/1 (X per km->km),|b/t|,-0.0715755795157146,0.006269210783543365,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.417,25313.0,km,,2016.0,China,Asia,Upper middle income,2015.0,2015.0,condo_apartment,transaction,journal,False,False,unknown,social media check-in hot-spot analysis (Getis-Ord Gi*),2015.0,ols,journal,True,True,False
67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb:T4-c1,4,1,13,Area,living_area,A_structural,level,m2,0.031,,6.907,0.0,***,,,high,Living area in m2 (coefficient as printed; interpreted by authors as semi-elasticity per unit); p-value printed as .000; *** significant at 1%,ln(price) of new housing unit,log,OLS,25323.0,0.724,t,"Global hedonic price model (HPM), semi-log OLS; 25,323 new-housing transactions, Shenzhen, July-December 2015; t-ratio and p-value printed in separate columns (no parentheses); only variables significant at 1% listed",semi_elasticity,3.1,0.4488200376429709,100*b/1 (X per m2->m2),|b/t|,0.0433719332524284,0.006279417004839786,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.907,25313.0,m2,,2016.0,China,Asia,Upper middle income,2015.0,2015.0,condo_apartment,transaction,journal,False,False,unknown,social media check-in hot-spot analysis (Getis-Ord Gi*),2015.0,ols,journal,True,True,True
67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb:T5-c1,5,median,14,DBus,transit_distance,D_location,level,km,-0.03028,,,0.004,**,,,medium,"GWR local coefficient summary: min -4.17797, lower quartile -0.35394, median -0.03028 (recorded), upper quartile 0.509983, max 23.5197; p-value .004; RPlot = plot (floor-area) ratio mapped to density; Fee = property management fee; DSnursery = distance to nursery school",ln(price) of new housing unit,log,GWR,25323.0,0.9399,none,GWR local coefficients: table reports min / lower quartile / median / upper quartile / max and a p-value per variable; beta recorded = median local coefficient (bandwidth 0.337),semi_elasticity,-3.028,1.0520604033015901,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.018087241405985936,0.006284303331636323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.878161739095483,25313.0,km,,2016.0,China,Asia,Upper middle income,2015.0,2015.0,condo_apartment,transaction,journal,False,False,unknown,social media check-in hot-spot analysis (Getis-Ord Gi*),2015.0,spatial,journal,True,True,False
67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb,67d132eca470e26b7a8c41462ca1252d056a93bb:T5-c1,5,median,14,DPark,green_space,E_environment,level,km,0.012992,,,0.855,,,,medium,"GWR local coefficient summary: min -2.27624, lower quartile -0.07367, median 0.012992 (recorded), upper quartile 0.328673, max 11.93626; p-value .855; RPlot = plot (floor-area) ratio mapped to density; Fee = property management fee; DSnursery = distance to nursery school",ln(price) of new housing unit,log,GWR,25323.0,0.9399,none,GWR local coefficients: table reports min / lower quartile / median / upper quartile / max and a p-value per variable; beta recorded = median local coefficient (bandwidth 0.337),semi_elasticity,1.2992,7.109453972280937,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),0.0011485969771561127,0.0062853273874633655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.18274258544544394,25313.0,km,,2016.0,China,Asia,Upper middle income,2015.0,2015.0,condo_apartment,transaction,journal,False,False,unknown,social media check-in hot-spot analysis (Getis-Ord Gi*),2015.0,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c1,2,1,8,Area,living_area,A_structural,level,m2,0.008,,315.66,,***,,,high,Building floor area in m2,log of real housing price,log,OLS,62140.0,0.853,t,OLS model; district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,0.8,0.0025343724260280046,100*b/1 (X per m2->m2),|b/t|,0.7848179019255282,0.002486276062616512,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),315.66,62130.0,m2,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,ols,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c1,2,1,8,Floor,floor_level,A_structural,level,count,-0.0004,,-1.05,,,,,high,Trading floor (floor on which the unit is located),log of real housing price,log,OLS,62140.0,0.853,t,OLS model; district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-0.04,0.0380952380952381,100*b/1 (per unit count),|b/t|,-0.0042124500969041865,0.0040118572351468445,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.05,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,ols,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c1,2,1,8,TStory,storeys,A_structural,level,count,-0.0003,,-1.01,,,,,high,Total number of storeys of the building,log of real housing price,log,OLS,62140.0,0.853,t,OLS model; district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-0.03,0.0297029702970297,100*b/1 (per unit count),|b/t|,-0.004051978494422616,0.004011859895467937,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.01,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,ols,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c1,2,1,8,Bathroom,bathrooms,A_structural,level,count,0.059,,24.31,,***,,,high,Number of bathrooms,log of real housing price,log,OLS,62140.0,0.853,t,OLS model; district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,5.8999999999999995,0.24269847799259564,100*b/1 (per unit count),|b/t|,0.0970685527674644,0.003992947460611452,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.31,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,ols,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c1,2,1,8,Age,age,A_structural,level,years,-0.011,,-118.36,,***,,,high,Dwelling age in years,log of real housing price,log,OLS,62140.0,0.853,t,OLS model; district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-1.0999999999999999,0.00929368029739777,100*b/1 (per year),|b/t|,-0.4289445129167328,0.0036240665167010214,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-118.36,62130.0,years,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,ols,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c1,2,1,8,Dist. MRT,transit_distance,D_location,level,100 m,-0.011,,-40.04,,***,,,high,"Distance to nearest MRT station, unit = 100 m (Table 1)",log of real housing price,log,OLS,62140.0,0.853,t,OLS model; district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-10.999999999999998,0.2747252747252747,100*b/0.1 (X per 100m->km),|b/t|,-0.15860292813775728,0.00396111209135258,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-40.04,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,ols,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c1,2,1,8,Dist. CC,cbd_distance,D_location,level,100 m,-0.004,,-32.22,,***,,,high,"Distance to city center, unit = 100 m (Table 1)",log of real housing price,log,OLS,62140.0,0.853,t,OLS model; district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-4.0,0.12414649286157667,100*b/0.1 (X per 100m->km),|b/t|,-0.1281966071692666,0.003978789794204425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-32.22,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,ols,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c1,2,1,8,THA,liquidity,G_market,binary,binary,-0.102,,-34.74,,***,,,high,Dummy = 1 if located in a housing-transaction hotspot area (Getis-Ord Gi*),log of real housing price,log,OLS,62140.0,0.853,t,OLS model; district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),pct_premium,-9.697434067988109,0.2651382103345579,100*(exp(b - se^2/2) - 1),|b/t|,-0.1380389107308333,0.003973486204111493,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-34.74,62130.0,binary,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,ols,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c2,2,2,8,Area,living_area,A_structural,level,m2,0.008,,316.6,,***,,,high,Building floor area in m2; z-statistic recorded in t field,log of real housing price,log,spatial_lag,62140.0,0.859,t,Spatial lag model (rho=0.196); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,0.8,0.002526847757422615,100*b/1 (X per m2->m2),|b/t|,0.7857130259297691,0.0024817214969354677,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),316.6,62130.0,m2,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c2,2,2,8,Floor,floor_level,A_structural,level,count,-0.0001,,-0.37,,,,,high,Trading floor (floor on which the unit is located); z-statistic recorded in t field,log of real housing price,log,spatial_lag,62140.0,0.859,t,Spatial lag model (rho=0.196); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-0.01,0.02702702702702703,100*b/1 (per unit count),|b/t|,-0.0014843987118146568,0.004011888410309883,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.37,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c2,2,2,8,TStory,storeys,A_structural,level,count,-0.0004,,-1.33,,,,,high,Total number of storeys of the building; z-statistic recorded in t field,log of real housing price,log,spatial_lag,62140.0,0.859,t,Spatial lag model (rho=0.196); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-0.04,0.03007518796992481,100*b/1 (per unit count),|b/t|,-0.005335741508022053,0.004011835720317333,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.33,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c2,2,2,8,Bathroom,bathrooms,A_structural,level,count,0.06,,25.31,,***,,,high,Number of bathrooms; z-statistic recorded in t field,log of real housing price,log,spatial_lag,62140.0,0.859,t,Spatial lag model (rho=0.196); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,6.0,0.2370604504148558,100*b/1 (per unit count),|b/t|,0.10102154789875127,0.003991368941080651,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.31,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c2,2,2,8,Age,age,A_structural,level,years,-0.011,,-121.44,,***,,,high,Dwelling age in years; z-statistic recorded in t field,log of real housing price,log,spatial_lag,62140.0,0.859,t,Spatial lag model (rho=0.196); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-1.0999999999999999,0.009057971014492754,100*b/1 (per year),|b/t|,-0.4379874255214203,0.0036066158228048447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-121.44,62130.0,years,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c2,2,2,8,Dist. MRT,transit_distance,D_location,level,100 m,-0.011,,-39.9,,***,,,high,"Distance to nearest MRT station, unit = 100 m (Table 1); z-statistic recorded in t field",log of real housing price,log,spatial_lag,62140.0,0.859,t,Spatial lag model (rho=0.196); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-10.999999999999998,0.2756892230576441,100*b/0.1 (X per 100m->km),|b/t|,-0.15806225098165366,0.003961459924352223,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-39.9,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c2,2,2,8,Dist. CC,cbd_distance,D_location,level,100 m,-0.003,,-27.49,,***,,,high,"Distance to city center, unit = 100 m (Table 1); z-statistic recorded in t field",log of real housing price,log,spatial_lag,62140.0,0.859,t,Spatial lag model (rho=0.196); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-2.9999999999999996,0.10913059294288834,100*b/0.1 (X per 100m->km),|b/t|,-0.10962226968601657,0.0039877144301934,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-27.49,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c2,2,2,8,THA,liquidity,G_market,binary,binary,-0.099,,-34.56,,***,,,high,Dummy = 1 if located in a housing-transaction hotspot area (Getis-Ord Gi*); z-statistic recorded in t field,log of real housing price,log,spatial_lag,62140.0,0.859,t,Spatial lag model (rho=0.196); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),pct_premium,-9.426100815764594,0.25945754656924563,100*(exp(b - se^2/2) - 1),|b/t|,-0.13733720794901302,0.003973877544820979,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-34.56,62130.0,binary,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c3,2,3,8,Area,living_area,A_structural,level,m2,0.007,,179.92,,***,,,high,Building floor area in m2; z-statistic recorded in t field,log of real housing price,log,spatial_error,62140.0,0.855,t,Spatial error model (lambda=0.056); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,0.7000000000000001,0.0038906180524677643,100*b/1 (X per m2->m2),|b/t|,0.5852760679041914,0.00325297947923628,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),179.92,62130.0,m2,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c3,2,3,8,Floor,floor_level,A_structural,level,count,-0.0008,,-2.33,,**,,,high,Trading floor (floor on which the unit is located); z-statistic recorded in t field,log of real housing price,log,spatial_error,62140.0,0.855,t,Spatial error model (lambda=0.056); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-0.08,0.034334763948497854,100*b/1 (per unit count),|b/t|,-0.009347301921344,0.004011717562808583,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.33,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c3,2,3,8,TStory,storeys,A_structural,level,count,-0.0009,,-2.69,,***,,,high,Total number of storeys of the building; z-statistic recorded in t field,log of real housing price,log,spatial_error,62140.0,0.855,t,Spatial error model (lambda=0.056); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-0.09,0.03345724907063197,100*b/1 (per unit count),|b/t|,-0.010791363312472348,0.004011659223967416,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.69,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c3,2,3,8,Bathroom,bathrooms,A_structural,level,count,0.061,,25.42,,***,,,high,Number of bathrooms; z-statistic recorded in t field,log of real housing price,log,spatial_error,62140.0,0.855,t,Spatial error model (lambda=0.056); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,6.1,0.2399685287175452,100*b/1 (per unit count),|b/t|,0.10145608886418755,0.0039911915367501,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.42,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c3,2,3,8,Age,age,A_structural,level,years,-0.011,,-114.1,,***,,,high,Dwelling age in years; z-statistic recorded in t field,log of real housing price,log,spatial_error,62140.0,0.855,t,Spatial error model (lambda=0.056); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-1.0999999999999999,0.009640666082383873,100*b/1 (per year),|b/t|,-0.41622157714188324,0.0036478665831891606,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-114.1,62130.0,years,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c3,2,3,8,Dist. MRT,transit_distance,D_location,level,100 m,-0.011,,-37.84,,***,,,high,"Distance to nearest MRT station, unit = 100 m (Table 1); z-statistic recorded in t field",log of real housing price,log,spatial_error,62140.0,0.855,t,Spatial error model (lambda=0.056); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-10.999999999999998,0.29069767441860456,100*b/0.1 (X per 100m->km),|b/t|,-0.15009036366713763,0.003966447242789049,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-37.84,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c3,2,3,8,Dist. CC,cbd_distance,D_location,level,100 m,-0.003,,-31.16,,***,,,high,"Distance to city center, unit = 100 m (Table 1); z-statistic recorded in t field",log of real housing price,log,spatial_error,62140.0,0.855,t,Spatial error model (lambda=0.056); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),semi_elasticity,-2.9999999999999996,0.0962772785622593,100*b/0.1 (X per 100m->km),|b/t|,-0.12404507193499618,0.0039809073149870405,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.16,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T2-c3,2,3,8,THA,liquidity,G_market,binary,binary,-0.101,,-34.42,,***,,,high,Dummy = 1 if located in a housing-transaction hotspot area (Getis-Ord Gi*); z-statistic recorded in t field,log of real housing price,log,spatial_error,62140.0,0.855,t,Spatial error model (lambda=0.056); district and trading year x quarter dummies included. Statistic printed = t value (OLS) or z-statistic (spatial models),pct_premium,-9.607085869753773,0.26524473074222044,100*(exp(b - se^2/2) - 1),|b/t|,-0.136791296075163,0.003974180594862376,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-34.42,62130.0,binary,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,spatial,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c1,3,1,9,Area,living_area,A_structural,level,m2,0.008,,131.06,,***,,,high,Building floor area in m2,log of real housing price,log,quantile,62140.0,0.577,t,Spatial quantile regression at quantile 0.1 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,0.8,0.00610407446970853,100*b/1 (X per m2->m2),|b/t|,0.46538797713656815,0.0035509535871857782,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),131.06,62130.0,m2,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c1,3,1,9,Floor,floor_level,A_structural,level,count,-0.002,,-2.15,,**,,,high,Trading floor (floor on which the unit is located),log of real housing price,log,quantile,62140.0,0.577,t,Spatial quantile regression at quantile 0.1 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-0.2,0.09302325581395349,100*b/1 (per unit count),|b/t|,-0.008625248729903522,0.004011743595303963,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.15,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c1,3,1,9,TStory,storeys,A_structural,level,count,-0.004,,-5.4,,***,,,high,Total number of storeys of the building,log of real housing price,log,quantile,62140.0,0.577,t,Spatial quantile regression at quantile 0.1 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-0.4,0.07407407407407407,100*b/1 (per unit count),|b/t|,-0.021659139146064214,0.004010951693715595,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.4,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c1,3,1,9,Bathroom,bathrooms,A_structural,level,count,0.069,,12.16,,***,,,high,Number of bathrooms,log of real housing price,log,quantile,62140.0,0.577,t,Spatial quantile regression at quantile 0.1 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,6.9,0.5674342105263158,100*b/1 (per unit count),|b/t|,0.04872666802968347,0.004007127305072654,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.16,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c1,3,1,9,Age,age,A_structural,level,years,-0.012,,-55.95,,***,,,high,Dwelling age in years,log of real housing price,log,quantile,62140.0,0.577,t,Spatial quantile regression at quantile 0.1 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-1.2,0.021447721179624665,100*b/1 (per year),|b/t|,-0.21901568425555434,0.003914489441564867,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-55.95,62130.0,years,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c1,3,1,9,Dist. MRT,transit_distance,D_location,level,100 m,-0.012,,-17.8,,***,,,high,"Distance to nearest MRT station, unit = 100 m (Table 1)",log of real housing price,log,quantile,62140.0,0.577,t,Spatial quantile regression at quantile 0.1 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-11.999999999999998,0.6741573033707865,100*b/0.1 (X per 100m->km),|b/t|,-0.07123029926587827,0.004001702205948218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.8,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c1,3,1,9,Dist. CC,cbd_distance,D_location,level,100 m,-0.002,,-9.48,,***,,,high,"Distance to city center, unit = 100 m (Table 1)",log of real housing price,log,quantile,62140.0,0.577,t,Spatial quantile regression at quantile 0.1 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-2.0,0.21097046413502107,100*b/0.1 (X per 100m->km),|b/t|,-0.03800526685198405,0.004008994393669203,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.48,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c1,3,1,9,THA,liquidity,G_market,binary,binary,-0.122,,-17.62,,***,,,high,Dummy = 1 if located in a housing-transaction hotspot area (Getis-Ord Gi*),log of real housing price,log,quantile,62140.0,0.577,t,Spatial quantile regression at quantile 0.1 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,pct_premium,-11.487284872939297,0.6128723096329199,100*(exp(b - se^2/2) - 1),|b/t|,-0.07051359255404434,0.004001906501364604,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.62,62130.0,binary,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c2,3,2,9,Area,living_area,A_structural,level,m2,0.008,,230.96,,***,,,high,Building floor area in m2,log of real housing price,log,quantile,62140.0,0.606,t,Spatial quantile regression at quantile 0.25 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,0.8,0.0034638032559750607,100*b/1 (X per m2->m2),|b/t|,0.6796689749703956,0.0029427995106096104,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),230.96,62130.0,m2,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c2,3,2,9,Floor,floor_level,A_structural,level,count,0.001,,1.51,,,,,high,Trading floor (floor on which the unit is located),log of real housing price,log,quantile,62140.0,0.606,t,Spatial quantile regression at quantile 0.25 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,0.1,0.06622516556291391,100*b/1 (per unit count),|b/t|,0.006057847016732288,0.004011819216378999,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.51,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c2,3,2,9,TStory,storeys,A_structural,level,count,-0.001,,-3.01,,***,,,high,Total number of storeys of the building,log of real housing price,log,quantile,62140.0,0.606,t,Spatial quantile regression at quantile 0.25 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-0.1,0.03322259136212625,100*b/1 (per unit count),|b/t|,-0.012074917039594813,0.004011600345380337,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.01,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c2,3,2,9,Bathroom,bathrooms,A_structural,level,count,0.061,,17.98,,***,,,high,Number of bathrooms,log of real housing price,log,quantile,62140.0,0.606,t,Spatial quantile regression at quantile 0.25 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,6.1,0.339265850945495,100*b/1 (per unit count),|b/t|,0.07194689566865423,0.004001495865887331,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.98,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c2,3,2,9,Age,age,A_structural,level,years,-0.012,,-88.2,,***,,,high,Dwelling age in years,log of real housing price,log,quantile,62140.0,0.606,t,Spatial quantile regression at quantile 0.25 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-1.2,0.013605442176870748,100*b/1 (per year),|b/t|,-0.3335809911284945,0.0037820974050849724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-88.2,62130.0,years,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c2,3,2,9,Dist. MRT,transit_distance,D_location,level,100 m,-0.013,,-33.05,,***,,,high,"Distance to nearest MRT station, unit = 100 m (Table 1)",log of real housing price,log,quantile,62140.0,0.606,t,Spatial quantile regression at quantile 0.25 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-13.0,0.39334341906202724,100*b/0.1 (X per 100m->km),|b/t|,-0.13144265101108937,0.003977084750713749,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-33.05,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c2,3,2,9,Dist. CC,cbd_distance,D_location,level,100 m,-0.003,,-16.04,,***,,,high,"Distance to city center, unit = 100 m (Table 1)",log of real housing price,log,quantile,62140.0,0.606,t,Spatial quantile regression at quantile 0.25 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-2.9999999999999996,0.18703241895261846,100*b/0.1 (X per 100m->km),|b/t|,-0.06421793447551657,0.004003611875032205,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.04,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c2,3,2,9,THA,liquidity,G_market,binary,binary,-0.124,,-30.11,,***,,,high,Dummy = 1 if located in a housing-transaction hotspot area (Getis-Ord Gi*),log of real housing price,log,quantile,62140.0,0.606,t,Spatial quantile regression at quantile 0.25 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,pct_premium,-11.662765007773979,0.36379641404669916,100*(exp(b - se^2/2) - 1),|b/t|,-0.11992626924232185,0.003982938201339151,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.11,62130.0,binary,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c3,3,3,9,Area,living_area,A_structural,level,m2,0.008,,305.09,,***,,,high,Building floor area in m2,log of real housing price,log,quantile,62140.0,0.641,t,Spatial quantile regression at quantile 0.5 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,0.8,0.002622177062506146,100*b/1 (X per m2->m2),|b/t|,0.7744051848532305,0.002538284391009967,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),305.09,62130.0,m2,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c3,3,3,9,Floor,floor_level,A_structural,level,count,0.001,,3.91,,***,,,high,Trading floor (floor on which the unit is located),log of real housing price,log,quantile,62140.0,0.641,t,Spatial quantile regression at quantile 0.5 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,0.1,0.025575447570332477,100*b/1 (per unit count),|b/t|,0.015684571362824928,0.0040113993255306716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.91,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c3,3,3,9,TStory,storeys,A_structural,level,count,0.001,,3.31,,***,,,high,Total number of storeys of the building,log of real housing price,log,quantile,62140.0,0.641,t,Spatial quantile regression at quantile 0.5 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,0.1,0.030211480362537763,100*b/1 (per unit count),|b/t|,0.01327819457122899,0.004011539145386402,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.31,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c3,3,3,9,Bathroom,bathrooms,A_structural,level,count,0.055,,21.54,,***,,,high,Number of bathrooms,log of real housing price,log,quantile,62140.0,0.641,t,Spatial quantile regression at quantile 0.5 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,5.5,0.255338904363974,100*b/1 (per unit count),|b/t|,0.08609530020573562,0.003996996295530903,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.54,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c3,3,3,9,Age,age,A_structural,level,years,-0.011,,-105.21,,***,,,high,Dwelling age in years,log of real housing price,log,quantile,62140.0,0.641,t,Spatial quantile regression at quantile 0.5 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-1.0999999999999999,0.010455279916357762,100*b/1 (per year),|b/t|,-0.38886962304523837,0.003696127963551358,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-105.21,62130.0,years,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c3,3,3,9,Dist. MRT,transit_distance,D_location,level,100 m,-0.011,,-38.23,,***,,,high,"Distance to nearest MRT station, unit = 100 m (Table 1)",log of real housing price,log,quantile,62140.0,0.641,t,Spatial quantile regression at quantile 0.5 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-10.999999999999998,0.28773214752811926,100*b/0.1 (X per 100m->km),|b/t|,-0.15160190236468427,0.003965521903339897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-38.23,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c3,3,3,9,Dist. CC,cbd_distance,D_location,level,100 m,-0.003,,-26.2,,***,,,high,"Distance to city center, unit = 100 m (Table 1)",log of real housing price,log,quantile,62140.0,0.641,t,Spatial quantile regression at quantile 0.5 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-2.9999999999999996,0.11450381679389314,100*b/0.1 (X per 100m->km),|b/t|,-0.1045356999030926,0.003989912210041702,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-26.2,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c3,3,3,9,THA,liquidity,G_market,binary,binary,-0.097,,-30.8,,***,,,high,Dummy = 1 if located in a housing-transaction hotspot area (Getis-Ord Gi*),log of real housing price,log,quantile,62140.0,0.641,t,Spatial quantile regression at quantile 0.5 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,pct_premium,-9.244849461162952,0.28582120972379044,100*(exp(b - se^2/2) - 1),|b/t|,-0.12263362214237468,0.003981611108518658,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.8,62130.0,binary,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c4,3,4,9,Area,living_area,A_structural,level,m2,0.008,,300.55,,***,,,high,Building floor area in m2,log of real housing price,log,quantile,62140.0,0.671,t,Spatial quantile regression at quantile 0.75 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,0.8,0.0026617867243387125,100*b/1 (X per m2->m2),|b/t|,0.769729876557214,0.002561070958433584,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),300.55,62130.0,m2,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c4,3,4,9,Floor,floor_level,A_structural,level,count,0.002,,5.064,,***,,,high,Trading floor (floor on which the unit is located),log of real housing price,log,quantile,62140.0,0.671,t,Spatial quantile regression at quantile 0.75 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,0.2,0.03949447077409163,100*b/1 (per unit count),|b/t|,0.02031203383913802,0.004011065134110984,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.064,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c4,3,4,9,TStory,storeys,A_structural,level,count,0.003,,7.32,,***,,,high,Total number of storeys of the building,log of real housing price,log,quantile,62140.0,0.671,t,Spatial quantile regression at quantile 0.75 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,0.3,0.040983606557377046,100*b/1 (per unit count),|b/t|,0.029354400276794333,0.004010163972239663,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.32,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c4,3,4,9,Bathroom,bathrooms,A_structural,level,count,0.054,,20.79,,***,,,high,Number of bathrooms,log of real housing price,log,quantile,62140.0,0.671,t,Spatial quantile regression at quantile 0.75 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,5.4,0.2597402597402597,100*b/1 (per unit count),|b/t|,0.08311863443541102,0.0039980103143535855,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.79,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c4,3,4,9,Age,age,A_structural,level,years,-0.01,,-100.58,,***,,,high,Dwelling age in years,log of real housing price,log,quantile,62140.0,0.671,t,Spatial quantile regression at quantile 0.75 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-1.0,0.00994233446013124,100*b/1 (per year),|b/t|,-0.3741999428127673,0.0037204209864065145,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-100.58,62130.0,years,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c4,3,4,9,Dist. MRT,transit_distance,D_location,level,100 m,-0.01,,-32.26,,***,,,high,"Distance to nearest MRT station, unit = 100 m (Table 1)",log of real housing price,log,quantile,62140.0,0.671,t,Spatial quantile regression at quantile 0.75 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-10.0,0.3099814011159331,100*b/0.1 (X per 100m->km),|b/t|,-0.12835313841242058,0.003978708568270942,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-32.26,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c4,3,4,9,Dist. CC,cbd_distance,D_location,level,100 m,-0.004,,-29.4,,***,,,high,"Distance to city center, unit = 100 m (Table 1)",log of real housing price,log,quantile,62140.0,0.671,t,Spatial quantile regression at quantile 0.75 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-4.0,0.13605442176870747,100*b/0.1 (X per 100m->km),|b/t|,-0.11713764713633111,0.003984273712120106,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-29.4,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c4,3,4,9,THA,liquidity,G_market,binary,binary,-0.061,,-19.22,,***,,,high,Dummy = 1 if located in a housing-transaction hotspot area (Getis-Ord Gi*),log of real housing price,log,quantile,62140.0,0.671,t,Spatial quantile regression at quantile 0.75 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,pct_premium,-5.918149860359867,0.29859634561049214,100*(exp(b - se^2/2) - 1),|b/t|,-0.07688036386024712,0.004000018931334398,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-19.22,62130.0,binary,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c5,3,5,9,Area,living_area,A_structural,level,m2,0.008,,265.16,,***,,,high,Building floor area in m2,log of real housing price,log,quantile,62140.0,0.693,t,Spatial quantile regression at quantile 0.9 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,0.8,0.003017046311660884,100*b/1 (X per m2->m2),|b/t|,0.7286160106961107,0.00274783530960971,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),265.16,62130.0,m2,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c5,3,5,9,Floor,floor_level,A_structural,level,count,0.002,,3.27,,***,,,high,Trading floor (floor on which the unit is located),log of real housing price,log,quantile,62140.0,0.693,t,Spatial quantile regression at quantile 0.9 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,0.2,0.06116207951070336,100*b/1 (per unit count),|b/t|,0.013117760785789887,0.004011547640914338,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.27,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c5,3,5,9,TStory,storeys,A_structural,level,count,0.003,,6.37,,***,,,high,Total number of storeys of the building,log of real housing price,log,quantile,62140.0,0.693,t,Spatial quantile regression at quantile 0.9 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,0.3,0.04709576138147566,100*b/1 (per unit count),|b/t|,0.025547416223605634,0.004010583394600571,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.37,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c5,3,5,9,Bathroom,bathrooms,A_structural,level,count,0.049,,16.63,,***,,,high,Number of bathrooms,log of real housing price,log,quantile,62140.0,0.693,t,Spatial quantile regression at quantile 0.9 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,4.9,0.29464822609741437,100*b/1 (per unit count),|b/t|,0.06656978250903975,0.0040029935363222946,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.63,62130.0,count,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c5,3,5,9,Age,age,A_structural,level,years,-0.01,,-86.66,,***,,,high,Dwelling age in years,log of real housing price,log,quantile,62140.0,0.693,t,Spatial quantile regression at quantile 0.9 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-1.0,0.01153934918070621,100*b/1 (per year),|b/t|,-0.3283896357140622,0.0037894026738294743,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-86.66,62130.0,years,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c5,3,5,9,Dist. MRT,transit_distance,D_location,level,100 m,-0.009,,-25.01,,***,,,high,"Distance to nearest MRT station, unit = 100 m (Table 1)",log of real housing price,log,quantile,62140.0,0.693,t,Spatial quantile regression at quantile 0.9 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-8.999999999999998,0.35985605757696915,100*b/0.1 (X per 100m->km),|b/t|,-0.09983614297336484,0.003991848979342856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-25.01,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c5,3,5,9,Dist. CC,cbd_distance,D_location,level,100 m,-0.004,,-26.04,,***,,,high,"Distance to city center, unit = 100 m (Table 1)",log of real housing price,log,quantile,62140.0,0.693,t,Spatial quantile regression at quantile 0.9 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,semi_elasticity,-4.0,0.15360983102918585,100*b/0.1 (X per 100m->km),|b/t|,-0.10390422696447446,0.003990177686807775,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-26.04,62130.0,100m,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1,69288e963b8055b19e0fd077000b14eb34270ae1:T3-c5,3,5,9,THA,liquidity,G_market,binary,binary,-0.038,,-10.64,,***,,,high,Dummy = 1 if located in a housing-transaction hotspot area (Getis-Ord Gi*),log of real housing price,log,quantile,62140.0,0.693,t,Spatial quantile regression at quantile 0.9 (with spatial lag term); district and trading year x quarter dummies included; pseudo R-square reported,pct_premium,-3.7293198840120723,0.3438260503182855,100*(exp(b - se^2/2) - 1),|b/t|,-0.042647702341546294,0.004008242701273148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.64,62130.0,binary,,2024.0,Taiwan,Asia,High income,2012.0,2021.0,unknown,transaction,journal,True,True,unknown,,2016.5,quantile,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T6-c1,6,1,16,Distance to the Corresponding Public Primary School,school_distance,D_location,log,m,-0.027,0.01,-2.657,0.008,,,,medium,"straight-line distance from neighbourhood centre to corresponding public primary school, metres, entered in logs; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,344.0,0.849,se,"citywide, 344 neighbourhoods in 7 districts; residual df 334 (Table 7); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS",elasticity,-0.027,0.01,b (log-log),reported,-0.14387203416943053,0.054148300402495485,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.657,334.0,m,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T6-c1,6,1,16,Distance to the District's CBD,cbd_distance,D_location,log,m,-0.007,0.011,-0.663,0.508,,,,medium,"straight-line distance to district CBD (Wanda Plaza), metres, entered in logs; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,344.0,0.849,se,"citywide, 344 neighbourhoods in 7 districts; residual df 334 (Table 7); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS",elasticity,-0.007,0.011,b (log-log),reported,-0.03625389736018949,0.05468159481174884,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.663,334.0,m,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T6-c1,6,1,16,Property Management Fee,public_services,F_neighbourhood,log,currency,0.029,0.019,1.536,0.125,,,,medium,RMB per m2 per month; continuous variables stated to enter in logarithmic form (estate upkeep fee); column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD),"ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,344.0,0.849,se,"citywide, 344 neighbourhoods in 7 districts; residual df 334 (Table 7); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS",elasticity,0.029,0.019,b (log-log),reported,0.08375090299895833,0.054525327473280163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.536,334.0,currency,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T6-c1,6,1,16,Green Coverage Ratio,green_space,E_environment,log,share,0.002,0.032,0.072,0.942,,,,medium,% of open space covered by greenery in the estate; continuous -> log form per text; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD),"ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,344.0,0.849,se,"citywide, 344 neighbourhoods in 7 districts; residual df 334 (Table 7); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS",elasticity,0.002,0.032,b (log-log),reported,0.0039396341438554215,0.05471714088688085,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.072,334.0,share,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T6-c1,6,1,16,Elevator,accessibility,B_interior,dummy,binary,0.003,0.022,0.123,0.902,,,,medium,1 if the estate has elevators; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD),"ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,344.0,0.849,se,"citywide, 344 neighbourhoods in 7 districts; residual df 334 (Table 7); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS",pct_premium,0.27618067808961033,2.2066099099074292,100*(exp(b - se^2/2) - 1),reported,0.006730108135391152,0.054716326303993104,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.123,334.0,binary,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T6-c1,6,1,16,Residential Area,living_area,A_structural,log,m2,-0.003,0.024,-0.106,0.916,,,,medium,"floor area within a house, m2, log form per text; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,344.0,0.849,se,"citywide, 344 neighbourhoods in 7 districts; residual df 334 (Table 7); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS",elasticity,-0.003,0.024,b (log-log),reported,-0.005799964388080212,0.05471664517056805,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.106,334.0,m2,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,True
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T6-c1,6,1,16,Floor Area Ratio,density,F_neighbourhood,log,index,-0.016,0.02,-0.775,0.439,,,,medium,"building gross floor area / land area of the estate, log form per text; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,344.0,0.849,se,"citywide, 344 neighbourhoods in 7 districts; residual df 334 (Table 7); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS",elasticity,-0.016,0.02,b (log-log),reported,-0.0423680356235517,0.054668433062647355,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.775,334.0,index,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T6-c1,6,1,16,Building Age,age,A_structural,log,years,-0.034,0.023,-1.466,0.144,,,,medium,"years since the building was built, log form (text); column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,344.0,0.849,se,"citywide, 344 neighbourhoods in 7 districts; residual df 334 (Table 7); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS",elasticity,-0.034,0.023,b (log-log),reported,-0.07995911114962143,0.05454236776918243,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.466,334.0,years,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T8-c1,8,1,17,Distance to the Corresponding Public Primary School,school_distance,D_location,log,m,-0.012,0.01,-1.146,0.253,,,,medium,"straight-line distance from neighbourhood centre to corresponding public primary school, metres, entered in logs; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,242.0,0.726,se,urban districts; residual df 232 (Table 9); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,-0.012,0.01,b (log-log),reported,-0.0750265289415271,0.06546817534164669,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.146,232.0,m,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T8-c1,8,1,17,Distance to the District's CBD,cbd_distance,D_location,log,m,-0.024,0.012,-1.948,0.053,,,,medium,"straight-line distance to district CBD (Wanda Plaza), metres, entered in logs; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,242.0,0.726,se,urban districts; residual df 232 (Table 9); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,-0.024,0.012,b (log-log),reported,-0.1268591885967761,0.06512278675399184,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.948,232.0,m,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T8-c1,8,1,17,Property Management Fee,public_services,F_neighbourhood,log,currency,0.016,0.02,0.823,0.411,,,,medium,RMB per m2 per month; continuous variables stated to enter in logarithmic form (estate upkeep fee); column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD),"ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,242.0,0.726,se,urban districts; residual df 232 (Table 9); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,0.016,0.02,b (log-log),reported,0.05395389474397995,0.06555758778126361,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.823,232.0,currency,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T8-c1,8,1,17,Green Coverage Ratio,green_space,E_environment,log,share,0.032,0.031,1.005,0.316,,,,medium,% of open space covered by greenery in the estate; continuous -> log form per text; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD),"ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,242.0,0.726,se,urban districts; residual df 232 (Table 9); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,0.032,0.031,b (log-log),reported,0.06583832274267414,0.06551076889818322,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.005,232.0,share,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T8-c1,8,1,17,Elevator,accessibility,B_interior,dummy,binary,-0.01,0.024,-0.429,0.668,,,,medium,1 if the estate has elevators; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD),"ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,242.0,0.726,se,urban districts; residual df 232 (Table 9); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,pct_premium,-1.023525954754645,2.3761196009980035,100*(exp(b - se^2/2) - 1),reported,-0.028154065031397404,0.06562719121537856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.429,232.0,binary,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T8-c1,8,1,17,Residential Area,living_area,A_structural,log,m2,-0.001,0.025,-0.041,0.968,,,,medium,"floor area within a house, m2, log form per text; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,242.0,0.726,se,urban districts; residual df 232 (Table 9); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,-0.001,0.025,b (log-log),reported,-0.0026917721217692685,0.06565297857973826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.041,232.0,m2,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T8-c1,8,1,17,Floor Area Ratio,density,F_neighbourhood,log,index,-0.054,0.023,-2.381,0.018,,,,medium,"building gross floor area / land area of the estate, log form per text; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,242.0,0.726,se,urban districts; residual df 232 (Table 9); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,-0.054,0.023,b (log-log),reported,-0.15444468913208453,0.064865472126033,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.381,232.0,index,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T8-c1,8,1,17,Building Age,age,A_structural,log,years,-0.071,0.023,-3.122,0.002,,,,medium,"years since the building was built, log form (text); column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,242.0,0.726,se,urban districts; residual df 232 (Table 9); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,-0.071,0.023,b (log-log),reported,-0.20079479750141924,0.06431607863594466,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.122,232.0,years,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T10-c1,10,1,18,Distance to the Corresponding Public Primary School,school_distance,D_location,log,m,-0.042,0.021,-2.001,0.048,,,,medium,"straight-line distance from neighbourhood centre to corresponding public primary school, metres, entered in logs; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,102.0,0.435,se,suburban districts; residual df 92 (Table 11); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,-0.042,0.021,b (log-log),reported,-0.20422195166123877,0.10205994585769054,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.001,92.0,m,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T10-c1,10,1,18,Distance to the District's CBD,cbd_distance,D_location,log,m,0.042,0.023,1.806,0.074,,,,medium,"straight-line distance to district CBD (Wanda Plaza), metres, entered in logs; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,102.0,0.435,se,suburban districts; residual df 92 (Table 11); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,0.042,0.023,b (log-log),reported,0.1850370637005404,0.10245684590284629,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.806,92.0,m,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T10-c1,10,1,18,Property Management Fee,public_services,F_neighbourhood,log,currency,0.016,0.039,0.407,0.685,,,,medium,RMB per m2 per month; continuous variables stated to enter in logarithmic form (estate upkeep fee); column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD),"ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,102.0,0.435,se,suburban districts; residual df 92 (Table 11); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,0.016,0.039,b (log-log),reported,0.04239453405461633,0.10416347433566665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.407,92.0,currency,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T10-c1,10,1,18,Green Coverage Ratio,green_space,E_environment,log,share,0.069,0.095,0.725,0.47,,,,medium,% of open space covered by greenery in the estate; continuous -> log form per text; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD),"ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,102.0,0.435,se,suburban districts; residual df 92 (Table 11); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,0.069,0.095,b (log-log),reported,0.07537147126758946,0.10396065002426132,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.725,92.0,share,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T10-c1,10,1,18,Elevator,accessibility,B_interior,dummy,binary,0.075,0.049,1.511,0.134,,,,medium,1 if the estate has elevators; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD),"ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,102.0,0.435,se,suburban districts; residual df 92 (Table 11); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,pct_premium,7.659092737422291,5.281632339334695,100*(exp(b - se^2/2) - 1),reported,0.1556135782496125,0.10298714642595136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.511,92.0,binary,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T10-c1,10,1,18,Residential Area,living_area,A_structural,log,m2,0.049,0.057,0.868,0.387,,,,medium,"floor area within a house, m2, log form per text; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,102.0,0.435,se,suburban districts; residual df 92 (Table 11); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,0.049,0.057,b (log-log),reported,0.09012696568654247,0.10383290977712266,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.868,92.0,m2,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T10-c1,10,1,18,Floor Area Ratio,density,F_neighbourhood,log,index,-0.043,0.043,-0.995,0.322,,,,medium,"building gross floor area / land area of the estate, log form per text; column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,102.0,0.435,se,suburban districts; residual df 92 (Table 11); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,-0.043,0.043,b (log-log),reported,-0.1031822273370634,0.10370073099202352,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.995,92.0,index,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de,6a582c18a0b55c4939a0e4812ae293fd34b678de:T10-c1,10,1,18,Building Age,age,A_structural,log,years,0.049,0.062,0.786,0.434,,,,medium,"years since the building was built, log form (text); column headed 'Standard Deviation' is the coefficient standard error (Excel output; t = coef/SD)","ln(housing price, RMB per m2, representative house of the neighbourhood)",log,IV,102.0,0.435,se,suburban districts; residual df 92 (Table 11); N derived from ANOVA df (not printed directly); R2 computed from ANOVA SS regression / SS total; author states 2SLS but no instrument or first stage is reported and the Excel output looks like OLS,elasticity,0.049,0.062,b (log-log),reported,0.08167240135809607,0.10390890758027489,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.786,92.0,years,,2018.0,China,Asia,Upper middle income,,,condo_apartment,listing,journal,False,False,OLS,,2015.0,iv,journal,True,True,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,Building age,age,A_structural,level,years,-0.0016,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),semi_elasticity,-0.16,0.01,100*b/1 (per year),reported,,,,-16.0,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,Building age,age,A_structural,level,years,-0.0027,0.0002,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,semi_elasticity,-0.27,0.02,100*b/1 (per year),reported,,,,-13.5,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,Building age,age,A_structural,level,years,-0.0026,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,semi_elasticity,-0.26,0.01,100*b/1 (per year),reported,,,,-25.999999999999996,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,Building age,age,A_structural,level,years,-0.0028,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,semi_elasticity,-0.27999999999999997,0.01,100*b/1 (per year),reported,,,,-28.0,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,Building age,age,A_structural,level,years,-0.0025,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,semi_elasticity,-0.25,0.01,100*b/1 (per year),reported,,,,-25.0,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,Building age,age,A_structural,level,years,-0.0022,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,semi_elasticity,-0.22,0.01,100*b/1 (per year),reported,,,,-22.0,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,Building age,age,A_structural,level,years,-0.0018,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,semi_elasticity,-0.18,0.01,100*b/1 (per year),reported,,,,-18.0,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,Building age,age,A_structural,level,years,-0.0016,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,semi_elasticity,-0.16,0.01,100*b/1 (per year),reported,,,,-16.0,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,Building age,age,A_structural,level,years,-0.0008,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,semi_elasticity,-0.08,0.01,100*b/1 (per year),reported,,,,-8.0,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,Building age,age,A_structural,level,years,-0.00057,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,semi_elasticity,-0.056999999999999995,0.01,100*b/1 (per year),reported,,,,-5.699999999999999,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,QMS,school_quality,F_neighbourhood,binary,binary,0.0834,0.0109,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),pct_premium,8.691194228479237,1.1848043983051866,100*(exp(b - se^2/2) - 1),reported,,,,7.651376146788991,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,QMS,school_quality,F_neighbourhood,binary,binary,0.0495,0.0189,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,pct_premium,5.055794055658791,1.985909169286018,100*(exp(b - se^2/2) - 1),reported,,,,2.619047619047619,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,QMS,school_quality,F_neighbourhood,binary,binary,0.051,0.0167,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,pct_premium,5.217616234803546,1.7573792317829502,100*(exp(b - se^2/2) - 1),reported,,,,3.053892215568862,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,QMS,school_quality,F_neighbourhood,binary,binary,0.0644,0.015,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,pct_premium,6.639894438997174,1.5997783815296618,100*(exp(b - se^2/2) - 1),reported,,,,4.293333333333333,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,QMS,school_quality,F_neighbourhood,binary,binary,0.075,0.0171,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,pct_premium,7.772657035216302,1.84318189801272,100*(exp(b - se^2/2) - 1),reported,,,,4.385964912280701,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,QMS,school_quality,F_neighbourhood,binary,binary,0.0739,0.0171,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,pct_premium,7.654172291034067,1.8411555126411874,100*(exp(b - se^2/2) - 1),reported,,,,4.321637426900584,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,QMS,school_quality,F_neighbourhood,binary,binary,0.0781,0.0131,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,pct_premium,8.11380053151456,1.4164123170076843,100*(exp(b - se^2/2) - 1),reported,,,,5.961832061068702,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,QMS,school_quality,F_neighbourhood,binary,binary,0.0827,0.0188,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,pct_premium,8.602395578245957,2.0420858824029122,100*(exp(b - se^2/2) - 1),reported,,,,4.398936170212766,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,QMS,school_quality,F_neighbourhood,binary,binary,0.0845,0.0175,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,pct_premium,8.80062305219187,1.9043024774060073,100*(exp(b - se^2/2) - 1),reported,,,,4.828571428571428,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,QMS,school_quality,F_neighbourhood,binary,binary,0.0979,0.0167,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,pct_premium,10.269871780048746,1.841763665555527,100*(exp(b - se^2/2) - 1),reported,,,,5.862275449101797,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,QPS,school_quality,F_neighbourhood,binary,binary,0.0294,0.0118,,,**,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),pct_premium,2.9764751960174474,1.2152070070798866,100*(exp(b - se^2/2) - 1),reported,,,,2.4915254237288136,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,QPS,school_quality,F_neighbourhood,binary,binary,0.0427,0.0192,,,**,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,pct_premium,4.343241726571123,2.0037595400729575,100*(exp(b - se^2/2) - 1),reported,,,,2.2239583333333335,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,QPS,school_quality,F_neighbourhood,binary,binary,0.0222,0.0232,,,,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,pct_premium,2.217312942192229,2.3720799485226847,100*(exp(b - se^2/2) - 1),reported,,,,0.956896551724138,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,QPS,school_quality,F_neighbourhood,binary,binary,0.0235,0.0164,,,*,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,pct_premium,2.3640632297778907,1.6789964132244721,100*(exp(b - se^2/2) - 1),reported,,,,1.4329268292682926,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,QPS,school_quality,F_neighbourhood,binary,binary,0.0177,0.0187,,,,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,pct_premium,1.7679621559664183,1.903393662089007,100*(exp(b - se^2/2) - 1),reported,,,,0.946524064171123,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,QPS,school_quality,F_neighbourhood,binary,binary,0.0157,0.017,,,,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,pct_premium,1.5677116574039918,1.726900617286876,100*(exp(b - se^2/2) - 1),reported,,,,0.9235294117647057,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,QPS,school_quality,F_neighbourhood,binary,binary,0.0274,0.0167,,,***,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,pct_premium,2.763552345780651,1.7163906495819146,100*(exp(b - se^2/2) - 1),reported,,,,1.6407185628742516,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,QPS,school_quality,F_neighbourhood,binary,binary,0.0389,0.0158,,,***,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,pct_premium,3.9536748725151005,1.6426730886447458,100*(exp(b - se^2/2) - 1),reported,,,,2.4620253164556956,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,QPS,school_quality,F_neighbourhood,binary,binary,0.0468,0.0152,,,***,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,pct_premium,4.779135778964139,1.5928268565711012,100*(exp(b - se^2/2) - 1),reported,,,,3.0789473684210527,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,QPS,school_quality,F_neighbourhood,binary,binary,0.0299,0.0174,,,*,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,pct_premium,3.0195530848235785,1.7928115989548667,100*(exp(b - se^2/2) - 1),reported,,,,1.7183908045977012,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,Subway,transit_distance,D_location,binary,binary,0.0481,0.0129,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),pct_premium,4.918827629359845,1.3535654951504803,100*(exp(b - se^2/2) - 1),reported,,,,3.7286821705426356,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,Subway,transit_distance,D_location,binary,binary,0.0606,0.0264,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,pct_premium,6.210365326347933,2.804930936655136,100*(exp(b - se^2/2) - 1),reported,,,,2.2954545454545454,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,Subway,transit_distance,D_location,binary,binary,0.0417,0.0211,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,pct_premium,4.234959927246695,2.1998472969719907,100*(exp(b - se^2/2) - 1),reported,,,,1.9763033175355451,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,Subway,transit_distance,D_location,binary,binary,0.0451,0.0184,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,pct_premium,4.595539360884415,1.9248837409820394,100*(exp(b - se^2/2) - 1),reported,,,,2.4510869565217392,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,Subway,transit_distance,D_location,binary,binary,0.05,0.0197,,,**,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,pct_premium,5.106712226684573,2.0710040598607673,100*(exp(b - se^2/2) - 1),reported,,,,2.538071065989848,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,Subway,transit_distance,D_location,binary,binary,0.0612,0.0226,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,pct_premium,6.284005247522351,2.4026320244185078,100*(exp(b - se^2/2) - 1),reported,,,,2.7079646017699117,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,Subway,transit_distance,D_location,binary,binary,0.0553,0.018,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,pct_premium,5.668642734116203,1.9023437239361627,100*(exp(b - se^2/2) - 1),reported,,,,3.0722222222222224,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,Subway,transit_distance,D_location,binary,binary,0.069,0.0178,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,pct_premium,7.126648566824478,1.9071564522840563,100*(exp(b - se^2/2) - 1),reported,,,,3.876404494382023,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,Subway,transit_distance,D_location,binary,binary,0.048,0.0216,,,**,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,pct_premium,4.892593333947848,2.2662086155008567,100*(exp(b - se^2/2) - 1),reported,,,,2.2222222222222223,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,Subway,transit_distance,D_location,binary,binary,0.00169,0.0256,,,,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,pct_premium,0.13632483794265848,2.5643300578683093,100*(exp(b - se^2/2) - 1),reported,,,,0.066015625,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,Dcbd,cbd_distance,D_location,level,km,-0.0625,0.029,,,**,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),semi_elasticity,-6.25,2.9000000000000004,100*b/1 (X per km->km),reported,,,,-2.155172413793103,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,Dcbd,cbd_distance,D_location,level,km,-0.103,0.0331,,,***,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,semi_elasticity,-10.299999999999999,3.3099999999999996,100*b/1 (X per km->km),reported,,,,-3.11178247734139,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,Dcbd,cbd_distance,D_location,level,km,-0.0675,0.0395,,,***,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,semi_elasticity,-6.75,3.95,100*b/1 (X per km->km),reported,,,,-1.7088607594936709,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,Dcbd,cbd_distance,D_location,level,km,-0.06,0.0302,,,**,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,semi_elasticity,-6.0,3.02,100*b/1 (X per km->km),reported,,,,-1.9867549668874172,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,Dcbd,cbd_distance,D_location,level,km,-0.069,0.0297,,,*,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,semi_elasticity,-6.9,2.97,100*b/1 (X per km->km),reported,,,,-2.3232323232323235,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,Dcbd,cbd_distance,D_location,level,km,-0.0705,0.0333,,,**,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,semi_elasticity,-7.049999999999999,3.3300000000000005,100*b/1 (X per km->km),reported,,,,-2.117117117117117,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,Dcbd,cbd_distance,D_location,level,km,-0.0615,0.0323,,,***,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,semi_elasticity,-6.15,3.2300000000000004,100*b/1 (X per km->km),reported,,,,-1.9040247678018574,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,Dcbd,cbd_distance,D_location,level,km,-0.0489,0.0195,,,**,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,semi_elasticity,-4.89,1.95,100*b/1 (X per km->km),reported,,,,-2.5076923076923077,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,Dcbd,cbd_distance,D_location,level,km,-0.03295,0.0505,,,,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,semi_elasticity,-3.295,5.050000000000001,100*b/1 (X per km->km),reported,,,,-0.6524752475247524,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,Dcbd,cbd_distance,D_location,level,km,-0.054,0.0813,,,,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,semi_elasticity,-5.4,8.129999999999999,100*b/1 (X per km->km),reported,,,,-0.6642066420664207,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,D.Xriver,water_proximity,E_environment,level,km,-0.0168,0.0056,,,***,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),semi_elasticity,-1.68,0.5599999999999999,100*b/1 (X per km->km),reported,,,,-3.0,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,D.Xriver,water_proximity,E_environment,level,km,-0.0125,0.0111,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,semi_elasticity,-1.25,1.11,100*b/1 (X per km->km),reported,,,,-1.1261261261261262,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,D.Xriver,water_proximity,E_environment,level,km,-0.0085,0.0083,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,semi_elasticity,-0.8500000000000001,0.83,100*b/1 (X per km->km),reported,,,,-1.0240963855421688,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,D.Xriver,water_proximity,E_environment,level,km,0.00265,0.0072,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,semi_elasticity,0.265,0.72,100*b/1 (X per km->km),reported,,,,0.3680555555555556,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,D.Xriver,water_proximity,E_environment,level,km,0.00066,0.0061,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,semi_elasticity,0.066,0.61,100*b/1 (X per km->km),reported,,,,0.1081967213114754,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,D.Xriver,water_proximity,E_environment,level,km,-0.0064,0.0078,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,semi_elasticity,-0.64,0.7799999999999999,100*b/1 (X per km->km),reported,,,,-0.8205128205128206,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,D.Xriver,water_proximity,E_environment,level,km,-0.0087,0.0072,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,semi_elasticity,-0.8699999999999999,0.72,100*b/1 (X per km->km),reported,,,,-1.2083333333333333,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,D.Xriver,water_proximity,E_environment,level,km,-0.013,0.0071,,,*,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,semi_elasticity,-1.3,0.7100000000000001,100*b/1 (X per km->km),reported,,,,-1.8309859154929575,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,D.Xriver,water_proximity,E_environment,level,km,-0.0252,0.0097,,,**,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,semi_elasticity,-2.52,0.97,100*b/1 (X per km->km),reported,,,,-2.597938144329897,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,D.Xriver,water_proximity,E_environment,level,km,-0.028,0.0083,,,**,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,semi_elasticity,-2.8000000000000003,0.83,100*b/1 (X per km->km),reported,,,,-3.3734939759036147,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,D.Lriver,water_proximity,E_environment,level,km,-0.0245,0.012,,,**,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),semi_elasticity,-2.45,1.2,100*b/1 (X per km->km),reported,,,,-2.0416666666666665,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,D.Lriver,water_proximity,E_environment,level,km,-0.0357,0.0224,,,,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,semi_elasticity,-3.5700000000000003,2.2399999999999998,100*b/1 (X per km->km),reported,,,,-1.5937500000000002,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,D.Lriver,water_proximity,E_environment,level,km,-0.0318,0.0158,,,**,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,semi_elasticity,-3.18,1.58,100*b/1 (X per km->km),reported,,,,-2.0126582278481013,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,D.Lriver,water_proximity,E_environment,level,km,-0.0315,0.0119,,,***,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,semi_elasticity,-3.15,1.1900000000000002,100*b/1 (X per km->km),reported,,,,-2.6470588235294117,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,D.Lriver,water_proximity,E_environment,level,km,-0.0263,0.0083,,,***,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,semi_elasticity,-2.63,0.83,100*b/1 (X per km->km),reported,,,,-3.1686746987951806,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,D.Lriver,water_proximity,E_environment,level,km,-0.0223,0.0061,,,***,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,semi_elasticity,-2.23,0.61,100*b/1 (X per km->km),reported,,,,-3.6557377049180326,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,D.Lriver,water_proximity,E_environment,level,km,-0.01385,0.0371,,,,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,semi_elasticity,-1.385,3.71,100*b/1 (X per km->km),reported,,,,-0.3733153638814016,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,D.Lriver,water_proximity,E_environment,level,km,-0.0075,0.0435,,,,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,semi_elasticity,-0.75,4.35,100*b/1 (X per km->km),reported,,,,-0.1724137931034483,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,D.Lriver,water_proximity,E_environment,level,km,-0.0025,0.0446,,,,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,semi_elasticity,-0.25,4.46,100*b/1 (X per km->km),reported,,,,-0.05605381165919283,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,D.Lriver,water_proximity,E_environment,level,km,-0.0171,0.0537,,,,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,semi_elasticity,-1.71,5.37,100*b/1 (X per km->km),reported,,,,-0.31843575418994413,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,D.YHwetland,water_proximity,E_environment,level,km,-0.0251,0.0049,,,***,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),semi_elasticity,-2.5100000000000002,0.49,100*b/1 (X per km->km),reported,,,,-5.122448979591837,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,D.YHwetland,water_proximity,E_environment,level,km,-0.00795,0.0097,,,,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,semi_elasticity,-0.795,0.97,100*b/1 (X per km->km),reported,,,,-0.8195876288659794,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,D.YHwetland,water_proximity,E_environment,level,km,-0.0183,0.0101,,,**,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,semi_elasticity,-1.83,1.01,100*b/1 (X per km->km),reported,,,,-1.811881188118812,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,D.YHwetland,water_proximity,E_environment,level,km,-0.0166,0.0092,,,*,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,semi_elasticity,-1.66,0.9199999999999999,100*b/1 (X per km->km),reported,,,,-1.8043478260869565,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,D.YHwetland,water_proximity,E_environment,level,km,-0.0235,0.0095,,,**,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,semi_elasticity,-2.35,0.95,100*b/1 (X per km->km),reported,,,,-2.473684210526316,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,D.YHwetland,water_proximity,E_environment,level,km,-0.0273,0.0087,,,***,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,semi_elasticity,-2.73,0.8699999999999999,100*b/1 (X per km->km),reported,,,,-3.137931034482759,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,D.YHwetland,water_proximity,E_environment,level,km,-0.0299,0.0086,,,***,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,semi_elasticity,-2.9899999999999998,0.86,100*b/1 (X per km->km),reported,,,,-3.4767441860465116,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,D.YHwetland,water_proximity,E_environment,level,km,-0.0312,0.0069,,,***,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,semi_elasticity,-3.1199999999999997,0.69,100*b/1 (X per km->km),reported,,,,-4.521739130434782,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,D.YHwetland,water_proximity,E_environment,level,km,-0.0405,0.0067,,,***,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,semi_elasticity,-4.05,0.67,100*b/1 (X per km->km),reported,,,,-6.044776119402985,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,D.YHwetland,water_proximity,E_environment,level,km,-0.042,0.0084,,,***,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,semi_elasticity,-4.2,0.84,100*b/1 (X per km->km),reported,,,,-5.000000000000001,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,D.LL,water_proximity,E_environment,level,km,-0.0173,0.0066,,,***,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),semi_elasticity,-1.73,0.66,100*b/1 (X per km->km),reported,,,,-2.621212121212121,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,D.LL,water_proximity,E_environment,level,km,0.00134,0.0181,,,,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,semi_elasticity,0.134,1.81,100*b/1 (X per km->km),reported,,,,0.07403314917127071,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,D.LL,water_proximity,E_environment,level,km,-0.0156,0.0131,,,,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,semi_elasticity,-1.5599999999999998,1.31,100*b/1 (X per km->km),reported,,,,-1.1908396946564885,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,D.LL,water_proximity,E_environment,level,km,-0.0164,0.0121,,,,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,semi_elasticity,-1.6400000000000001,1.21,100*b/1 (X per km->km),reported,,,,-1.3553719008264464,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,D.LL,water_proximity,E_environment,level,km,-0.0205,0.0089,,,*,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,semi_elasticity,-2.0500000000000003,0.89,100*b/1 (X per km->km),reported,,,,-2.303370786516854,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,D.LL,water_proximity,E_environment,level,km,-0.0207,0.0069,,,**,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,semi_elasticity,-2.07,0.69,100*b/1 (X per km->km),reported,,,,-3.0,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,D.LL,water_proximity,E_environment,level,km,-0.0223,0.0052,,,**,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,semi_elasticity,-2.23,0.52,100*b/1 (X per km->km),reported,,,,-4.288461538461538,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,D.LL,water_proximity,E_environment,level,km,-0.0243,0.0068,,,***,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,semi_elasticity,-2.4299999999999997,0.6799999999999999,100*b/1 (X per km->km),reported,,,,-3.573529411764706,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,D.LL,water_proximity,E_environment,level,km,-0.0209,0.0077,,,**,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,semi_elasticity,-2.09,0.77,100*b/1 (X per km->km),reported,,,,-2.714285714285714,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,D.LL,water_proximity,E_environment,level,km,-0.0319,0.0105,,,***,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,semi_elasticity,-3.19,1.05,100*b/1 (X per km->km),reported,,,,-3.0380952380952375,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,D.ML,water_proximity,E_environment,level,km,-0.0143,0.0045,,,***,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),semi_elasticity,-1.43,0.44999999999999996,100*b/1 (X per km->km),reported,,,,-3.177777777777778,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,D.ML,water_proximity,E_environment,level,km,-0.0344,0.0108,,,***,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,semi_elasticity,-3.44,1.08,100*b/1 (X per km->km),reported,,,,-3.185185185185185,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,D.ML,water_proximity,E_environment,level,km,-0.0156,0.0098,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,semi_elasticity,-1.5599999999999998,0.98,100*b/1 (X per km->km),reported,,,,-1.5918367346938775,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,D.ML,water_proximity,E_environment,level,km,-0.0039,0.0048,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,semi_elasticity,-0.38999999999999996,0.48,100*b/1 (X per km->km),reported,,,,-0.8125,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,D.ML,water_proximity,E_environment,level,km,-0.0014,0.0043,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,semi_elasticity,-0.13999999999999999,0.43,100*b/1 (X per km->km),reported,,,,-0.32558139534883723,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,D.ML,water_proximity,E_environment,level,km,-0.004,0.0045,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,semi_elasticity,-0.4,0.44999999999999996,100*b/1 (X per km->km),reported,,,,-0.888888888888889,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,D.ML,water_proximity,E_environment,level,km,-0.0082,0.0055,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,semi_elasticity,-0.8200000000000001,0.5499999999999999,100*b/1 (X per km->km),reported,,,,-1.4909090909090912,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,D.ML,water_proximity,E_environment,level,km,-0.0066,0.0052,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,semi_elasticity,-0.66,0.52,100*b/1 (X per km->km),reported,,,,-1.2692307692307694,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,D.ML,water_proximity,E_environment,level,km,-0.0053,0.0048,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,semi_elasticity,-0.53,0.48,100*b/1 (X per km->km),reported,,,,-1.1041666666666667,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,D.ML,water_proximity,E_environment,level,km,-0.0019,0.0058,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,semi_elasticity,-0.19,0.58,100*b/1 (X per km->km),reported,,,,-0.32758620689655177,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,D.SL,water_proximity,E_environment,level,km,-0.0124,0.0167,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),semi_elasticity,-1.24,1.67,100*b/1 (X per km->km),reported,,,,-0.7425149700598802,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,D.SL,water_proximity,E_environment,level,km,-0.0214,0.026,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,semi_elasticity,-2.1399999999999997,2.6,100*b/1 (X per km->km),reported,,,,-0.823076923076923,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,D.SL,water_proximity,E_environment,level,km,0.00524,0.0288,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,semi_elasticity,0.524,2.88,100*b/1 (X per km->km),reported,,,,0.18194444444444444,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,D.SL,water_proximity,E_environment,level,km,-0.0001,0.0212,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,semi_elasticity,-0.01,2.12,100*b/1 (X per km->km),reported,,,,-0.0047169811320754715,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,D.SL,water_proximity,E_environment,level,km,0.0044,0.0241,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,semi_elasticity,0.44,2.41,100*b/1 (X per km->km),reported,,,,0.18257261410788383,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,D.SL,water_proximity,E_environment,level,km,0.00533,0.0216,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,semi_elasticity,0.5329999999999999,2.16,100*b/1 (X per km->km),reported,,,,0.24675925925925923,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,D.SL,water_proximity,E_environment,level,km,-0.0113,0.0139,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,semi_elasticity,-1.13,1.39,100*b/1 (X per km->km),reported,,,,-0.8129496402877698,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,D.SL,water_proximity,E_environment,level,km,-0.0118,0.0183,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,semi_elasticity,-1.18,1.83,100*b/1 (X per km->km),reported,,,,-0.6448087431693988,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,D.SL,water_proximity,E_environment,level,km,-0.0098,0.0293,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,semi_elasticity,-0.98,2.93,100*b/1 (X per km->km),reported,,,,-0.33447098976109213,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,D.SL,water_proximity,E_environment,level,km,-0.0421,0.0378,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,semi_elasticity,-4.21,3.7800000000000002,100*b/1 (X per km->km),reported,,,,-1.1137566137566137,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,D.YL,green_space,E_environment,level,km,-0.0234,0.0045,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),semi_elasticity,-2.34,0.44999999999999996,100*b/1 (X per km->km),reported,,,,-5.2,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,D.YL,green_space,E_environment,level,km,-0.0277,0.0068,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,semi_elasticity,-2.77,0.6799999999999999,100*b/1 (X per km->km),reported,,,,-4.073529411764706,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,D.YL,green_space,E_environment,level,km,-0.0323,0.0068,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,semi_elasticity,-3.2300000000000004,0.6799999999999999,100*b/1 (X per km->km),reported,,,,-4.750000000000001,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,D.YL,green_space,E_environment,level,km,-0.0349,0.0056,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,semi_elasticity,-3.49,0.5599999999999999,100*b/1 (X per km->km),reported,,,,-6.232142857142858,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,D.YL,green_space,E_environment,level,km,-0.0311,0.0037,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,semi_elasticity,-3.11,0.37,100*b/1 (X per km->km),reported,,,,-8.405405405405405,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,D.YL,green_space,E_environment,level,km,-0.0281,0.0052,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,semi_elasticity,-2.81,0.52,100*b/1 (X per km->km),reported,,,,-5.403846153846154,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,D.YL,green_space,E_environment,level,km,-0.0251,0.0044,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,semi_elasticity,-2.5100000000000002,0.44,100*b/1 (X per km->km),reported,,,,-5.704545454545454,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,D.YL,green_space,E_environment,level,km,-0.019,0.0078,,,**,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,semi_elasticity,-1.9,0.7799999999999999,100*b/1 (X per km->km),reported,,,,-2.435897435897436,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,D.YL,green_space,E_environment,level,km,-0.0182,0.0061,,,**,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,semi_elasticity,-1.82,0.61,100*b/1 (X per km->km),reported,,,,-2.983606557377049,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,D.YL,green_space,E_environment,level,km,-0.0212,0.0073,,,**,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,semi_elasticity,-2.12,0.73,100*b/1 (X per km->km),reported,,,,-2.904109589041096,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c1,3,1,8,D.NWG,green_space,E_environment,level,km,-0.0124,0.0047,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,OLS,,0.519,se,Conditional mean (OLS),semi_elasticity,-1.24,0.47000000000000003,100*b/1 (X per km->km),reported,,,,-2.6382978723404253,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,ols,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c2,3,2,8,D.NWG,green_space,E_environment,level,km,-0.0082,0.0021,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.321,se,Quantile 0.1,semi_elasticity,-0.8200000000000001,0.21,100*b/1 (X per km->km),reported,,,,-3.9047619047619055,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c3,3,3,8,D.NWG,green_space,E_environment,level,km,-0.0108,0.0022,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.307,se,Quantile 0.2,semi_elasticity,-1.08,0.22,100*b/1 (X per km->km),reported,,,,-4.909090909090909,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c4,3,4,8,D.NWG,green_space,E_environment,level,km,-0.0861,0.0015,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.313,se,Quantile 0.3,semi_elasticity,-8.61,0.15,100*b/1 (X per km->km),reported,,,,-57.4,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c5,3,5,8,D.NWG,green_space,E_environment,level,km,0.0089,0.0022,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.346,se,Quantile 0.4,semi_elasticity,0.89,0.22,100*b/1 (X per km->km),reported,,,,4.045454545454545,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c6,3,6,8,D.NWG,green_space,E_environment,level,km,-0.0138,0.0024,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.331,se,Quantile 0.5,semi_elasticity,-1.38,0.24,100*b/1 (X per km->km),reported,,,,-5.75,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c7,3,7,8,D.NWG,green_space,E_environment,level,km,-0.0135,0.0022,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.358,se,Quantile 0.6,semi_elasticity,-1.35,0.22,100*b/1 (X per km->km),reported,,,,-6.136363636363636,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c8,3,8,8,D.NWG,green_space,E_environment,level,km,-0.0131,0.0026,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.7,semi_elasticity,-1.31,0.26,100*b/1 (X per km->km),reported,,,,-5.038461538461539,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c9,3,9,8,D.NWG,green_space,E_environment,level,km,-0.0095,0.0026,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.343,se,Quantile 0.8,semi_elasticity,-0.95,0.26,100*b/1 (X per km->km),reported,,,,-3.6538461538461537,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T3-c10,3,10,8,D.NWG,green_space,E_environment,level,km,-0.0054,0.0038,,,,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.9,semi_elasticity,-0.54,0.38,100*b/1 (X per km->km),reported,,,,-1.4210526315789473,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,Building age,age,A_structural,level,years,-0.0015,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),semi_elasticity,-0.15,0.01,100*b/1 (per year),reported,,,,-15.0,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,Building age,age,A_structural,level,years,-0.0026,0.0002,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.26,0.02,100*b/1 (per year),reported,,,,-12.999999999999998,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,Building age,age,A_structural,level,years,-0.0024,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.24,0.01,100*b/1 (per year),reported,,,,-23.999999999999996,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,Building age,age,A_structural,level,years,-0.0026,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.26,0.01,100*b/1 (per year),reported,,,,-25.999999999999996,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,Building age,age,A_structural,level,years,-0.0024,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.24,0.01,100*b/1 (per year),reported,,,,-23.999999999999996,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,Building age,age,A_structural,level,years,-0.0021,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.21,0.01,100*b/1 (per year),reported,,,,-20.999999999999996,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,Building age,age,A_structural,level,years,-0.002,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.2,0.01,100*b/1 (per year),reported,,,,-20.0,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,Building age,age,A_structural,level,years,-0.0017,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.16999999999999998,0.01,100*b/1 (per year),reported,,,,-17.0,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,Building age,age,A_structural,level,years,-0.0009,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.09,0.01,100*b/1 (per year),reported,,,,-9.0,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,Building age,age,A_structural,level,years,-0.0006,0.0001,,,***,,,medium,"Age of house in years (2019 minus building year). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.06,0.01,100*b/1 (per year),reported,,,,-5.999999999999999,,years,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,QMS,school_quality,F_neighbourhood,binary,binary,0.0817,0.0111,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),pct_premium,8.506337453899349,1.2044945463392225,100*(exp(b - se^2/2) - 1),reported,,,,7.360360360360359,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,QMS,school_quality,F_neighbourhood,binary,binary,0.0623,0.021,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),pct_premium,6.4046933096782555,2.2349913207605465,100*(exp(b - se^2/2) - 1),reported,,,,2.9666666666666663,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,QMS,school_quality,F_neighbourhood,binary,binary,0.0478,0.0145,,,**,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),pct_premium,4.885057596285547,1.520993221154359,100*(exp(b - se^2/2) - 1),reported,,,,3.296551724137931,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,QMS,school_quality,F_neighbourhood,binary,binary,0.0653,0.0115,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),pct_premium,6.740863538876951,1.2276011031362366,100*(exp(b - se^2/2) - 1),reported,,,,5.678260869565217,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,QMS,school_quality,F_neighbourhood,binary,binary,0.0705,0.0136,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),pct_premium,7.294533885742438,1.4593406144257695,100*(exp(b - se^2/2) - 1),reported,,,,5.1838235294117645,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,QMS,school_quality,F_neighbourhood,binary,binary,0.0669,0.0099,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),pct_premium,6.913615967179632,1.0584966684333512,100*(exp(b - se^2/2) - 1),reported,,,,6.757575757575757,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,QMS,school_quality,F_neighbourhood,binary,binary,0.0743,0.0127,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),pct_premium,7.704303436108373,1.3679549679187566,100*(exp(b - se^2/2) - 1),reported,,,,5.850393700787402,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,QMS,school_quality,F_neighbourhood,binary,binary,0.0797,0.0134,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),pct_premium,8.28649063220912,1.4511692545989177,100*(exp(b - se^2/2) - 1),reported,,,,5.94776119402985,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,QMS,school_quality,F_neighbourhood,binary,binary,0.0773,0.0124,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),pct_premium,8.028308226630054,1.3396540106516175,100*(exp(b - se^2/2) - 1),reported,,,,6.233870967741935,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,QMS,school_quality,F_neighbourhood,binary,binary,0.0981,0.0164,,,***,,,medium,"Residential district belongs to a quality middle-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),pct_premium,10.292475560730963,1.809039862519307,100*(exp(b - se^2/2) - 1),reported,,,,5.9817073170731705,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,QPS,school_quality,F_neighbourhood,binary,binary,0.028,0.0119,,,**,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),pct_premium,2.832287144278145,1.2237908644614959,100*(exp(b - se^2/2) - 1),reported,,,,2.3529411764705883,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,QPS,school_quality,F_neighbourhood,binary,binary,0.0503,0.0136,,,***,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),pct_premium,5.148927879176846,1.4301576740229394,100*(exp(b - se^2/2) - 1),reported,,,,3.698529411764706,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,QPS,school_quality,F_neighbourhood,binary,binary,0.0208,0.014,,,,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),pct_premium,2.091777280593843,1.4294249587103929,100*(exp(b - se^2/2) - 1),reported,,,,1.4857142857142855,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,QPS,school_quality,F_neighbourhood,binary,binary,0.0244,0.0149,,,,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),pct_premium,2.4586375448556907,1.526803172798176,100*(exp(b - se^2/2) - 1),reported,,,,1.6375838926174497,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,QPS,school_quality,F_neighbourhood,binary,binary,0.0182,0.0134,,,,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),pct_premium,1.8275204497828934,1.364611283328583,100*(exp(b - se^2/2) - 1),reported,,,,1.3582089552238805,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,QPS,school_quality,F_neighbourhood,binary,binary,0.0104,0.0178,,,,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),pct_premium,1.029420447962237,1.7986085969791061,100*(exp(b - se^2/2) - 1),reported,,,,0.5842696629213483,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,True
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,QPS,school_quality,F_neighbourhood,binary,binary,0.0236,0.0138,,,*,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),pct_premium,2.378319441860266,1.4129553435001572,100*(exp(b - se^2/2) - 1),reported,,,,1.710144927536232,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,QPS,school_quality,F_neighbourhood,binary,binary,0.0348,0.0161,,,**,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),pct_premium,3.52784196139051,1.6670142949658915,100*(exp(b - se^2/2) - 1),reported,,,,2.1614906832298137,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,QPS,school_quality,F_neighbourhood,binary,binary,0.0462,0.0156,,,**,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),pct_premium,4.715642103627604,1.63376280097994,100*(exp(b - se^2/2) - 1),reported,,,,2.9615384615384617,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,QPS,school_quality,F_neighbourhood,binary,binary,0.0342,0.0306,,,,,,medium,"Residential district belongs to a quality primary-school district (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),pct_premium,3.430718902888752,3.166462125688157,100*(exp(b - se^2/2) - 1),reported,,,,1.1176470588235294,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,Subway,transit_distance,D_location,binary,binary,0.0472,0.0129,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),pct_premium,4.824443163873826,1.352347834234449,100*(exp(b - se^2/2) - 1),reported,,,,3.6589147286821704,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,Subway,transit_distance,D_location,binary,binary,0.0534,0.022,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),pct_premium,5.459625816536873,2.3206733029546522,100*(exp(b - se^2/2) - 1),reported,,,,2.4272727272727277,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,Subway,transit_distance,D_location,binary,binary,0.047,0.0178,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),pct_premium,4.795597874258739,1.8656571761617873,100*(exp(b - se^2/2) - 1),reported,,,,2.640449438202247,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,Subway,transit_distance,D_location,binary,binary,0.0417,0.0142,,,**,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),pct_premium,4.247654954857705,1.4804659534124298,100*(exp(b - se^2/2) - 1),reported,,,,2.936619718309859,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,Subway,transit_distance,D_location,binary,binary,0.0475,0.0196,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),pct_premium,4.844479650249256,2.055346554197719,100*(exp(b - se^2/2) - 1),reported,,,,2.423469387755102,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,Subway,transit_distance,D_location,binary,binary,0.0573,0.0216,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),pct_premium,5.872644626755608,2.2873826623310527,100*(exp(b - se^2/2) - 1),reported,,,,2.6527777777777777,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,Subway,transit_distance,D_location,binary,binary,0.0553,0.0183,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),pct_premium,5.668067369922936,1.9340494526684322,100*(exp(b - se^2/2) - 1),reported,,,,3.021857923497268,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,Subway,transit_distance,D_location,binary,binary,0.0707,0.02,,,***,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),pct_premium,7.304456943071291,2.1465183996138424,100*(exp(b - se^2/2) - 1),reported,,,,3.5349999999999997,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,Subway,transit_distance,D_location,binary,binary,0.0444,0.0205,,,*,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),pct_premium,4.518078975139184,2.143070884452277,100*(exp(b - se^2/2) - 1),reported,,,,2.1658536585365855,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,Subway,transit_distance,D_location,binary,binary,0.0165,0.023,,,,,,medium,"Subway station within 1 km of property (1/0). Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),pct_premium,1.636801189109538,2.338264816607928,100*(exp(b - se^2/2) - 1),reported,,,,0.7173913043478262,,binary,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,D.CBD,cbd_distance,D_location,level,km,-0.0575,0.0267,,,**,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),semi_elasticity,-5.75,2.67,100*b/1 (X per km->km),reported,,,,-2.153558052434457,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,D.CBD,cbd_distance,D_location,level,km,-0.1365,0.045,,,***,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-13.65,4.5,100*b/1 (X per km->km),reported,,,,-3.0333333333333337,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,D.CBD,cbd_distance,D_location,level,km,-0.079,0.0271,,,***,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-7.9,2.71,100*b/1 (X per km->km),reported,,,,-2.915129151291513,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,D.CBD,cbd_distance,D_location,level,km,-0.0595,0.0202,,,***,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-5.949999999999999,2.02,100*b/1 (X per km->km),reported,,,,-2.9455445544554455,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,D.CBD,cbd_distance,D_location,level,km,-0.0672,0.0266,,,***,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-6.72,2.6599999999999997,100*b/1 (X per km->km),reported,,,,-2.526315789473684,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,D.CBD,cbd_distance,D_location,level,km,-0.0557,0.0291,,,*,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-5.57,2.91,100*b/1 (X per km->km),reported,,,,-1.9140893470790377,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,D.CBD,cbd_distance,D_location,level,km,-0.0555,0.0274,,,**,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-5.55,2.74,100*b/1 (X per km->km),reported,,,,-2.0255474452554743,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,D.CBD,cbd_distance,D_location,level,km,-0.0381,0.0224,,,**,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-3.81,2.2399999999999998,100*b/1 (X per km->km),reported,,,,-1.7008928571428572,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,D.CBD,cbd_distance,D_location,level,km,-0.00635,0.0507,,,,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.635,5.07,100*b/1 (X per km->km),reported,,,,-0.1252465483234714,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,D.CBD,cbd_distance,D_location,level,km,-0.0417,0.0984,,,,,,medium,"Walking distance to CBD (Wuyi Square), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-4.17,9.84,100*b/1 (X per km->km),reported,,,,-0.42378048780487804,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,D.Xriver,water_proximity,E_environment,level,km,-0.0172,0.0057,,,***,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),semi_elasticity,-1.72,0.5700000000000001,100*b/1 (X per km->km),reported,,,,-3.017543859649123,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,D.Xriver,water_proximity,E_environment,level,km,-0.0128,0.0106,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.28,1.06,100*b/1 (X per km->km),reported,,,,-1.2075471698113207,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,D.Xriver,water_proximity,E_environment,level,km,-0.00706,0.0084,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.7060000000000001,0.84,100*b/1 (X per km->km),reported,,,,-0.8404761904761906,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,D.Xriver,water_proximity,E_environment,level,km,0.0004,0.0071,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),semi_elasticity,0.04,0.7100000000000001,100*b/1 (X per km->km),reported,,,,0.056338028169014086,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,D.Xriver,water_proximity,E_environment,level,km,-0.0007,0.0086,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.06999999999999999,0.86,100*b/1 (X per km->km),reported,,,,-0.08139534883720931,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,D.Xriver,water_proximity,E_environment,level,km,-0.0073,0.0091,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.73,0.91,100*b/1 (X per km->km),reported,,,,-0.8021978021978021,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,D.Xriver,water_proximity,E_environment,level,km,-0.0066,0.0097,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.66,0.97,100*b/1 (X per km->km),reported,,,,-0.6804123711340206,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,D.Xriver,water_proximity,E_environment,level,km,-0.0115,0.0135,,,,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.15,1.35,100*b/1 (X per km->km),reported,,,,-0.8518518518518519,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,D.Xriver,water_proximity,E_environment,level,km,-0.0236,0.0132,,,**,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.36,1.32,100*b/1 (X per km->km),reported,,,,-1.7878787878787878,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,D.Xriver,water_proximity,E_environment,level,km,-0.0314,0.0097,,,***,,,medium,"Walking distance to Xiangjiang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-3.1399999999999997,0.97,100*b/1 (X per km->km),reported,,,,-3.2371134020618553,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,D.Lriver,water_proximity,E_environment,level,km,-0.0236,0.0118,,,**,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),semi_elasticity,-2.36,1.18,100*b/1 (X per km->km),reported,,,,-2.0,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,D.Lriver,water_proximity,E_environment,level,km,-0.0312,0.0512,,,,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-3.1199999999999997,5.12,100*b/1 (X per km->km),reported,,,,-0.6093749999999999,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,D.Lriver,water_proximity,E_environment,level,km,-0.0325,0.0529,,,,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-3.25,5.29,100*b/1 (X per km->km),reported,,,,-0.6143667296786389,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,D.Lriver,water_proximity,E_environment,level,km,-0.0221,0.0111,,,**,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.21,1.11,100*b/1 (X per km->km),reported,,,,-1.990990990990991,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,D.Lriver,water_proximity,E_environment,level,km,-0.0252,0.0104,,,***,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.52,1.04,100*b/1 (X per km->km),reported,,,,-2.4230769230769234,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,D.Lriver,water_proximity,E_environment,level,km,-0.0214,0.0081,,,***,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.1399999999999997,0.8099999999999999,100*b/1 (X per km->km),reported,,,,-2.6419753086419755,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,D.Lriver,water_proximity,E_environment,level,km,-0.0112,0.0261,,,,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.1199999999999999,2.6100000000000003,100*b/1 (X per km->km),reported,,,,-0.4291187739463601,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,D.Lriver,water_proximity,E_environment,level,km,-0.0062,0.0263,,,,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.62,2.63,100*b/1 (X per km->km),reported,,,,-0.23574144486692014,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,D.Lriver,water_proximity,E_environment,level,km,-0.0015,0.0363,,,,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.15,3.63,100*b/1 (X per km->km),reported,,,,-0.04132231404958678,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,D.Lriver,water_proximity,E_environment,level,km,-0.0083,0.0543,,,,,,medium,"Walking distance to Liuyang River, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.83,5.43,100*b/1 (X per km->km),reported,,,,-0.15285451197053407,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,D.YHwetland,water_proximity,E_environment,level,km,-0.0227,0.0056,,,***,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),semi_elasticity,-2.27,0.5599999999999999,100*b/1 (X per km->km),reported,,,,-4.053571428571429,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,D.YHwetland,water_proximity,E_environment,level,km,-0.0125,0.0099,,,,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.25,0.9900000000000001,100*b/1 (X per km->km),reported,,,,-1.2626262626262625,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,D.YHwetland,water_proximity,E_environment,level,km,-0.0153,0.0081,,,*,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.53,0.8099999999999999,100*b/1 (X per km->km),reported,,,,-1.8888888888888888,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,D.YHwetland,water_proximity,E_environment,level,km,-0.0171,0.0069,,,**,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.71,0.69,100*b/1 (X per km->km),reported,,,,-2.4782608695652177,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,D.YHwetland,water_proximity,E_environment,level,km,-0.0222,0.0067,,,***,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.22,0.67,100*b/1 (X per km->km),reported,,,,-3.3134328358208958,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,D.YHwetland,water_proximity,E_environment,level,km,-0.0237,0.0071,,,***,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.37,0.7100000000000001,100*b/1 (X per km->km),reported,,,,-3.338028169014084,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,D.YHwetland,water_proximity,E_environment,level,km,-0.0235,0.0095,,,***,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.35,0.95,100*b/1 (X per km->km),reported,,,,-2.473684210526316,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,D.YHwetland,water_proximity,E_environment,level,km,-0.0215,0.0086,,,*,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.15,0.86,100*b/1 (X per km->km),reported,,,,-2.5,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,D.YHwetland,water_proximity,E_environment,level,km,-0.026,0.0071,,,**,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.6,0.7100000000000001,100*b/1 (X per km->km),reported,,,,-3.661971830985915,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,D.YHwetland,water_proximity,E_environment,level,km,-0.0285,0.0073,,,***,,,medium,"Walking distance to Yanghu National Wetland Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.85,0.73,100*b/1 (X per km->km),reported,,,,-3.904109589041096,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,D.LL,water_proximity,E_environment,level,km,-0.0166,0.0008,,,**,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),semi_elasticity,-1.66,0.08,100*b/1 (X per km->km),reported,,,,-20.75,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,D.LL,water_proximity,E_environment,level,km,-0.0074,0.0011,,,,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.74,0.11,100*b/1 (X per km->km),reported,,,,-6.7272727272727275,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,D.LL,water_proximity,E_environment,level,km,-0.0189,0.0184,,,,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.8900000000000001,1.8399999999999999,100*b/1 (X per km->km),reported,,,,-1.0271739130434783,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,D.LL,water_proximity,E_environment,level,km,-0.0152,0.0181,,,,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.52,1.81,100*b/1 (X per km->km),reported,,,,-0.8397790055248618,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,D.LL,water_proximity,E_environment,level,km,-0.021,0.0103,,,**,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.1,1.03,100*b/1 (X per km->km),reported,,,,-2.0388349514563107,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,D.LL,water_proximity,E_environment,level,km,-0.0179,0.0087,,,**,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.79,0.8699999999999999,100*b/1 (X per km->km),reported,,,,-2.057471264367816,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,D.LL,water_proximity,E_environment,level,km,-0.0231,0.0095,,,***,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.31,0.95,100*b/1 (X per km->km),reported,,,,-2.431578947368421,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,D.LL,water_proximity,E_environment,level,km,-0.0235,0.0093,,,***,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.35,0.9299999999999999,100*b/1 (X per km->km),reported,,,,-2.526881720430108,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,D.LL,water_proximity,E_environment,level,km,-0.0195,0.0077,,,***,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.95,0.77,100*b/1 (X per km->km),reported,,,,-2.5324675324675323,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,D.LL,water_proximity,E_environment,level,km,-0.0143,0.0081,,,*,,,medium,"Walking distance to nearest large lake (>200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.43,0.8099999999999999,100*b/1 (X per km->km),reported,,,,-1.7654320987654322,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,D.ML,water_proximity,E_environment,level,km,-0.0145,0.0085,,,*,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),semi_elasticity,-1.4500000000000002,0.8500000000000001,100*b/1 (X per km->km),reported,,,,-1.7058823529411764,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,D.ML,water_proximity,E_environment,level,km,-0.0332,0.0137,,,**,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-3.32,1.37,100*b/1 (X per km->km),reported,,,,-2.423357664233577,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,D.ML,water_proximity,E_environment,level,km,-0.0159,0.0122,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.59,1.22,100*b/1 (X per km->km),reported,,,,-1.3032786885245902,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,D.ML,water_proximity,E_environment,level,km,-0.0051,0.0066,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.51,0.66,100*b/1 (X per km->km),reported,,,,-0.7727272727272728,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,D.ML,water_proximity,E_environment,level,km,-0.0013,0.0066,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.13,0.66,100*b/1 (X per km->km),reported,,,,-0.19696969696969696,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,D.ML,water_proximity,E_environment,level,km,-0.0038,0.0047,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.38,0.47000000000000003,100*b/1 (X per km->km),reported,,,,-0.8085106382978723,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,D.ML,water_proximity,E_environment,level,km,-0.0071,0.005,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.7100000000000001,0.5,100*b/1 (X per km->km),reported,,,,-1.4200000000000002,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,D.ML,water_proximity,E_environment,level,km,-0.0051,0.0048,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.51,0.48,100*b/1 (X per km->km),reported,,,,-1.0625000000000002,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,D.ML,water_proximity,E_environment,level,km,-0.0049,0.0055,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.49,0.5499999999999999,100*b/1 (X per km->km),reported,,,,-0.890909090909091,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,D.ML,water_proximity,E_environment,level,km,-0.005,0.0041,,,,,,medium,"Walking distance to nearest medium lake (18,000-200,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.5,0.41000000000000003,100*b/1 (X per km->km),reported,,,,-1.2195121951219512,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,D.SL,water_proximity,E_environment,level,km,-0.0128,0.0167,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),semi_elasticity,-1.28,1.67,100*b/1 (X per km->km),reported,,,,-0.7664670658682635,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,D.SL,water_proximity,E_environment,level,km,-0.0207,0.0267,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.07,2.67,100*b/1 (X per km->km),reported,,,,-0.7752808988764044,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,D.SL,water_proximity,E_environment,level,km,0.00136,0.0216,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),semi_elasticity,0.136,2.16,100*b/1 (X per km->km),reported,,,,0.06296296296296297,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,D.SL,water_proximity,E_environment,level,km,-0.0065,0.0231,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.65,2.31,100*b/1 (X per km->km),reported,,,,-0.2813852813852814,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,D.SL,water_proximity,E_environment,level,km,0.00368,0.022,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),semi_elasticity,0.368,2.1999999999999997,100*b/1 (X per km->km),reported,,,,0.1672727272727273,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,D.SL,water_proximity,E_environment,level,km,-0.0008,0.0228,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.08,2.2800000000000002,100*b/1 (X per km->km),reported,,,,-0.03508771929824561,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,D.SL,water_proximity,E_environment,level,km,-0.0107,0.0227,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.0699999999999998,2.27,100*b/1 (X per km->km),reported,,,,-0.47136563876651977,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,D.SL,water_proximity,E_environment,level,km,-0.0137,0.0284,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.37,2.8400000000000003,100*b/1 (X per km->km),reported,,,,-0.48239436619718307,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,D.SL,water_proximity,E_environment,level,km,-0.0218,0.0284,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.18,2.8400000000000003,100*b/1 (X per km->km),reported,,,,-0.7676056338028169,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,D.SL,water_proximity,E_environment,level,km,-0.029,0.0345,,,,,,medium,"Walking distance to nearest small lake (<18,000 m2), km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.9000000000000004,3.45,100*b/1 (X per km->km),reported,,,,-0.8405797101449275,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,D.YL,green_space,E_environment,level,km,-0.0203,0.0058,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),semi_elasticity,-2.03,0.58,100*b/1 (X per km->km),reported,,,,-3.5,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,D.YL,green_space,E_environment,level,km,-0.0424,0.0084,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-4.24,0.84,100*b/1 (X per km->km),reported,,,,-5.047619047619048,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,D.YL,green_space,E_environment,level,km,-0.0373,0.0085,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-3.73,0.8500000000000001,100*b/1 (X per km->km),reported,,,,-4.388235294117647,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,D.YL,green_space,E_environment,level,km,-0.032,0.0073,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-3.2,0.73,100*b/1 (X per km->km),reported,,,,-4.383561643835616,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,D.YL,green_space,E_environment,level,km,-0.0285,0.0077,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.85,0.77,100*b/1 (X per km->km),reported,,,,-3.7012987012987013,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,D.YL,green_space,E_environment,level,km,-0.0211,0.0072,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.11,0.72,100*b/1 (X per km->km),reported,,,,-2.930555555555556,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,D.YL,green_space,E_environment,level,km,-0.0214,0.0066,,,***,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-2.1399999999999997,0.66,100*b/1 (X per km->km),reported,,,,-3.242424242424242,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,D.YL,green_space,E_environment,level,km,-0.0176,0.0103,,,*,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.76,1.03,100*b/1 (X per km->km),reported,,,,-1.70873786407767,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,D.YL,green_space,E_environment,level,km,-0.0066,0.0118,,,,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.66,1.18,100*b/1 (X per km->km),reported,,,,-0.5593220338983051,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,D.YL,green_space,E_environment,level,km,-0.00744,0.0111,,,,,,medium,"Walking distance to Yuelu Mountain National Forest Park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.744,1.11,100*b/1 (X per km->km),reported,,,,-0.6702702702702703,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c1,4,1,10,D.NWG,green_space,E_environment,level,km,-0.0121,0.0017,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,IV,,0.531,se,Conditional mean (spatial 2SLS with spatial lag WlnP instrumented),semi_elasticity,-1.21,0.16999999999999998,100*b/1 (X per km->km),reported,,,,-7.11764705882353,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,iv,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c2,4,2,10,D.NWG,green_space,E_environment,level,km,0.0043,0.0032,,,,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.335,se,Quantile 0.1 (spatial quantile regression with instrumented spatial lag),semi_elasticity,0.43,0.32,100*b/1 (X per km->km),reported,,,,1.34375,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c3,4,3,10,D.NWG,green_space,E_environment,level,km,-0.005,0.0034,,,,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.311,se,Quantile 0.2 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.5,0.33999999999999997,100*b/1 (X per km->km),reported,,,,-1.4705882352941178,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c4,4,4,10,D.NWG,green_space,E_environment,level,km,-0.0082,0.0025,,,**,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.329,se,Quantile 0.3 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.8200000000000001,0.25,100*b/1 (X per km->km),reported,,,,-3.2800000000000002,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c5,4,5,10,D.NWG,green_space,E_environment,level,km,-0.0091,0.0014,,,**,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.352,se,Quantile 0.4 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.91,0.13999999999999999,100*b/1 (X per km->km),reported,,,,-6.5,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c6,4,6,10,D.NWG,green_space,E_environment,level,km,-0.0155,0.0018,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.341,se,Quantile 0.5 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.55,0.18,100*b/1 (X per km->km),reported,,,,-8.61111111111111,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c7,4,7,10,D.NWG,green_space,E_environment,level,km,-0.0164,0.0021,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.367,se,Quantile 0.6 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.6400000000000001,0.21,100*b/1 (X per km->km),reported,,,,-7.809523809523811,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c8,4,8,10,D.NWG,green_space,E_environment,level,km,-0.0183,0.0022,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.339,se,Quantile 0.7 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.83,0.22,100*b/1 (X per km->km),reported,,,,-8.318181818181818,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c9,4,9,10,D.NWG,green_space,E_environment,level,km,-0.0114,0.003,,,***,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.361,se,Quantile 0.8 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-1.1400000000000001,0.3,100*b/1 (X per km->km),reported,,,,-3.8000000000000003,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178,6c554bbc30f053c6546ae8df71b70b126d3f4178:T4-c10,4,10,10,D.NWG,green_space,E_environment,level,km,-0.00907,0.0301,,,,,,medium,"Walking distance to nearest non-water green space park, km. Bracketed values are not defined in the table note (only star legend ***p<0.01, **p<0.05, *p<0.10); magnitudes are consistent with standard errors and are recorded as SE with medium confidence.","ln property price (per m2, RMB; inferred from text)",log,quantile,,0.353,se,Quantile 0.9 (spatial quantile regression with instrumented spatial lag),semi_elasticity,-0.907,3.01,100*b/1 (X per km->km),reported,,,,-0.30132890365448506,,km,,2021.0,China,Asia,Upper middle income,2019.0,2019.0,condo_apartment,transaction,journal,False,False,unknown,,2019.0,quantile,journal,True,False,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c1,5,1,7,lnroom,bedrooms,A_structural,log,count,0.766,,113.44,,***,,,high,"Log number of rooms in the house (all rooms, not only bedrooms); stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,All transactions; mall proximity = ln distance to nearest mall,elasticity,0.766,0.0067524682651622005,b (log-log),|b/t|,0.7474548956486194,0.006588988854448337,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),113.44,10165.0,count,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,True
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c2,5,2,7,lnroom,bedrooms,A_structural,log,count,0.764,,113.22,,***,,,high,"Log number of rooms in the house (all rooms, not only bedrooms); stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.686,t,All transactions; mall proximity = number of malls within 3 km,elasticity,0.764,0.006747924394983219,b (log-log),|b/t|,0.7468141399751687,0.006596132661854519,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),113.22,10165.0,count,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c3,5,3,7,lnroom,bedrooms,A_structural,log,count,0.765,,113.23,,***,,,high,"Log number of rooms in the house (all rooms, not only bedrooms); stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,"All transactions; mall proximity = binary indicators within 500 m, 800 m and 1 km",elasticity,0.765,0.006756160028261062,b (log-log),|b/t|,0.7468433104459178,0.006595807740403759,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),113.23,10165.0,count,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c1,5,1,7,lnsize,living_area,A_structural,log,m2,0.0309,,11.21,,***,,,high,"Log residential building area in square metres; stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,All transactions; mall proximity = ln distance to nearest mall,elasticity,0.0309,0.0027564674397859055,b (log-log),|b/t|,0.11050550442300827,0.009857761322302252,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.21,10165.0,m2,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c2,5,2,7,lnsize,living_area,A_structural,log,m2,0.0308,,11.18,,***,,,high,"Log residential building area in square metres; stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.686,t,All transactions; mall proximity = number of malls within 3 km,elasticity,0.0308,0.0027549194991055457,b (log-log),|b/t|,0.11021336860715875,0.009858083059674307,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.18,10165.0,m2,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c3,5,3,7,lnsize,living_area,A_structural,log,m2,0.031,,11.26,,***,,,high,"Log residential building area in square metres; stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,"All transactions; mall proximity = binary indicators within 500 m, 800 m and 1 km",elasticity,0.031,0.002753108348134991,b (log-log),|b/t|,0.11099233377015312,0.00985722324779335,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.26,10165.0,m2,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c1,5,1,7,lntfloors,storeys,A_structural,log,count,0.124,,23.33,,***,,,high,"Log total number of floors of the building (excluding ground floor); stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,All transactions; mall proximity = ln distance to nearest mall,elasticity,0.124,0.005315045006429491,b (log-log),|b/t|,0.22544178869138676,0.009663171396973286,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.33,10165.0,count,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c2,5,2,7,lntfloors,storeys,A_structural,log,count,0.118,,22.23,,***,,,high,"Log total number of floors of the building (excluding ground floor); stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.686,t,All transactions; mall proximity = number of malls within 3 km,elasticity,0.118,0.005308142150247413,b (log-log),|b/t|,0.2153166971176818,0.009685861318834088,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.23,10165.0,count,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c3,5,3,7,lntfloors,storeys,A_structural,log,count,0.118,,22.14,,***,,,high,"Log total number of floors of the building (excluding ground floor); stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,"All transactions; mall proximity = binary indicators within 500 m, 800 m and 1 km",elasticity,0.118,0.005329719963866305,b (log-log),|b/t|,0.21448515019237782,0.009687676160450668,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.14,10165.0,count,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c1,5,1,7,lnbage,age,A_structural,log,years,-0.191,,-30.31,,***,,,high,"Log building age in years (built 2021 = 1 year); stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,All transactions; mall proximity = ln distance to nearest mall,elasticity,-0.191,0.006301550643352029,b (log-log),|b/t|,-0.2879013037811516,0.009498558356356039,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.31,10165.0,years,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c2,5,2,7,lnbage,age,A_structural,log,years,-0.199,,-31.88,,***,,,high,"Log building age in years (built 2021 = 1 year); stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.686,t,All transactions; mall proximity = number of malls within 3 km,elasticity,-0.199,0.006242158092848181,b (log-log),|b/t|,-0.3014890162376341,0.009456995490515497,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.88,10165.0,years,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c3,5,3,7,lnbage,age,A_structural,log,years,-0.198,,-31.08,,***,,,high,"Log building age in years (built 2021 = 1 year); stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,"All transactions; mall proximity = binary indicators within 500 m, 800 m and 1 km",elasticity,-0.198,0.006370656370656372,b (log-log),|b/t|,-0.2945876759634679,0.00947836795249253,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.08,10165.0,years,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c1,5,1,8,subway,transit_distance,D_location,dummy,binary,0.0124,,2.04,,*,,,high,"1 if a subway station within 1 km of the community; stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,All transactions; mall proximity = ln distance to nearest mall,pct_premium,1.2458494767417339,0.6154273168922415,100*(exp(b - se^2/2) - 1),|b/t|,0.02022961385564631,0.009916477380218778,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.04,10165.0,binary,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c2,5,2,8,subway,transit_distance,D_location,dummy,binary,0.0123,,2.04,,*,,,high,"1 if a subway station within 1 km of the community; stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.686,t,All transactions; mall proximity = number of malls within 3 km,pct_premium,1.2357554408119364,0.6104031500017993,100*(exp(b - se^2/2) - 1),|b/t|,0.02022961385564631,0.009916477380218778,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.04,10165.0,binary,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c3,5,3,8,subway,transit_distance,D_location,dummy,binary,0.012,,1.99,,*,,,high,"1 if a subway station within 1 km of the community; stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,"All transactions; mall proximity = binary indicators within 500 m, 800 m and 1 km",pct_premium,1.2053888183677808,0.6102948475574338,100*(exp(b - se^2/2) - 1),|b/t|,0.01973398550018569,0.009916575628234016,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.99,10165.0,binary,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c1,5,1,8,lncbd2,cbd_distance,D_location,log,km,-0.0487,,-11.28,,***,,,high,"Log Euclidean distance (km) from community to Saigao New Block (Weiyang District CBD); stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,All transactions; mall proximity = ln distance to nearest mall,elasticity,-0.0487,0.004317375886524823,b (log-log),|b/t|,-0.11118704315909769,0.009857007372260434,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.28,10165.0,km,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c2,5,2,8,lncbd2,cbd_distance,D_location,log,km,-0.0413,,-8.07,,***,,,high,"Log Euclidean distance (km) from community to Saigao New Block (Weiyang District CBD); stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.686,t,All transactions; mall proximity = number of malls within 3 km,elasticity,-0.0413,0.0051177199504337054,b (log-log),|b/t|,-0.07978717100904319,0.009886886122558015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.07,10165.0,km,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c3,5,3,8,lncbd2,cbd_distance,D_location,log,km,-0.0684,,-17.63,,***,,,high,"Log Euclidean distance (km) from community to Saigao New Block (Weiyang District CBD); stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,"All transactions; mall proximity = binary indicators within 500 m, 800 m and 1 km",elasticity,-0.0684,0.0038797504254112314,b (log-log),|b/t|,-0.17224965580750795,0.009770258412223936,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.63,10165.0,km,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c1,5,1,8,lndshop,commercial_distance,D_location,log,km,-0.0239,,-5.63,,***,,,high,"Log Euclidean distance (km) to nearest shopping mall; stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,All transactions; mall proximity = ln distance to nearest mall,elasticity,-0.0239,0.004245115452930728,b (log-log),|b/t|,-0.05575433495662941,0.009903079033149097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.63,10165.0,km,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c3,5,3,8,bshop500m,commercial_distance,D_location,dummy,binary,-0.0393,,-3.86,,***,,,high,"1 if a shopping mall within 500 m; stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,"All transactions; mall proximity = binary indicators within 500 m, 800 m and 1 km",pct_premium,-3.858760400595085,0.9788980707066692,100*(exp(b - se^2/2) - 1),|b/t|,-0.03825740929867575,0.009911245932299417,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.86,10165.0,binary,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c3,5,3,8,bshop800m,commercial_distance,D_location,dummy,binary,0.0553,,5.01,,***,,,high,"1 if a shopping mall within 800 m; stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,"All transactions; mall proximity = binary indicators within 500 m, 800 m and 1 km",pct_premium,5.679324483893056,1.1665514297368575,100*(exp(b - se^2/2) - 1),|b/t|,0.04963048288821304,0.00990628400962336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.01,10165.0,binary,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3,6e83e47fe67686f424f9c68dca8dac1370a653d3:T5-c3,5,3,8,bshop1km,commercial_distance,D_location,dummy,binary,-0.0334,,-3.74,,***,,,high,"1 if a shopping mall within 1 km; stars: * p<0.05, ** p<0.01, *** p<0.001",ln total transaction price (tprice),log,OLS,10175.0,0.685,t,"All transactions; mall proximity = binary indicators within 500 m, 800 m and 1 km",pct_premium,-3.2886944534556095,0.8637129454555059,100*(exp(b - se^2/2) - 1),|b/t|,-0.03706972033078823,0.009911689928018242,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.74,10165.0,binary,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,conference,False,False,unknown,,2019.0,ols,other,True,True,False
6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620:T6-c1,6,1,15,Building age,age,A_structural,level,years,-0.009,,-87.388,0.001,***,,,high,p printed as <0.001,log of housing unit price (per ping),log,OLS,108671.0,0.533,t,"Full sample, baseline; t values and p values printed in separate columns (classical SE)",semi_elasticity,-0.8999999999999999,0.010298896873712635,100*b/1 (per year),|b/t|,-0.2562514355403295,0.0029323412315229716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-87.388,108661.0,years,,2026.0,Taiwan,Asia,High income,2021.0,2024.0,mixed,transaction,journal,True,True,robust,,2022.5,ols,journal,True,True,False
6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620:T6-c1,6,1,15,Floor area,living_area,A_structural,level,ping (1 ping = 3.306 m2),-0.001,,-19.028,0.001,***,,,high,"Dependent variable is price per ping, so this is the effect of size on unit price; p printed as <0.001",log of housing unit price (per ping),log,OLS,108671.0,0.533,t,"Full sample, baseline; t values and p values printed in separate columns (classical SE)",semi_elasticity,-0.03024986387561256,0.0015897553014301326,100*b/3.3058 (X per pyeong->m2),|b/t|,-0.0576280533450121,0.0030285922506312858,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-19.028,108661.0,pyeong,,2026.0,Taiwan,Asia,High income,2021.0,2024.0,mixed,transaction,journal,True,True,robust,,2022.5,ols,journal,True,True,True
6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620:T6-c1,6,1,15,Floor level,floor_level,A_structural,level,count,0.006,,32.799,0.001,***,,,high,p printed as <0.001,log of housing unit price (per ping),log,OLS,108671.0,0.533,t,"Full sample, baseline; t values and p values printed in separate columns (classical SE)",semi_elasticity,0.6,0.018293240647580717,100*b/1 (per unit count),|b/t|,0.09901124183364539,0.0030187274561311443,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.799,108661.0,count,,2026.0,Taiwan,Asia,High income,2021.0,2024.0,mixed,transaction,journal,True,True,robust,,2022.5,ols,journal,True,True,False
6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620:T6-c1,6,1,15,Has parking,parking,A_structural,binary,binary,-0.08,,-30.929,0.001,***,,,high,p printed as <0.001,log of housing unit price (per ping),log,OLS,108671.0,0.533,t,"Full sample, baseline; t values and p values printed in separate columns (classical SE)",pct_premium,-7.688674158950592,0.23877043457897398,100*(exp(b - se^2/2) - 1),|b/t|,-0.09341695949647111,0.0030203679231941257,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.929,108661.0,binary,,2026.0,Taiwan,Asia,High income,2021.0,2024.0,mixed,transaction,journal,True,True,robust,,2022.5,ols,journal,True,True,False
6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620:T8-c1,8,1,17,Has parking,parking,A_structural,binary,binary,-0.015,0.009,,,*,,,high,HC1 robust SE,log of housing unit price (per ping),log,OLS,27708.0,0.591,se,Small units (< 25 ping); HC1 robust SE,pct_premium,-1.492795662258728,0.8866007456427563,100*(exp(b - se^2/2) - 1),reported,-0.010013888881664363,0.006008333328998618,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6666666666666667,27698.0,binary,,2026.0,Taiwan,Asia,High income,2021.0,2024.0,mixed,transaction,journal,True,True,robust,,2022.5,ols,journal,True,True,False
6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620:T8-c2,8,2,17,Has parking,parking,A_structural,binary,binary,-0.076,0.003,,,***,,,high,HC1 robust SE,log of housing unit price (per ping),log,OLS,80963.0,0.526,se,Large units (>= 25 ping); HC1 robust SE,pct_premium,-7.318796410416328,0.27804486196781464,100*(exp(b - se^2/2) - 1),reported,-0.08868724326235537,0.0035008122340403442,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-25.333333333333332,80953.0,binary,,2026.0,Taiwan,Asia,High income,2021.0,2024.0,mixed,transaction,journal,True,True,robust,,2022.5,ols,journal,True,True,False
6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620:T6-c1,6,1,15,Elevator building,accessibility,B_interior,binary,binary,0.15,,33.041,0.001,***,,,high,Elevator building vs walk-up apartment; p printed as <0.001,log of housing unit price (per ping),log,OLS,108671.0,0.533,t,"Full sample, baseline; t values and p values printed in separate columns (classical SE)",pct_premium,16.182227013881413,0.5274511558646604,100*(exp(b - se^2/2) - 1),|b/t|,0.09973453364074052,0.003018508327252218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.041,108661.0,binary,,2026.0,Taiwan,Asia,High income,2021.0,2024.0,mixed,transaction,journal,True,True,robust,,2022.5,ols,journal,True,True,True
6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620:T8-c1,8,1,17,Elevator building,accessibility,B_interior,binary,binary,0.13,0.013,,,***,,,high,Elevator building vs walk-up apartment; HC1 robust SE,log of housing unit price (per ping),log,OLS,27708.0,0.591,se,Small units (< 25 ping); HC1 robust SE,pct_premium,13.87321563918762,1.4804768983220082,100*(exp(b - se^2/2) - 1),reported,0.059978171917410325,0.005997817191741033,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.0,27698.0,binary,,2026.0,Taiwan,Asia,High income,2021.0,2024.0,mixed,transaction,journal,True,True,robust,,2022.5,ols,journal,True,True,False
6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620,6edd1ccf2791c69eb6ab0393c5323dfff21ae620:T8-c2,8,2,17,Elevator building,accessibility,B_interior,binary,binary,0.149,0.006,,,***,,,high,Elevator building vs walk-up apartment; HC1 robust SE,log of housing unit price (per ping),log,OLS,80963.0,0.526,se,Large units (>= 25 ping); HC1 robust SE,pct_premium,16.065209728330764,0.6964037935254512,100*(exp(b - se^2/2) - 1),reported,0.08695020300420381,0.0035013504565451206,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.833333333333332,80953.0,binary,,2026.0,Taiwan,Asia,High income,2021.0,2024.0,mixed,transaction,journal,True,True,robust,,2022.5,ols,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Higher net residential density,density,F_neighbourhood,log,per_km2,-0.003,0.001,,,***,,,high,"ln(1+net residential density per km2) at census-tract level; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,-0.003,0.001,b (log-log),reported,-0.011236033862680541,0.0037453446208935135,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Higher net residential density,density,F_neighbourhood,log,per_km2,-0.01,0.001,,,***,,,high,"ln(1+net residential density per km2) at census-tract level; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,-0.01,0.001,b (log-log),reported,-0.04953713264795739,0.0049537132647957385,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.0,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Higher net residential density,density,F_neighbourhood,log,per_km2,-0.004,0.001,,,**,,,high,"ln(1+net residential density per km2) at census-tract level; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,-0.004,0.001,b (log-log),reported,-0.02285378499664151,0.005713446249160378,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Higher net residential density,density,F_neighbourhood,log,per_km2,0.001,0.001,,,,,,high,"ln(1+net residential density per km2) at census-tract level; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.001,0.001,b (log-log),reported,0.0037455547914624562,0.0037455547914624562,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Higher net residential density,density,F_neighbourhood,log,per_km2,-0.009,0.001,,,***,,,high,"ln(1+net residential density per km2) at census-tract level; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,-0.009,0.001,b (log-log),reported,-0.033691092088245736,0.003743454676471749,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Higher intersection density,walkability,D_location,log,per_km2,-0.006,0.003,,,,,,high,"ln(1+four-way intersection density per km2) within 1,200 m network buffer; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,-0.006,0.003,b (log-log),reported,-0.007490951946705858,0.0037454759733529294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Higher intersection density,walkability,D_location,log,per_km2,0.001,0.004,,,,,,high,"ln(1+four-way intersection density per km2) within 1,200 m network buffer; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.001,0.004,b (log-log),reported,0.0012399496719601717,0.004959798687840687,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.25,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Higher intersection density,walkability,D_location,log,per_km2,-0.099,0.004,,,***,,,high,"ln(1+four-way intersection density per km2) within 1,200 m network buffer; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,-0.099,0.004,b (log-log),reported,-0.14005070521928892,0.005658614352294503,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-24.75,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Higher intersection density,walkability,D_location,log,per_km2,-0.006,0.003,,,,,,high,"ln(1+four-way intersection density per km2) within 1,200 m network buffer; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,-0.006,0.003,b (log-log),reported,-0.007490951946705858,0.0037454759733529294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Higher intersection density,walkability,D_location,log,per_km2,-0.01,0.004,,,**,,,high,"ln(1+four-way intersection density per km2) within 1,200 m network buffer; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,-0.01,0.004,b (log-log),reported,-0.00936354215759,0.0037454168630360004,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Bars,neighbourhood_amenities,F_neighbourhood,log,per_km2,-0.077,0.003,,,***,,,high,"ln(1+density of bars per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,-0.077,0.003,b (log-log),reported,-0.09569537782958157,0.003728391344009672,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-25.666666666666664,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Bars,neighbourhood_amenities,F_neighbourhood,log,per_km2,-0.086,0.004,,,***,,,high,"ln(1+density of bars per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,-0.086,0.004,b (log-log),reported,-0.1060345885156302,0.004931841326308382,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.499999999999996,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Bars,neighbourhood_amenities,F_neighbourhood,log,per_km2,-0.049,0.003,,,***,,,high,"ln(1+density of bars per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,-0.049,0.003,b (log-log),reported,-0.09293998218256713,0.005690202990769416,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.333333333333332,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Bars,neighbourhood_amenities,F_neighbourhood,log,per_km2,-0.068,0.002,,,***,,,high,"ln(1+density of bars per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,-0.068,0.002,b (log-log),reported,-0.12632947311258536,0.0037155727386054523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-34.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Bars,neighbourhood_amenities,F_neighbourhood,log,per_km2,-0.087,0.003,,,***,,,high,"ln(1+density of bars per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,-0.087,0.003,b (log-log),reported,-0.10798666748707428,0.0037236781892094587,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-28.999999999999996,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Cafés,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.104,0.003,,,***,,,high,"ln(1+density of cafés per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.104,0.003,b (log-log),reported,0.12876583904177072,0.0037143992031280024,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.666666666666664,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Cafés,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.095,0.004,,,***,,,high,"ln(1+density of cafés per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.095,0.004,b (log-log),reported,0.11698646892201965,0.0049257460598745115,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.75,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Cafés,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.104,0.004,,,***,,,high,"ln(1+density of cafés per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.104,0.004,b (log-log),reported,0.1469747766399546,0.005652876024613639,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.0,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Cafés,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.082,0.003,,,***,,,high,"ln(1+density of cafés per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.082,0.003,b (log-log),reported,0.1018468530483572,0.003726104379817946,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.333333333333332,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Cafés,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.148,0.004,,,***,,,high,"ln(1+density of cafés per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.148,0.004,b (log-log),reported,0.13727450701569202,0.0037101218112349193,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Restaurants,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.014,0.004,,,***,,,high,"ln(1+density of restaurants per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.014,0.004,b (log-log),reported,0.01310840737221821,0.0037452592492052033,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Restaurants,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.048,0.006,,,***,,,high,"ln(1+density of restaurants per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.048,0.006,b (log-log),reported,0.039647222441540515,0.004955902805192565,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Restaurants,neighbourhood_amenities,F_neighbourhood,log,per_km2,-0.006,0.004,,,,,,high,"ln(1+density of restaurants per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,-0.006,0.004,b (log-log),reported,-0.00857209337179556,0.005714728914530375,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Restaurants,neighbourhood_amenities,F_neighbourhood,log,per_km2,-0.001,0.003,,,,,,high,"ln(1+density of restaurants per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,-0.001,0.003,b (log-log),reported,-0.001248526048643995,0.003745578145931986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3333333333333333,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Restaurants,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.019,0.005,,,***,,,high,"ln(1+density of restaurants per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.019,0.005,b (log-log),reported,0.014231766555431718,0.0037452017251136103,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Hobby classes,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.032,0.003,,,***,,,high,"ln(1+density of hobby classes per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.032,0.003,b (log-log),reported,0.0399210158112802,0.0037425952323075187,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.666666666666666,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Hobby classes,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.074,0.004,,,***,,,high,"ln(1+density of hobby classes per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.074,0.004,b (log-log),reported,0.0913725095172389,0.0049390545684994,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.5,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Hobby classes,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.018,0.004,,,***,,,high,"ln(1+density of hobby classes per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.018,0.004,b (log-log),reported,0.02570872483645304,0.005713049963656231,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Hobby classes,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.028,0.003,,,***,,,high,"ln(1+density of hobby classes per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.028,0.003,b (log-log),reported,0.0349374143646734,0.0037432943962150077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.333333333333334,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Hobby classes,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.045,0.003,,,***,,,high,"ln(1+density of hobby classes per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.045,0.003,b (log-log),reported,0.05609525032454107,0.0037396833549694047,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Cultural institutions,neighbourhood_amenities,F_neighbourhood,log,per_km2,-0.06,0.003,,,***,,,high,"ln(1+density of cultural institutions per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,-0.06,0.003,b (log-log),reported,-0.0747023091671727,0.0037351154583586343,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-20.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Cultural institutions,neighbourhood_amenities,F_neighbourhood,log,per_km2,-0.05,0.004,,,***,,,high,"ln(1+density of cultural institutions per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,-0.05,0.004,b (log-log),reported,-0.06187872387696933,0.004950297910157547,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.5,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Cultural institutions,neighbourhood_amenities,F_neighbourhood,log,per_km2,-0.029,0.004,,,***,,,high,"ln(1+density of cultural institutions per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,-0.029,0.004,b (log-log),reported,-0.04139778798872427,0.005710039722582658,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.25,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Cultural institutions,neighbourhood_amenities,F_neighbourhood,log,per_km2,-0.04,0.003,,,***,,,high,"ln(1+density of cultural institutions per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,-0.04,0.003,b (log-log),reported,-0.049878917813824294,0.003740918836036822,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.333333333333334,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Cultural institutions,neighbourhood_amenities,F_neighbourhood,log,per_km2,-0.081,0.004,,,***,,,high,"ln(1+density of cultural institutions per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,-0.081,0.004,b (log-log),reported,-0.07563077958708246,0.0037348533129423437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-20.25,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Parks,green_space,E_environment,log,per_km2,0.052,0.005,,,***,,,high,"ln(1+density of parks per km2) within 1,200 m; density not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.052,0.005,b (log-log),reported,0.038924521898753096,0.0037427424902647215,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.399999999999999,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Parks,green_space,E_environment,log,per_km2,0.023,0.005,,,***,,,high,"ln(1+density of parks per km2) within 1,200 m; density not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.023,0.005,b (log-log),reported,0.022809155868500495,0.004958512145326195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.6,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Parks,green_space,E_environment,log,per_km2,0.043,0.011,,,***,,,high,"ln(1+density of parks per km2) within 1,200 m; density not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.043,0.011,b (log-log),reported,0.02233464290105564,0.005713513300270048,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.909090909090909,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Parks,green_space,E_environment,log,per_km2,0.057,0.004,,,***,,,high,"ln(1+density of parks per km2) within 1,200 m; density not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.057,0.004,b (log-log),reported,0.053298664477777986,0.0037402571563352974,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.25,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Parks,green_space,E_environment,log,per_km2,0.047,0.006,,,***,,,high,"ln(1+density of parks per km2) within 1,200 m; density not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.047,0.006,b (log-log),reported,0.02932776420384673,0.003743969898363412,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.833333333333333,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Gyms and fitness clubs,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.063,0.003,,,***,,,high,"ln(1+density of gyms per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.063,0.003,b (log-log),reported,0.07841500135341449,0.0037340476834959277,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Gyms and fitness clubs,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.07,0.003,,,***,,,high,"ln(1+density of gyms per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.07,0.003,b (log-log),reported,0.114961438371154,0.004926918787335171,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.333333333333336,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Gyms and fitness clubs,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.045,0.003,,,***,,,high,"ln(1+density of gyms per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.045,0.003,b (log-log),reported,0.08541083194193988,0.0056940554627959925,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.0,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Gyms and fitness clubs,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.043,0.003,,,***,,,high,"ln(1+density of gyms per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.043,0.003,b (log-log),reported,0.0536094593871932,0.0037401948409669676,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.333333333333332,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Gyms and fitness clubs,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.082,0.003,,,***,,,high,"ln(1+density of gyms per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.082,0.003,b (log-log),reported,0.1018468530483572,0.003726104379817946,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.333333333333332,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Convenience stores,commercial_distance,D_location,log,per_km2,0.092,0.004,,,***,,,high,"ln(1+density of convenience stores per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.092,0.004,b (log-log),reported,0.085830456141314,0.003731758962665826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Convenience stores,commercial_distance,D_location,log,per_km2,0.067,0.006,,,***,,,high,"ln(1+density of convenience stores per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.067,0.006,b (log-log),reported,0.05529971196396517,0.004952213011698373,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.166666666666668,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Convenience stores,commercial_distance,D_location,log,per_km2,0.05,0.005,,,***,,,high,"ln(1+density of convenience stores per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.05,0.005,b (log-log),reported,0.05705629040480525,0.005705629040480525,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.0,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Convenience stores,commercial_distance,D_location,log,per_km2,0.108,0.004,,,***,,,high,"ln(1+density of convenience stores per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.108,0.004,b (log-log),reported,0.10061746928335115,0.003726572936420413,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,True
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Convenience stores,commercial_distance,D_location,log,per_km2,0.094,0.005,,,***,,,high,"ln(1+density of convenience stores per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.094,0.005,b (log-log),reported,0.07024298793317335,0.0037363291453815606,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.8,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Schools,school_distance,D_location,log,per_km2,0.144,0.004,,,***,,,high,"ln(1+density of schools per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.144,0.004,b (log-log),reported,0.13363154159114599,0.003711987266420722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),36.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Schools,school_distance,D_location,log,per_km2,0.099,0.005,,,***,,,high,"ln(1+density of schools per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.099,0.005,b (log-log),reported,0.0977339451215354,0.00493605783442098,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.8,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Schools,school_distance,D_location,log,per_km2,0.114,0.005,,,***,,,high,"ln(1+density of schools per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.114,0.005,b (log-log),reported,0.12920835746685017,0.005667033222230271,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.8,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Schools,school_distance,D_location,log,per_km2,0.167,0.004,,,***,,,high,"ln(1+density of schools per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.167,0.004,b (log-log),reported,0.15450033738090313,0.0037006068833749257,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),41.75,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,True
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Schools,school_distance,D_location,log,per_km2,0.142,0.004,,,***,,,high,"ln(1+density of schools per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.142,0.004,b (log-log),reported,0.13180801586701318,0.0037129018554088226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.49999999999999,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Childcare facilities,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.063,0.003,,,***,,,high,"ln(1+density of childcare facilities per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.063,0.003,b (log-log),reported,0.07841500135341449,0.0037340476834959277,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Childcare facilities,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.052,0.005,,,***,,,high,"ln(1+density of childcare facilities per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.052,0.005,b (log-log),reported,0.05151346067186511,0.004953217372294723,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.399999999999999,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Childcare facilities,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.059,0.004,,,***,,,high,"ln(1+density of childcare facilities per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.059,0.004,b (log-log),reported,0.08399744628480181,0.005694742121003513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.749999999999998,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Childcare facilities,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.048,0.003,,,***,,,high,"ln(1+density of childcare facilities per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.048,0.003,b (log-log),reported,0.05982196741164862,0.0037388729632280384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Childcare facilities,neighbourhood_amenities,F_neighbourhood,log,per_km2,0.059,0.004,,,***,,,high,"ln(1+density of childcare facilities per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.059,0.004,b (log-log),reported,0.05516319846486195,0.0037398778620245394,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.749999999999998,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Retail shops,commercial_distance,D_location,log,per_km2,0.036,0.003,,,***,,,high,"ln(1+density of retail shops per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.036,0.003,b (log-log),reported,0.04490163983939006,0.003741803319949172,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.999999999999998,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Retail shops,commercial_distance,D_location,log,per_km2,0.042,0.003,,,***,,,high,"ln(1+density of retail shops per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.042,0.003,b (log-log),reported,0.06927044107629034,0.004947888648306453,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.0,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Retail shops,commercial_distance,D_location,log,per_km2,0.015,0.003,,,***,,,high,"ln(1+density of retail shops per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.015,0.003,b (log-log),reported,0.028563035769473815,0.005712607153894763,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Retail shops,commercial_distance,D_location,log,per_km2,0.033,0.003,,,***,,,high,"ln(1+density of retail shops per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.033,0.003,b (log-log),reported,0.04116646537108159,0.0037424059428255987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Retail shops,commercial_distance,D_location,log,per_km2,0.035,0.003,,,***,,,high,"ln(1+density of retail shops per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.035,0.003,b (log-log),reported,0.04365678314529263,0.0037420099838822245,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.666666666666668,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Welfare facilities for older adults,public_services,F_neighbourhood,log,per_km2,0.02,0.003,,,***,,,high,"ln(1+density of welfare facilities for older adults per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.02,0.003,b (log-log),reported,0.02496275915964519,0.003744413873946778,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.666666666666667,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Welfare facilities for older adults,public_services,F_neighbourhood,log,per_km2,0.012,0.004,,,**,,,high,"ln(1+density of welfare facilities for older adults per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.012,0.004,b (log-log),reported,0.014877760648974864,0.004959253549658288,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Welfare facilities for older adults,public_services,F_neighbourhood,log,per_km2,0.005,0.003,,,***,,,high,"ln(1+density of welfare facilities for older adults per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.005,0.003,b (log-log),reported,0.009524466108276916,0.005714679664966149,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6666666666666667,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Welfare facilities for older adults,public_services,F_neighbourhood,log,per_km2,0.028,0.003,,,***,,,high,"ln(1+density of welfare facilities for older adults per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.028,0.003,b (log-log),reported,0.0349374143646734,0.0037432943962150077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.333333333333334,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Welfare facilities for older adults,public_services,F_neighbourhood,log,per_km2,0.015,0.003,,,***,,,high,"ln(1+density of welfare facilities for older adults per km2) within 1,200 m; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.015,0.003,b (log-log),reported,0.01872462192935807,0.0037449243858716135,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Hospitals,hospital_distance,D_location,log,per_km2,0.028,0.005,,,***,,,high,"ln(1+density of hospitals per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.028,0.005,b (log-log),reported,0.020970641337717085,0.0037447573817351943,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.6,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Hospitals,hospital_distance,D_location,log,per_km2,0.017,0.006,,,**,,,high,"ln(1+density of hospitals per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.017,0.006,b (log-log),reported,0.014051386383218874,0.0049593128411360736,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8333333333333335,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Hospitals,hospital_distance,D_location,log,per_km2,0.021,0.006,,,***,,,high,"ln(1+density of hospitals per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.021,0.006,b (log-log),reported,0.019998285934662397,0.0057137959813321135,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Hospitals,hospital_distance,D_location,log,per_km2,0.018,0.004,,,***,,,high,"ln(1+density of hospitals per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.018,0.004,b (log-log),reported,0.016852721077709756,0.0037450491283799454,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Hospitals,hospital_distance,D_location,log,per_km2,0.073,0.006,,,***,,,high,"ln(1+density of hospitals per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.073,0.006,b (log-log),reported,0.045523990120411695,0.0037416978181160298,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.166666666666666,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,True
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Pharmacies,commercial_distance,D_location,log,per_km2,0.01,0.004,,,**,,,high,"ln(1+density of pharmacies per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.01,0.004,b (log-log),reported,0.00936354215759,0.0037454168630360004,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Pharmacies,commercial_distance,D_location,log,per_km2,-0.016,0.005,,,***,,,high,"ln(1+density of pharmacies per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,-0.016,0.005,b (log-log),reported,-0.015869369378237533,0.004959177930699229,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Pharmacies,commercial_distance,D_location,log,per_km2,0.037,0.004,,,***,,,high,"ln(1+density of pharmacies per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.037,0.004,b (log-log),reported,0.052789475643591606,0.0057069703398477415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.25,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Pharmacies,commercial_distance,D_location,log,per_km2,0.029,0.004,,,***,,,high,"ln(1+density of pharmacies per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.029,0.004,b (log-log),reported,0.027145455778165198,0.003744200796988303,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.25,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Pharmacies,commercial_distance,D_location,log,per_km2,-0.029,0.005,,,***,,,high,"ln(1+density of pharmacies per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,-0.029,0.005,b (log-log),reported,-0.02171924560305469,0.00374469751776805,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.8,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Bus stops,transit_distance,D_location,log,per_km2,0.029,0.003,,,***,,,high,"ln(1+density of bus stops per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.029,0.003,b (log-log),reported,0.03618357365664109,0.0037431283093076993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.666666666666666,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Bus stops,transit_distance,D_location,log,per_km2,-0.004,0.005,,,,,,high,"ln(1+density of bus stops per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,-0.004,0.005,b (log-log),reported,-0.003967810766475637,0.004959763458094546,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Bus stops,transit_distance,D_location,log,per_km2,0.122,0.004,,,***,,,high,"ln(1+density of bus stops per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.122,0.004,b (log-log),reported,0.17171656903082813,0.005630051443633709,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.5,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Bus stops,transit_distance,D_location,log,per_km2,0.061,0.004,,,***,,,high,"ln(1+density of bus stops per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.061,0.004,b (log-log),reported,0.057027155552538636,0.0037394856100025336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.25,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Bus stops,transit_distance,D_location,log,per_km2,0.03,0.004,,,***,,,high,"ln(1+density of bus stops per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.03,0.004,b (log-log),reported,0.02808078016589886,0.0037441040221198483,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.5,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,Facility density: Stations,transit_distance,D_location,log,per_km2,0.056,0.005,,,***,,,high,"ln(1+density of railway stations per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,elasticity,0.056,0.005,b (log-log),reported,0.041913643382590605,0.0037422895877313044,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.2,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,Facility density: Stations,transit_distance,D_location,log,per_km2,0.009,0.006,,,,,,high,"ln(1+density of railway stations per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,elasticity,0.009,0.006,b (log-log),reported,0.007439497868694415,0.004959665245796277,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4999999999999998,40651.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,Facility density: Stations,transit_distance,D_location,log,per_km2,0.0,0.006,,,,,,high,"ln(1+density of railway stations per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,elasticity,0.0,0.006,b (log-log),reported,0.0,0.005714938887484885,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0,30618.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,Facility density: Stations,transit_distance,D_location,log,per_km2,0.068,0.005,,,***,,,high,"ln(1+density of railway stations per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,elasticity,0.068,0.005,b (log-log),reported,0.050873939528383774,0.003740730847675277,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.600000000000001,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,Facility density: Stations,transit_distance,D_location,log,per_km2,0.062,0.006,,,***,,,high,"ln(1+density of railway stations per km2) within 1,200 m; density (access), not distance; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,elasticity,0.062,0.006,b (log-log),reported,0.03867538015741264,0.003742778724910901,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.333333333333334,71279.0,per_km2,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,"Maximum flooding depth (0.0, 3.0) m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.122,0.003,,,***,,,high,"Hazard-map maximum flooding depth between 0 and 3 m; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,pct_premium,-11.485561465606908,0.26554451055078815,100*(exp(b - se^2/2) - 1),reported,-0.1505834345976316,0.0037028713425647113,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-40.666666666666664,71279.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,"Maximum flooding depth (0.0, 3.0) m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.118,0.005,,,***,,,high,"Hazard-map maximum flooding depth between 0 and 3 m; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,pct_premium,-11.131505601661118,0.44434802630730874,100*(exp(b - se^2/2) - 1),reported,-0.11625762465350402,0.004926170536165424,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-23.599999999999998,40651.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,"Maximum flooding depth (0.0, 3.0) m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.028,0.004,,,***,,,high,"Hazard-map maximum flooding depth between 0 and 3 m; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,pct_premium,-2.761941227457121,0.38895534672049875,100*(exp(b - se^2/2) - 1),reported,-0.03997259960861241,0.005710371372658915,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,30618.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,"Maximum flooding depth (0.0, 3.0) m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.078,0.004,,,***,,,high,"Hazard-map maximum flooding depth between 0 and 3 m; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,pct_premium,-7.504297314227426,0.3699857706174157,100*(exp(b - se^2/2) - 1),reported,-0.0728447877364425,0.0037356301403303847,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-19.5,71279.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,"Maximum flooding depth (0.0, 3.0) m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.134,0.004,,,***,,,high,"Hazard-map maximum flooding depth between 0 and 3 m; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,pct_premium,-12.541693208919602,0.3498360258413336,100*(exp(b - se^2/2) - 1),reported,-0.12450069473675465,0.0037164386488583476,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-33.5,71279.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,"Maximum flooding depth [3.0, 5.0) m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.188,0.005,,,***,,,high,"Hazard-map maximum flooding depth 3-5 m; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,pct_premium,-17.139565038642456,0.4143073536163403,100*(exp(b - se^2/2) - 1),reported,-0.1394576252920635,0.0037089793960655183,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-37.6,71279.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,"Maximum flooding depth [3.0, 5.0) m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.248,0.005,,,***,,,high,"Hazard-map maximum flooding depth 3-5 m; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,pct_premium,-21.964981116029136,0.39017997163901713,100*(exp(b - se^2/2) - 1),reported,-0.23888386780369467,0.004816207012171263,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-49.6,40651.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,"Maximum flooding depth [3.0, 5.0) m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.006,0.005,,,,,,high,"Hazard-map maximum flooding depth 3-5 m; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,pct_premium,-0.5994461092958092,0.49700898202696764,100*(exp(b - se^2/2) - 1),reported,-0.006857765402553355,0.005714804502127796,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2,30618.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,"Maximum flooding depth [3.0, 5.0) m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.114,0.003,,,***,,,high,"Hazard-map maximum flooding depth 3-5 m; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,pct_premium,-10.774605926935909,0.26767738676472247,100*(exp(b - se^2/2) - 1),reported,-0.14091191060298913,0.0037082081737628714,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-38.0,71279.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,"Maximum flooding depth [3.0, 5.0) m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.189,0.006,,,***,,,high,"Hazard-map maximum flooding depth 3-5 m; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,pct_premium,-17.22283933282862,0.4966719040168402,100*(exp(b - se^2/2) - 1),reported,-0.11717305969369665,0.003719779672815767,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.5,71279.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-ca,3,a,11,"Maximum flooding depth [5.0, inf] m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.219,0.007,,,***,,,high,"Hazard-map maximum flooding depth 5 m or more; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.509,se,All samples (target area); 0.50 conditional quantile; pseudo R2,pct_premium,-19.66979629873733,0.5623252027075386,100*(exp(b - se^2/2) - 1),reported,-0.11638679788983075,0.0037201259599489284,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.285714285714285,71279.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cb,3,b,11,"Maximum flooding depth [5.0, inf] m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.213,0.007,,,***,,,high,"Hazard-map maximum flooding depth 5 m or more; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,40661.0,0.543,se,Central cities; 0.50 conditional quantile; pseudo R2,pct_premium,-19.186366236632757,0.565709296051542,100*(exp(b - se^2/2) - 1),reported,-0.1492297878632147,0.004904265328838042,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.428571428571427,40651.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T3-cc,3,c,11,"Maximum flooding depth [5.0, inf] m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.085,0.01,,,***,,,high,"Hazard-map maximum flooding depth 5 m or more; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,30628.0,0.463,se,Other (non-central) cities; 0.50 conditional quantile; pseudo R2,pct_premium,-8.153364006464148,0.9185122844014574,100*(exp(b - se^2/2) - 1),reported,-0.048519767668567894,0.0057082079610079875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.5,30618.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-ca,4,a,12,"Maximum flooding depth [5.0, inf] m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.113,0.005,,,***,,,high,"Hazard-map maximum flooding depth 5 m or more; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.437,se,All samples; 0.15 conditional quantile; pseudo R2,pct_premium,-10.686050419745886,0.44657533005800776,100*(exp(b - se^2/2) - 1),reported,-0.08434846594285564,0.0037322330063210454,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.6,71279.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937,7059eb726206d6598f1ef88ae9a43a35a98c6937:T4-cc,4,c,12,"Maximum flooding depth [5.0, inf] m (ref: 0.0 m)",flood_risk,E_environment,dummy,binary,-0.278,0.016,,,***,,,high,"Hazard-map maximum flooding depth 5 m or more; reference no flood risk; stars: * p<0.05, ** p<0.01, *** p<0.001",log sale price (JPY) of single-family detached house,log,quantile,71289.0,0.531,se,All samples; 0.85 conditional quantile; pseudo R2,pct_premium,-24.280010627530746,1.2116749144229368,100*(exp(b - se^2/2) - 1),reported,-0.06494209048152816,0.0037376742723181674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.375,71279.0,binary,,2023.0,Japan,Asia,High income,2015.0,2020.0,single_family,transaction,journal,True,False,unknown,,2017.5,quantile,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M1,3,Model 1,16,Area,living_area,A_structural,level,m2,0.0032,0.0008,,,***,,,high,Size of the property in m2,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,900.0,0.603,se,"Damascus Governorate districts (12 districts), property attributes + building war-damage dummies",semi_elasticity,0.32,0.08,100*b/1 (X per m2->m2),reported,0.13289109883701908,0.03322277470925477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,890.0,m2,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M2,3,Model 2,16,Area,living_area,A_structural,level,m2,0.0104,0.0011,,,***,,,high,Size of the property in m2,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,1511.0,0.474,se,"Rural Damascus Governorate districts (37 districts), property attributes + building war-damage dummies",semi_elasticity,1.04,0.11,100*b/1 (X per m2->m2),reported,0.23707679659554992,0.025075430409144703,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.454545454545453,1501.0,m2,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M1,3,Model 1,16,Age,age,A_structural,level,years,-0.0018,0.0025,,,,,,high,Age of property in years,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,900.0,0.603,se,"Damascus Governorate districts (12 districts), property attributes + building war-damage dummies",semi_elasticity,-0.18,0.25,100*b/1 (per year),reported,-0.024127429081618888,0.03351031816891512,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.72,890.0,years,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M2,3,Model 2,16,Age,age,A_structural,level,years,-0.004,0.002,,,*,,,high,Age of property in years,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,1511.0,0.474,se,"Rural Damascus Governorate districts (37 districts), property attributes + building war-damage dummies",semi_elasticity,-0.4,0.2,100*b/1 (per year),reported,-0.0515539262226467,0.025776963111323353,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,1501.0,years,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M1,3,Model 1,16,N_bed,bedrooms,A_structural,level,count,0.1361,0.0337,,,***,,,high,Number of bedrooms,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,900.0,0.603,se,"Damascus Governorate districts (12 districts), property attributes + building war-damage dummies",semi_elasticity,13.61,3.37,100*b/1 (per unit count),reported,0.13414973403878797,0.03321709064737072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0385756676557865,890.0,count,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M2,3,Model 2,16,N_bed,bedrooms,A_structural,level,count,-0.0201,0.0268,,,,,,high,Number of bedrooms,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,1511.0,0.474,se,"Rural Damascus Governorate districts (37 districts), property attributes + building war-damage dummies",semi_elasticity,-2.01,2.68,100*b/1 (per unit count),reported,-0.01935483870967742,0.025806451612903226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.75,1501.0,count,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M1,3,Model 1,16,N_bath,bathrooms,A_structural,level,count,0.06,0.053,,,,,,high,Number of bathrooms,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,900.0,0.603,se,"Damascus Governorate districts (12 districts), property attributes + building war-damage dummies",semi_elasticity,6.0,5.3,100*b/1 (per unit count),reported,0.03791996358471805,0.03349596783316761,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1320754716981132,890.0,count,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M2,3,Model 2,16,N_bath,bathrooms,A_structural,level,count,-0.0436,0.037,,,,,,high,Number of bathrooms,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,1511.0,0.474,se,"Rural Damascus Governorate districts (37 districts), property attributes + building war-damage dummies",semi_elasticity,-4.36,3.6999999999999997,100*b/1 (per unit count),reported,-0.03040140317835012,0.025799355908232898,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1783783783783783,1501.0,count,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M1,3,Model 1,16,N_balcony,terrace_balcony,C_exterior,level,count,0.0491,0.0514,,,,,,high,Number of balconies,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,900.0,0.603,se,"Damascus Governorate districts (12 districts), property attributes + building war-damage dummies",semi_elasticity,4.91,5.140000000000001,100*b/1 (per unit count),reported,0.03200374821190966,0.03350290546012539,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9552529182879377,890.0,count,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M2,3,Model 2,16,N_balcony,terrace_balcony,C_exterior,level,count,0.0229,0.0345,,,,,,high,Number of balconies,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,1511.0,0.474,se,"Rural Damascus Governorate districts (37 districts), property attributes + building war-damage dummies",semi_elasticity,2.29,3.45,100*b/1 (per unit count),reported,0.017130195180799494,0.02580749928985077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6637681159420289,1501.0,count,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M1,3,Model 1,16,Parking,parking,A_structural,dummy,binary,-0.0572,0.0692,,,,,,high,Parking dummy,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,900.0,0.603,se,"Damascus Governorate districts (12 districts), property attributes + building war-damage dummies",pct_premium,-5.785333387324276,6.535283772547442,100*(exp(b - se^2/2) - 1),reported,-0.027696716884101212,0.033507216929716845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8265895953757226,890.0,binary,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M2,3,Model 2,16,Parking,parking,A_structural,dummy,binary,0.2003,0.0734,,,**,,,high,Parking dummy,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,1511.0,0.474,se,"Rural Damascus Governorate districts (37 districts), property attributes + building war-damage dummies",pct_premium,21.848248530559268,8.967786177238793,100*(exp(b - se^2/2) - 1),reported,0.07026190007486811,0.025747496083351577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7288828337874658,1501.0,binary,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M1,3,Model 1,16,Elevator,accessibility,B_interior,dummy,binary,-0.0411,0.0799,,,,,,high,Elevator dummy,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,900.0,0.603,se,"Damascus Governorate districts (12 districts), property attributes + building war-damage dummies",pct_premium,-4.332543707301772,7.668267883151981,100*(exp(b - se^2/2) - 1),reported,-0.017239929685718667,0.0335150944498521,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5143929912390488,890.0,binary,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,True
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T3-M2,3,Model 2,16,Elevator,accessibility,B_interior,dummy,binary,0.0432,0.042,,,,,,high,Elevator dummy,"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,1511.0,0.474,se,"Rural Damascus Governorate districts (37 districts), property attributes + building war-damage dummies",pct_premium,4.322617193142664,4.385416153900877,100*(exp(b - se^2/2) - 1),reported,0.026539400660646785,0.02580219508673993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0285714285714285,1501.0,binary,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T4-M3,4,Model 3,17,D_city_center,cbd_distance,D_location,level,m,6e-05,4e-05,,,***,,,medium,Distance to city centre (Great Umayyad Mosque) in metres; Model 3 stars *** printed despite SE 0.00004 (as printed),"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,900.0,0.427,se,"Damascus Governorate districts, district attributes + district war-damage dummies",semi_elasticity,6.0,4.0,100*b/0.001 (X per m->km),reported,0.050216678166132296,0.0334777854440882,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5,890.0,m,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,True
71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7,71a2f8a0af3e00fb77bb5a3c7e34234f9d6c71e7:T4-M4,4,Model 4,17,D_city_center,cbd_distance,D_location,level,m,4e-05,9e-06,,,**,,,high,Distance to city centre (Great Umayyad Mosque) in metres; Model 3 stars *** printed despite SE 0.00004 (as printed),"natural log of property price (USD, inflation-adjusted to 2010)",log,OLS,1511.0,0.432,se,"Rural Damascus Governorate districts, district attributes + district war-damage dummies",semi_elasticity,4.0,0.8999999999999999,100*b/0.001 (X per m->km),reported,0.1139693650206361,0.025643107129643117,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.444444444444445,1501.0,m,,2024.0,Syria,,,2010.0,2022.0,mixed,transaction,journal,True,True,unknown,,2016.0,ols,journal,True,True,False
75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65:T2-HPM,2,Hedonic price model (HPM),7,FLOORSIZE,living_area,A_structural,level,m2,0.005,,49.578,,,,,high,"floor area in square metres; t-ratio printed in separate column, no SE; printed standardised coefficient = 0.542; text states all variables significant at 1% level",ln selling price (MYR),log,OLS,4393.0,0.73,none,"global semi-log OLS, landed residential sales Kuala Lumpur 2010; r2 = adjusted R2; AICc 5663.63; t-ratio in separate column; variables retained by significance (stepwise-type selection)",semi_elasticity,0.5,0.010085118399290008,100*b/1 (X per m2->m2),|b/t|,0.5994181701761168,0.012090406433823808,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),49.578,4383.0,m2,,2017.0,Malaysia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65:T2-HPM,2,Hedonic price model (HPM),7,LOTSIZE,lot_size,A_structural,level,m2,0.000186,,9.593,,,,,high,"lot size in square metres; t-ratio printed in separate column, no SE; printed standardised coefficient = 0.086; text states all variables significant at 1% level",ln selling price (MYR),log,OLS,4393.0,0.73,none,"global semi-log OLS, landed residential sales Kuala Lumpur 2010; r2 = adjusted R2; AICc 5663.63; t-ratio in separate column; variables retained by significance (stepwise-type selection)",semi_elasticity,0.0186,0.0019389137913061606,100*b/1 (X per m2->m2),|b/t|,0.14340248593168906,0.014948659015082777,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.593,4383.0,m2,,2017.0,Malaysia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65:T2-HPM,2,Hedonic price model (HPM),7,BEDROOMS,bedrooms,A_structural,dummy,binary,0.19,,11.497,,,,,high,"dummy = 1 if four or more bedrooms; t-ratio printed in separate column, no SE; printed standardised coefficient = 0.108; text states all variables significant at 1% level",ln selling price (MYR),log,OLS,4393.0,0.73,none,"global semi-log OLS, landed residential sales Kuala Lumpur 2010; r2 = adjusted R2; AICc 5663.63; t-ratio in separate column; variables retained by significance (stepwise-type selection)",pct_premium,20.908447964840214,1.998411964467929,100*(exp(b - se^2/2) - 1),|b/t|,0.17109879409801748,0.01488203827937875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.497,4383.0,binary,,2017.0,Malaysia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65:T2-HPM,2,Hedonic price model (HPM),7,TYPE_TERRACED,dwelling_type,A_structural,dummy,binary,-0.084,,-2.841,,,,,high,"dummy = 1 if cluster/terraced house (reference: detached and other types); t-ratio printed in separate column, no SE; printed standardised coefficient = -0.043; text states all variables significant at 1% level",ln selling price (MYR),log,OLS,4393.0,0.73,none,"global semi-log OLS, landed residential sales Kuala Lumpur 2010; r2 = adjusted R2; AICc 5663.63; t-ratio in separate column; variables retained by significance (stepwise-type selection)",pct_premium,-8.097054439277906,2.7184873464269788,100*(exp(b - se^2/2) - 1),|b/t|,-0.04287320891015263,0.01509088662800163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.841,4383.0,binary,,2017.0,Malaysia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65:T2-HPM,2,Hedonic price model (HPM),7,TYPE_TOWNHOUSE,dwelling_type,A_structural,dummy,binary,-0.223,,-5.645,,,,,high,"dummy = 1 if town house; t-ratio printed in separate column, no SE; printed standardised coefficient = -0.062; text states all variables significant at 1% level",ln selling price (MYR),log,OLS,4393.0,0.73,none,"global semi-log OLS, landed residential sales Kuala Lumpur 2010; r2 = adjusted R2; AICc 5663.63; t-ratio in separate column; variables retained by significance (stepwise-type selection)",pct_premium,-20.05092227709564,3.1607725667437654,100*(exp(b - se^2/2) - 1),|b/t|,-0.08495817639633119,0.015050164109181788,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.645,4383.0,binary,,2017.0,Malaysia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65:T2-HPM,2,Hedonic price model (HPM),7,TYPE_SEMIDETACHED,dwelling_type,A_structural,dummy,binary,0.357,,10.454,,,,,high,"dummy = 1 if semi-detached; t-ratio printed in separate column, no SE; printed standardised coefficient = 0.124; text states all variables significant at 1% level",ln selling price (MYR),log,OLS,4393.0,0.73,none,"global semi-log OLS, landed residential sales Kuala Lumpur 2010; r2 = adjusted R2; AICc 5663.63; t-ratio in separate column; variables retained by significance (stepwise-type selection)",pct_premium,42.82028449922131,4.880101449567955,100*(exp(b - se^2/2) - 1),|b/t|,0.155972772236994,0.014919913165964607,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.454,4383.0,binary,,2017.0,Malaysia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65:T2-HPM,2,Hedonic price model (HPM),7,TYPE_BUNGALOW,dwelling_type,A_structural,dummy,binary,0.442,,9.869,,,,,high,"dummy = 1 if bungalow; t-ratio printed in separate column, no SE; printed standardised coefficient = 0.096; text states all variables significant at 1% level",ln selling price (MYR),log,OLS,4393.0,0.73,none,"global semi-log OLS, landed residential sales Kuala Lumpur 2010; r2 = adjusted R2; AICc 5663.63; t-ratio in separate column; variables retained by significance (stepwise-type selection)",pct_premium,55.42561568975282,6.967986191831751,100*(exp(b - se^2/2) - 1),|b/t|,0.14743985404422366,0.014939695414350355,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.869,4383.0,binary,,2017.0,Malaysia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65:T2-HPM,2,Hedonic price model (HPM),7,PRIMARY_SCHOOL,school_distance,D_location,level,m,2.832e-05,,2.783,,,,,high,"network distance in metres to nearest primary school; t-ratio printed in separate column, no SE; printed standardised coefficient = 0.031; text states all variables significant at 1% level",ln selling price (MYR),log,OLS,4393.0,0.73,none,"global semi-log OLS, landed residential sales Kuala Lumpur 2010; r2 = adjusted R2; AICc 5663.63; t-ratio in separate column; variables retained by significance (stepwise-type selection)",semi_elasticity,2.832,1.017606899029824,100*b/0.001 (X per m->km),|b/t|,0.041999497487108864,0.015091447174670812,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.783,4383.0,m,,2017.0,Malaysia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65:T2-HPM,2,Hedonic price model (HPM),7,SECONDARY_SCHOOL,school_distance,D_location,level,m,5.244e-05,,6.881,,,,,high,"network distance in metres to nearest secondary school; t-ratio printed in separate column, no SE; printed standardised coefficient = 0.07; text states all variables significant at 1% level",ln selling price (MYR),log,OLS,4393.0,0.73,none,"global semi-log OLS, landed residential sales Kuala Lumpur 2010; r2 = adjusted R2; AICc 5663.63; t-ratio in separate column; variables retained by significance (stepwise-type selection)",semi_elasticity,5.244,0.7620985321900886,100*b/0.001 (X per m->km),|b/t|,0.10337907202756663,0.015023844212696792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.881,4383.0,m,,2017.0,Malaysia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65:T2-HPM,2,Hedonic price model (HPM),7,SHOPMALL,commercial_distance,D_location,level,m,-8.112e-05,,-11.385,,,,,high,"network distance in metres to nearest shopping mall; t-ratio printed in separate column, no SE; printed standardised coefficient = -0.112; text states all variables significant at 1% level",ln selling price (MYR),log,OLS,4393.0,0.73,none,"global semi-log OLS, landed residential sales Kuala Lumpur 2010; r2 = adjusted R2; AICc 5663.63; t-ratio in separate column; variables retained by significance (stepwise-type selection)",semi_elasticity,-8.112,0.7125164690382082,100*b/0.001 (X per m->km),|b/t|,-0.16948011047854353,0.01488626354664414,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.385,4383.0,m,,2017.0,Malaysia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65:T2-HPM,2,Hedonic price model (HPM),7,FOREST,green_space,E_environment,level,m,-2.973e-05,,-5.934,,,,,high,"network distance in metres to nearest forest; t-ratio printed in separate column, no SE; printed standardised coefficient = 0.052; text states all variables significant at 1% level",ln selling price (MYR),log,OLS,4393.0,0.73,none,"global semi-log OLS, landed residential sales Kuala Lumpur 2010; r2 = adjusted R2; AICc 5663.63; t-ratio in separate column; variables retained by significance (stepwise-type selection)",semi_elasticity,-2.973,0.5010111223458038,100*b/0.001 (X per m->km),|b/t|,-0.08927384683434206,0.01504446357167881,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.934,4383.0,m,,2017.0,Malaysia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65,75ba68147bf6e34f9b631b70a8cea636eda11e65:T2-HPM,2,Hedonic price model (HPM),7,RAIL_STATION,transit_distance,D_location,dummy,binary,-0.036,,-2.132,,,,,high,"dummy = 1 if within 2 km radius of nearest rail station; t-ratio printed in separate column, no SE; printed standardised coefficient = -0.018; text states all variables significant at 1% level",ln selling price (MYR),log,OLS,4393.0,0.73,none,"global semi-log OLS, landed residential sales Kuala Lumpur 2010; r2 = adjusted R2; AICc 5663.63; t-ratio in separate column; variables retained by significance (stepwise-type selection)",pct_premium,-3.5497216759221795,1.6288485255812581,100*(exp(b - se^2/2) - 1),|b/t|,-0.03218669520917442,0.015096948972408262,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.132,4383.0,binary,,2017.0,Malaysia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c1,3,1 (Overall),9,Age of house (Years),age,A_structural,level,years,-0.0023,0.0018,,,,,,high,,Log of rent,log,OLS,201.0,0.7904,se,Khulna city overall,semi_elasticity,-0.22999999999999998,0.18,100*b/1 (per year),reported,-0.0920640989270479,0.07205016437768964,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.277777777777778,191.0,years,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c2,3,2 (Planned areas),9,Age of house (Years),age,A_structural,level,years,-0.0085,0.0064,,,,,,high,,Log of rent,log,OLS,72.0,0.6072,se,planned residential areas,semi_elasticity,-0.8500000000000001,0.64,100*b/1 (per year),reported,-0.166322674985009,0.12523119057694795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.328125,62.0,years,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c3,3,3 (Unplanned areas),9,Age of house (Years),age,A_structural,level,years,-0.0019,0.0018,,,,,,high,,Log of rent,log,OLS,129.0,0.7954,se,unplanned residential areas,semi_elasticity,-0.19,0.18,100*b/1 (per year),reported,-0.09631278113658055,0.09124368739255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0555555555555556,119.0,years,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c1,3,1 (Overall),9,Two rooms (=1),bedrooms,A_structural,dummy,binary,0.3915,0.0924,,,***,,,medium,Two-room flat (ref. one room); planned-area column blank,Log of rent,log,OLS,201.0,0.7904,se,Khulna city overall,pct_premium,47.2896867861802,13.667788850173668,100*(exp(b - se^2/2) - 1),reported,0.29311378190031734,0.06917934469371473,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.237012987012988,191.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c3,3,3 (Unplanned areas),9,Two rooms (=1),bedrooms,A_structural,dummy,binary,0.4072,0.0835,,,***,,,medium,Two-room flat (ref. one room); planned-area column blank,Log of rent,log,OLS,129.0,0.7954,se,unplanned residential areas,pct_premium,49.737544910871236,12.546748381035254,100*(exp(b - se^2/2) - 1),reported,0.4081173380526394,0.08368810836786687,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.876646706586826,119.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c1,3,1 (Overall),9,Three rooms (=1),bedrooms,A_structural,dummy,binary,0.4772,0.0908,,,***,,,high,Three-room flat (ref. one room),Log of rent,log,OLS,201.0,0.7904,se,Khulna city overall,pct_premium,60.4926048789646,14.632925964566411,100*(exp(b - se^2/2) - 1),reported,0.35544245031779265,0.06763238576876691,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.255506607929515,191.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c2,3,2 (Planned areas),9,Three rooms (=1),bedrooms,A_structural,dummy,binary,-0.0137,0.1151,,,,,,high,Three-room flat (ref. one room),Log of rent,log,OLS,72.0,0.6072,se,planned residential areas,pct_premium,-2.0118864519689805,11.353388240086181,100*(exp(b - se^2/2) - 1),reported,-0.015114708813437953,0.1269856193012196,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.11902693310165074,62.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c3,3,3 (Unplanned areas),9,Three rooms (=1),bedrooms,A_structural,dummy,binary,0.4943,0.0814,,,***,,,high,Three-room flat (ref. one room),Log of rent,log,OLS,129.0,0.7954,se,unplanned residential areas,pct_premium,63.39281440806119,13.34431137784058,100*(exp(b - se^2/2) - 1),reported,0.4863824848328258,0.08009616480961364,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.072481572481573,119.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c1,3,1 (Overall),9,Four rooms (=1),bedrooms,A_structural,dummy,binary,0.6137,0.103,,,***,,,high,Four-room flat (ref. one room),Log of rent,log,OLS,201.0,0.7904,se,Khulna city overall,pct_premium,83.74807943576994,19.02671216509515,100*(exp(b - se^2/2) - 1),reported,0.3958986814229461,0.06644543618472128,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.958252427184466,191.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c2,3,2 (Planned areas),9,Four rooms (=1),bedrooms,A_structural,dummy,binary,0.0777,0.1291,,,,,,high,Four-room flat (ref. one room),Log of rent,log,OLS,72.0,0.6072,se,planned residential areas,pct_premium,7.182906431040825,13.953106963389148,100*(exp(b - se^2/2) - 1),reported,0.0762138574396928,0.12663074640237248,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6018590240123936,62.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c3,3,3 (Unplanned areas),9,Four rooms (=1),bedrooms,A_structural,dummy,binary,0.6826,0.1178,,,***,,,high,Four-room flat (ref. one room),Log of rent,log,OLS,129.0,0.7954,se,unplanned residential areas,pct_premium,96.53327708178183,23.312814273720736,100*(exp(b - se^2/2) - 1),reported,0.46911189707930867,0.08095719524749863,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.794567062818336,119.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,True
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c1,3,1 (Overall),9,Garage (=1),garage,A_structural,dummy,binary,0.1549,0.0425,,,***,,,high,,Log of rent,log,OLS,201.0,0.7904,se,Khulna city overall,pct_premium,16.648724150011397,4.9620501048752175,100*(exp(b - se^2/2) - 1),reported,0.25500308688959855,0.0699653401730661,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.644705882352941,191.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c2,3,2 (Planned areas),9,Garage (=1),garage,A_structural,dummy,binary,0.183,0.0803,,,**,,,high,,Log of rent,log,OLS,72.0,0.6072,se,planned residential areas,pct_premium,19.694916260330398,9.64253969688907,100*(exp(b - se^2/2) - 1),reported,0.2780170875690565,0.12199329033767889,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2789539227895395,62.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c3,3,3 (Unplanned areas),9,Garage (=1),garage,A_structural,dummy,binary,0.124,0.0569,,,**,,,high,,Log of rent,log,OLS,129.0,0.7954,se,unplanned residential areas,pct_premium,13.018484048765178,6.441170305985307,100*(exp(b - se^2/2) - 1),reported,0.19590172035472098,0.08989361200148083,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1792618629173988,119.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c1,3,1 (Overall),9,Open space (meters),green_space,E_environment,level,m,-0.0002,0.0001,,,***,,,high,Distance to nearest open space in metres,Log of rent,log,OLS,201.0,0.7904,se,Khulna city overall,semi_elasticity,-20.0,10.0,100*b/0.001 (X per m->km),reported,-0.1432229748078866,0.07161148740394328,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,191.0,m,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c2,3,2 (Planned areas),9,Open space (meters),green_space,E_environment,level,m,-0.0002,0.0002,,,,,,high,Distance to nearest open space in metres,Log of rent,log,OLS,72.0,0.6072,se,planned residential areas,semi_elasticity,-20.0,20.0,100*b/0.001 (X per m->km),reported,-0.1259881576697424,0.12598815766974242,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,62.0,m,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c3,3,3 (Unplanned areas),9,Open space (meters),green_space,E_environment,level,m,-0.0003,0.0001,,,***,,,high,Distance to nearest open space in metres,Log of rent,log,OLS,129.0,0.7954,se,unplanned residential areas,semi_elasticity,-30.0,10.0,100*b/0.001 (X per m->km),reported,-0.26516504294495524,0.08838834764831845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.9999999999999996,119.0,m,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c1,3,1 (Overall),9,Stationary shop distance within 0.5-1 km,commercial_distance,D_location,dummy,binary,0.0276,0.0512,,,,,,high,ref. < 0.5 km,Log of rent,log,OLS,201.0,0.7904,se,Khulna city overall,pct_premium,2.6637891330760555,5.263280171050715,100*(exp(b - se^2/2) - 1),reported,0.03897555602958569,0.07230248075053576,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5390625,191.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c2,3,2 (Planned areas),9,Stationary shop distance within 0.5-1 km,commercial_distance,D_location,dummy,binary,0.0309,0.0925,,,,,,high,ref. < 0.5 km,Log of rent,log,OLS,72.0,0.6072,se,planned residential areas,pct_premium,2.697940274957489,9.540286834563853,100*(exp(b - se^2/2) - 1),reported,0.04238677903412955,0.12688598901802536,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3340540540540541,62.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c3,3,3 (Unplanned areas),9,Stationary shop distance within 0.5-1 km,commercial_distance,D_location,dummy,binary,-0.0006,0.0646,,,,,,high,ref. < 0.5 km,Log of rent,log,OLS,129.0,0.7954,se,unplanned residential areas,pct_premium,-0.2682974373609204,6.456125162567475,100*(exp(b - se^2/2) - 1),reported,-0.0008514224440509584,0.09166981647615322,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.009287925696594425,119.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c1,3,1 (Overall),9,Stationary shop distance above 1 km,commercial_distance,D_location,dummy,binary,-0.0563,0.0895,,,,,,high,ref. < 0.5 km,Log of rent,log,OLS,201.0,0.7904,se,Khulna city overall,pct_premium,-5.852277848378473,8.46003687441699,100*(exp(b - se^2/2) - 1),reported,-0.04546940450757936,0.0722826235067203,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.629050279329609,191.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c2,3,2 (Planned areas),9,Stationary shop distance above 1 km,commercial_distance,D_location,dummy,binary,0.0329,0.2432,,,,,,high,ref. < 0.5 km,Log of rent,log,OLS,72.0,0.6072,se,planned residential areas,pct_premium,0.3332420207431852,25.13343564511267,100*(exp(b - se^2/2) - 1),reported,0.017177992017679937,0.12698138780242435,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.13527960526315788,62.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c3,3,3 (Unplanned areas),9,Stationary shop distance above 1 km,commercial_distance,D_location,dummy,binary,-0.1015,0.0983,,,,,,high,ref. < 0.5 km,Log of rent,log,OLS,129.0,0.7954,se,unplanned residential areas,pct_premium,-10.087341232851344,8.88121999293403,100*(exp(b - se^2/2) - 1),reported,-0.09423282305649858,0.09126193602417546,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0325534079348933,119.0,binary,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c1,3,1 (Overall),9,Hospital distance (km),hospital_distance,D_location,level,km,-0.1665,0.0505,,,***,,,high,,Log of rent,log,OLS,201.0,0.7904,se,Khulna city overall,semi_elasticity,-16.650000000000002,5.050000000000001,100*b/1 (X per km->km),reported,-0.23205265019350957,0.07038233534397738,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.297029702970297,191.0,km,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c2,3,2 (Planned areas),9,Hospital distance (km),hospital_distance,D_location,level,km,-0.1722,0.0756,,,**,,,high,,Log of rent,log,OLS,72.0,0.6072,se,planned residential areas,semi_elasticity,-17.22,7.5600000000000005,100*b/1 (X per km->km),reported,-0.2778846880589063,0.12199815573317838,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.2777777777777777,62.0,km,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c3,3,3 (Unplanned areas),9,Hospital distance (km),hospital_distance,D_location,level,km,-0.186,0.0882,,,**,,,high,,Log of rent,log,OLS,129.0,0.7954,se,unplanned residential areas,semi_elasticity,-18.6,8.82,100*b/1 (X per km->km),reported,-0.18980327427609814,0.09000348812447236,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.108843537414966,119.0,km,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,True
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c1,3,1 (Overall),9,School distance (km),school_distance,D_location,level,km,-0.2411,0.0438,,,***,,,high,,Log of rent,log,OLS,201.0,0.7904,se,Khulna city overall,semi_elasticity,-24.11,4.38,100*b/1 (X per km->km),reported,-0.3700259211367352,0.06722163146324762,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.504566210045662,191.0,km,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c2,3,2 (Planned areas),9,School distance (km),school_distance,D_location,level,km,-0.0476,0.1283,,,,,,high,,Log of rent,log,OLS,72.0,0.6072,se,planned residential areas,semi_elasticity,-4.760000000000001,12.83,100*b/1 (X per km->km),reported,-0.047065524341536595,0.12685938598779717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3710054559625877,62.0,km,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,False
75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884,75d0711aebd70fde400d1a6a49265e443bbe1884:T3-c3,3,3 (Unplanned areas),9,School distance (km),school_distance,D_location,level,km,-0.254,0.0745,,,***,,,high,,Log of rent,log,OLS,129.0,0.7954,se,unplanned residential areas,semi_elasticity,-25.4,7.449999999999999,100*b/1 (X per km->km),reported,-0.29830874586797146,0.08749606916206247,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.409395973154363,119.0,km,,2020.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,unknown,,2017.0,ols,journal,True,True,True
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Leq 16h,noise,E_environment,level,db,-0.0098,0.001,,,,,,high,"Aircraft noise Leq 16h daytime, dB(A) above 50",log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",semi_elasticity,-0.98,0.1,100*b/1 (per dB),reported,-0.15849722199910846,0.016173185918276375,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.799999999999999,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Leq 16h,noise,E_environment,level,db,-0.007,0.0013,,,,,,high,"Aircraft noise Leq 16h daytime, dB(A) above 50",log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",semi_elasticity,-0.7000000000000001,0.13,100*b/1 (per dB),reported,-0.08786021020997507,0.016316896181852513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.384615384615385,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Leq 16h,noise,E_environment,level,db,-0.0098,0.0009,,,,,,high,"Aircraft noise Leq 16h daytime, dB(A) above 50",log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",semi_elasticity,-0.98,0.09,100*b/1 (per dB),reported,-0.17559143343714675,0.016125743887084903,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.88888888888889,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Leq 16h,noise,E_environment,level,db,-0.0099,0.0011,,,,,,high,"Aircraft noise Leq 16h daytime, dB(A) above 50",log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",semi_elasticity,-0.9900000000000001,0.11,100*b/1 (per dB),reported,-0.145845837799237,0.01620509308880411,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.0,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Leq 16h,noise,E_environment,level,db,-0.0099,0.001,,,,,,high,"Aircraft noise Leq 16h daytime, dB(A) above 50",log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",semi_elasticity,-0.9900000000000001,0.1,100*b/1 (per dB),reported,-0.16007330327796845,0.016169020533128128,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.9,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Leq 16h,noise,E_environment,level,db,-0.0086,0.0023,,,,,,high,"Aircraft noise Leq 16h daytime, dB(A) above 50",log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",semi_elasticity,-0.86,0.22999999999999998,100*b/1 (per dB),reported,-0.06113330261550045,0.0163496041878664,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.739130434782609,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Age of building,age,A_structural,level,years,-0.0029,0.0003,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",semi_elasticity,-0.29,0.03,100*b/1 (per year),reported,-0.15639389604861728,0.016178678901581096,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.666666666666666,3727.0,years,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Age of building,age,A_structural,level,years,-0.0026,0.0003,,,,,,high,,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",semi_elasticity,-0.26,0.03,100*b/1 (per year),reported,-0.1405528612729212,0.016217637839183213,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.666666666666668,3727.0,years,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Age of building,age,A_structural,level,years,-0.003,0.0003,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",semi_elasticity,-0.3,0.03,100*b/1 (per year),reported,-0.16164816125656176,0.016164816125656175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.000000000000002,3727.0,years,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Age of building,age,A_structural,level,years,-0.003,0.0003,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",semi_elasticity,-0.3,0.03,100*b/1 (per year),reported,-0.16164816125656176,0.016164816125656175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.000000000000002,3727.0,years,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Age of building,age,A_structural,level,years,-0.0034,0.0003,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",semi_elasticity,-0.33999999999999997,0.03,100*b/1 (per year),reported,-0.1825241932628583,0.016105075876134554,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.333333333333334,3727.0,years,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,New,condition,A_structural,dummy,binary,0.1377,0.012,,,,,,high,Condition: new (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,14.754858279035243,1.3771574511153968,100*(exp(b - se^2/2) - 1),reported,0.18472835308971755,0.01609833142394053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.475,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,New,condition,A_structural,dummy,binary,0.1373,0.0116,,,,,,high,Condition: new (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,14.709506942483364,1.3307198083497631,100*(exp(b - se^2/2) - 1),reported,0.19033562514266122,0.01608079571489344,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.836206896551726,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,New,condition,A_structural,dummy,binary,0.1358,0.0119,,,,,,high,Condition: new (ref. needs renovation),log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,14.53716792153652,1.3630888083526214,100*(exp(b - se^2/2) - 1),reported,0.1837448316580981,0.016101351227771486,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.411764705882353,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,New,condition,A_structural,dummy,binary,0.1359,0.0116,,,,,,high,Condition: new (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,14.549025995638566,1.3288581041151162,100*(exp(b - se^2/2) - 1),reported,0.1884641160147208,0.01608670894606888,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.715517241379311,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,New,condition,A_structural,dummy,binary,0.1367,0.0116,,,,,,high,Condition: new (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,14.64070188190021,1.3299216159464202,100*(exp(b - se^2/2) - 1),reported,0.1895338026113303,0.016083336578576676,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.784482758620689,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,New,condition,A_structural,dummy,binary,0.1271,0.0117,,,,,,high,Condition: new (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,13.545284643076606,1.3285707612378306,100*(exp(b - se^2/2) - 1),reported,0.1751906577913077,0.016126913423747447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.863247863247862,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Renovated,renovation,A_structural,dummy,binary,0.1451,0.009,,,,,,high,Condition: renovated (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,15.610835666882771,1.040539662004895,100*(exp(b - se^2/2) - 1),reported,0.25533233263965127,0.01583729148006107,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.122222222222224,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Renovated,renovation,A_structural,dummy,binary,0.1452,0.0093,,,,,,high,Condition: renovated (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,15.62207994547784,1.0753318452130993,100*(exp(b - se^2/2) - 1),reported,0.24776884619677073,0.01586949221508242,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.612903225806452,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Renovated,renovation,A_structural,dummy,binary,0.1419,0.0096,,,,,,high,Condition: renovated (ref. needs renovation),log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,15.240829243721565,1.1063629407694486,100*(exp(b - se^2/2) - 1),reported,0.2353211406101963,0.015920246299209895,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.781250000000002,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Renovated,renovation,A_structural,dummy,binary,0.1443,0.0093,,,,,,high,Condition: renovated (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,15.518066886424364,1.0743644819311815,100*(exp(b - se^2/2) - 1),reported,0.2463265465361347,0.015875515473222815,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.516129032258068,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Renovated,renovation,A_structural,dummy,binary,0.1448,0.0092,,,,,,high,Condition: renovated (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,15.575947269734659,1.0633437146353608,100*(exp(b - se^2/2) - 1),reported,0.24964763263482145,0.015861589918786997,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.739130434782611,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Renovated,renovation,A_structural,dummy,binary,0.1491,0.0093,,,,,,high,Condition: renovated (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,16.073886507396274,1.0795338279497553,100*(exp(b - se^2/2) - 1),reported,0.25399970667924454,0.015843040054439796,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.03225806451613,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Well maintained,condition,A_structural,dummy,binary,0.1126,0.008,,,,,,high,Condition: well maintained (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,11.914835641360444,0.8953473357872158,100*(exp(b - se^2/2) - 1),reported,0.22465843512571632,0.015961522921898137,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.075000000000001,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Well maintained,condition,A_structural,dummy,binary,0.1125,0.008,,,,,,high,Condition: well maintained (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,11.903644717351813,0.8952578055302246,100*(exp(b - se^2/2) - 1),reported,0.22446897336190988,0.015962238105735813,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.0625,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Well maintained,condition,A_structural,dummy,binary,0.1096,0.0082,,,,,,high,Condition: well maintained (ref. needs renovation),log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,11.579413489161205,0.9149819517872426,100*(exp(b - se^2/2) - 1),reported,0.21387019270294325,0.0160012370452932,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.365853658536585,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Well maintained,condition,A_structural,dummy,binary,0.1119,0.008,,,,,,high,Condition: well maintained (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,11.836522669149542,0.8947208119610869,100*(exp(b - se^2/2) - 1),reported,0.22333166874463536,0.015966517872717453,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.987499999999999,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Well maintained,condition,A_structural,dummy,binary,0.1119,0.008,,,,,,high,Condition: well maintained (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,11.836522669149542,0.8947208119610869,100*(exp(b - se^2/2) - 1),reported,0.22333166874463536,0.015966517872717453,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.987499999999999,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Well maintained,condition,A_structural,dummy,binary,0.1111,0.008,,,,,,high,Condition: well maintained (ref. needs renovation),log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,11.74708922915999,0.8940053215458436,100*(exp(b - se^2/2) - 1),reported,0.22181384325426934,0.015972193933700758,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.887500000000001,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Brick building,roof_materials,A_structural,binary,binary,0.0284,0.009,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,2.876545913299644,0.925926412480037,100*(exp(b - se^2/2) - 1),reported,0.051619851337817775,0.01635840359297042,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.155555555555556,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Brick building,roof_materials,A_structural,binary,binary,0.029,0.0092,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,2.9381030148120324,0.9470706269171203,100*(exp(b - se^2/2) - 1),reported,0.05156468023014001,0.016358450279906487,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1521739130434785,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Brick building,roof_materials,A_structural,binary,binary,0.0298,0.0094,,,,,,high,,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,3.02029482827606,0.9684335558351763,100*(exp(b - se^2/2) - 1),reported,0.051858976565356506,0.016358200661555408,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1702127659574466,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Brick building,roof_materials,A_structural,binary,binary,0.029,0.0093,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,2.9380077971107754,0.9573648728618716,100*(exp(b - se^2/2) - 1),reported,0.051011671931503806,0.016358915481482255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1182795698924735,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Brick building,roof_materials,A_structural,binary,binary,0.0278,0.0093,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,2.8145562734826157,0.9562167240415074,100*(exp(b - se^2/2) - 1),reported,0.04890600149118458,0.0163606407866193,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.989247311827957,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Brick building,roof_materials,A_structural,binary,binary,0.028,0.0093,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,2.835121241165517,0.9564079865119253,100*(exp(b - se^2/2) - 1),reported,0.04925699261347977,0.016360358260905778,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0107526881720434,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Detached,dwelling_type,A_structural,binary,binary,0.0256,0.006,,,,,,high,Detached house,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,2.5912027607686294,0.6155582965142293,100*(exp(b - se^2/2) - 1),reported,0.06971896799153866,0.016340383123016874,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.266666666666667,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Detached,dwelling_type,A_structural,binary,binary,0.0264,0.0056,,,,,,high,Detached house,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,2.673546763270518,0.5749808775037913,100*(exp(b - se^2/2) - 1),reported,0.07699192482602739,0.016331620417642172,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.714285714285714,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Detached,dwelling_type,A_structural,binary,binary,0.0253,0.0057,,,,,,high,Detached house,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,2.5606100097955276,0.5846049738864971,100*(exp(b - se^2/2) - 1),reported,0.07251387929796531,0.01633711905132025,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.43859649122807,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Detached,dwelling_type,A_structural,binary,binary,0.0277,0.0056,,,,,,high,Detached house,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,2.8071091708176343,0.5757288387139952,100*(exp(b - se^2/2) - 1),reported,0.08075904372784713,0.016326738082164043,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.946428571428571,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Detached,dwelling_type,A_structural,binary,binary,0.0271,0.0056,,,,,,high,Detached house,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,2.745443406894288,0.5753835050212345,100*(exp(b - se^2/2) - 1),reported,0.0790207935976936,0.016329020079228197,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.839285714285714,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Detached,dwelling_type,A_structural,binary,binary,0.0267,0.0057,,,,,,high,Detached house,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,2.704295420127867,0.5854239940302656,100*(exp(b - se^2/2) - 1),reported,0.07650363220747551,0.016332236089236347,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.684210526315789,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Cellar,basement,A_structural,binary,binary,0.0476,0.01,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,4.869863474217095,1.0487510709848031,100*(exp(b - se^2/2) - 1),reported,0.07773402340261264,0.01633067718542282,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.760000000000001,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Cellar,basement,A_structural,binary,binary,0.0478,0.0103,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,4.890520152328892,1.0804296674406826,100*(exp(b - se^2/2) - 1),reported,0.07579835526408402,0.01633311839372522,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.640776699029126,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Cellar,basement,A_structural,binary,binary,0.0487,0.0106,,,,,,high,,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,4.9846349865271256,1.112899651803396,100*(exp(b - se^2/2) - 1),reported,0.07504418583990098,0.016334052770081115,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.59433962264151,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Cellar,basement,A_structural,binary,binary,0.0468,0.0103,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,4.785682059959262,1.079349777808049,100*(exp(b - se^2/2) - 1),reported,0.0742214439763655,0.016335061387960786,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.543689320388349,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Cellar,basement,A_structural,binary,binary,0.0458,0.0103,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,4.680948753280423,1.078270967525283,100*(exp(b - se^2/2) - 1),reported,0.07264397573720444,0.016336963975834187,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.446601941747573,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Cellar,basement,A_structural,binary,binary,0.0441,0.0104,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,4.503034157994623,1.0868903326829793,100*(exp(b - se^2/2) - 1),reported,0.06929157753377348,0.01634087089231846,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.240384615384616,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Double glazing,insulation,B_interior,binary,binary,0.0312,0.005,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,3.1678925551215764,0.5158459108091927,100*(exp(b - se^2/2) - 1),reported,0.10168292482603558,0.01629534051699288,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.239999999999999,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Double glazing,insulation,B_interior,binary,binary,0.0317,0.0055,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,3.2192184487312536,0.5677142880816927,100*(exp(b - se^2/2) - 1),reported,0.0939918015494865,0.016307725820888824,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.763636363636364,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Double glazing,insulation,B_interior,binary,binary,0.0322,0.0056,,,,,,high,,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,3.2707836472077645,0.5783254564964275,100*(exp(b - se^2/2) - 1),reported,0.09377138115476108,0.016308066287784535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.75,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Double glazing,insulation,B_interior,binary,binary,0.034,0.0055,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,3.4568958754279233,0.5690215337004648,100*(exp(b - se^2/2) - 1),reported,0.10074449972773084,0.016296904367721163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.1818181818181825,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Double glazing,insulation,B_interior,binary,binary,0.0326,0.0055,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,3.312157561662543,0.5682254609342458,100*(exp(b - se^2/2) - 1),reported,0.09663575931318147,0.016303579025230004,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.927272727272727,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Double glazing,insulation,B_interior,binary,binary,0.0291,0.0055,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,2.9511970595558656,0.5662401481450301,100*(exp(b - se^2/2) - 1),reported,0.08634271328109008,0.016319069520480945,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.290909090909091,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Floor heating,heating,A_structural,binary,binary,0.0356,0.006,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,3.6222614898801186,0.6217447602442431,100*(exp(b - se^2/2) - 1),reported,0.09673364475035996,0.016303423272532577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.933333333333334,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Floor heating,heating,A_structural,binary,binary,0.0359,0.0064,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,3.653095771798931,0.663393399097204,100*(exp(b - se^2/2) - 1),reported,0.09149749713981345,0.016311531523532204,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.609375,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Floor heating,heating,A_structural,binary,binary,0.0357,0.0066,,,,,,high,,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,3.6322325035784697,0.6839876316120044,100*(exp(b - se^2/2) - 1),reported,0.08825647105257256,0.016316322379467195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.409090909090909,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Floor heating,heating,A_structural,binary,binary,0.0333,0.0064,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,3.38394776681874,0.6616708165872022,100*(exp(b - se^2/2) - 1),reported,0.08492057598209958,0.016321071660223344,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.203125,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Floor heating,heating,A_structural,binary,binary,0.0349,0.0064,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,3.549494485303817,0.6627303372842683,100*(exp(b - se^2/2) - 1),reported,0.08896928114898875,0.016315283649098223,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.453125,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Floor heating,heating,A_structural,binary,binary,0.0326,0.0065,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,3.3115376905767935,0.6715391811041086,100*(exp(b - se^2/2) - 1),reported,0.08187737509955736,0.01632524350144549,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.015384615384615,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Garage,garage,A_structural,binary,binary,0.0253,0.005,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,2.5609940999992142,0.5128113806021904,100*(exp(b - se^2/2) - 1),reported,0.08260078437834147,0.01632426568741926,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.06,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Garage,garage,A_structural,binary,binary,0.0257,0.0055,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,2.601757373646252,0.5643182008032935,100*(exp(b - se^2/2) - 1),reported,0.07631717866657951,0.0163324701426532,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.672727272727273,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Garage,garage,A_structural,binary,binary,0.0253,0.0056,,,,,,high,,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,2.5606679565565615,0.5743487462744533,100*(exp(b - se^2/2) - 1),reported,0.07380177865153938,0.016335571559234013,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.517857142857143,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Garage,garage,A_structural,binary,binary,0.0254,0.0055,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,2.5709814630515693,0.5641489307348323,100*(exp(b - se^2/2) - 1),reported,0.07543141533533147,0.016333574186784373,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.618181818181818,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Garage,garage,A_structural,binary,binary,0.0259,0.0055,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,2.622279777292924,0.5644310757305707,100*(exp(b - se^2/2) - 1),reported,0.07690758732182051,0.016331727037452233,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.709090909090909,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Garage,garage,A_structural,binary,binary,0.0278,0.0056,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,2.817390395787389,0.5757864144766066,100*(exp(b - se^2/2) - 1),reported,0.0810486808919141,0.016326352985421542,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.964285714285714,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Underground garage,garage,A_structural,binary,binary,0.029,0.007,,,,,,high,Underground garage,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,2.9399373881519697,0.7205972161325915,100*(exp(b - se^2/2) - 1),reported,0.06770528473816853,0.0163426549367993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.142857142857143,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Underground garage,garage,A_structural,binary,binary,0.0293,0.0071,,,,,,high,Underground garage,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,2.9707514077235375,0.7311107624093711,100*(exp(b - se^2/2) - 1),reported,0.06744342277965115,0.016342945451724343,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.126760563380281,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Underground garage,garage,A_structural,binary,binary,0.0264,0.0072,,,,,,high,Underground garage,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,2.6724953915346905,0.7392611282191603,100*(exp(b - se^2/2) - 1),reported,0.059952849027080264,0.016350777007385527,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.666666666666667,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Underground garage,garage,A_structural,binary,binary,0.027,0.0071,,,,,,high,Underground garage,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,2.734190828435734,0.7294311399620775,100*(exp(b - se^2/2) - 1),reported,0.06217056009786972,0.01634855469240278,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8028169014084505,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Underground garage,garage,A_structural,binary,binary,0.0289,0.0072,,,,,,high,Underground garage,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,2.9294977491051144,0.741111593157097,100*(exp(b - se^2/2) - 1),reported,0.06560681816939823,0.016344951239434854,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.013888888888888,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Underground garage,garage,A_structural,binary,binary,0.0287,0.0073,,,,,,high,Underground garage,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,2.908839299072463,0.751254543793872,100*(exp(b - se^2/2) - 1),reported,0.06426590708509713,0.01634638054777732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.931506849315068,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Modern kitchen,kitchen_quality,B_interior,binary,binary,0.0589,0.005,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,6.06559102380424,0.5303345842598922,100*(exp(b - se^2/2) - 1),reported,0.18946429344178622,0.01608355631933669,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.78,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Modern kitchen,kitchen_quality,B_interior,binary,binary,0.0586,0.0052,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,6.03366796457494,0.5513825280571756,100*(exp(b - se^2/2) - 1),reported,0.18152592867939932,0.01610810288622656,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.26923076923077,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Modern kitchen,kitchen_quality,B_interior,binary,binary,0.0592,0.0054,,,,,,high,,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,6.097194792145633,0.5729332051828222,100*(exp(b - se^2/2) - 1),reported,0.17674873883505374,0.016122351177521792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.962962962962964,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Modern kitchen,kitchen_quality,B_interior,binary,binary,0.0587,0.0053,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,6.04421618832931,0.5620422396259663,100*(exp(b - se^2/2) - 1),reported,0.17850513005261423,0.016117158250065676,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.075471698113208,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Modern kitchen,kitchen_quality,B_interior,binary,binary,0.0585,0.0052,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,6.023065127929161,0.5513273925611906,100*(exp(b - se^2/2) - 1),reported,0.1812263396911068,0.016109007972542822,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.250000000000002,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Modern kitchen,kitchen_quality,B_interior,binary,binary,0.0634,0.0053,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,6.543797099911819,0.5646900556456685,100*(exp(b - se^2/2) - 1),reported,0.1922881550412152,0.01607456185675774,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.962264150943396,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Swimming pool,pool,C_exterior,binary,binary,0.0637,0.015,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,6.5652726335688305,1.5986589285168566,100*(exp(b - se^2/2) - 1),reported,0.06939373775627673,0.016340754573691538,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.246666666666667,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Swimming pool,pool,C_exterior,binary,binary,0.0641,0.0147,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,6.608382208265695,1.567312549598071,100*(exp(b - se^2/2) - 1),reported,0.07124526015531388,0.016338616603480717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.3605442176870755,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Swimming pool,pool,C_exterior,binary,binary,0.0653,0.0152,,,,,,high,,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,6.735591204137004,1.6225684145800694,100*(exp(b - se^2/2) - 1),reported,0.07019678784996061,0.01633983423153754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.296052631578947,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Swimming pool,pool,C_exterior,binary,binary,0.0598,0.0147,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,6.150950348095563,1.5605875746929077,100*(exp(b - se^2/2) - 1),reported,0.06648782055469657,0.016343996022642804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.068027210884353,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Swimming pool,pool,C_exterior,binary,binary,0.0624,0.0147,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,6.427301920366513,1.5646503817475659,100*(exp(b - se^2/2) - 1),reported,0.06936497483225325,0.016340787340290427,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.244897959183674,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Swimming pool,pool,C_exterior,binary,binary,0.0587,0.0149,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,6.0339346395852145,1.580081013288094,100*(exp(b - se^2/2) - 1),reported,0.06439760903698316,0.016346241476167787,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9395973154362416,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,18,Sauna,recreation_private,C_exterior,binary,binary,0.0396,0.011,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,4.03315911712312,1.1444339864501194,100*(exp(b - se^2/2) - 1),reported,0.05886660941064001,0.0163518359474,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6000000000000005,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Sauna,recreation_private,C_exterior,binary,binary,0.0396,0.0109,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,4.033273033494722,1.1340300411187547,100*(exp(b - se^2/2) - 1),reported,0.059404772845442266,0.01635131373776062,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6330275229357802,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,18,Sauna,recreation_private,C_exterior,binary,binary,0.0379,0.0113,,,,,,high,,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,3.856105590135095,1.173648922392023,100*(exp(b - se^2/2) - 1),reported,0.05485631649286043,0.01635557721291089,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3539823008849563,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Sauna,recreation_private,C_exterior,binary,binary,0.0391,0.0109,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,3.981269398970011,1.1334631678283278,100*(exp(b - se^2/2) - 1),reported,0.05865730974282897,0.016352037754394772,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5871559633027528,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Sauna,recreation_private,C_exterior,binary,binary,0.0378,0.0109,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,3.8461815748618955,1.1319906230716263,100*(exp(b - se^2/2) - 1),reported,0.05671344700551246,0.016353877575663645,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.467889908256881,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Sauna,recreation_private,C_exterior,binary,binary,0.0526,0.011,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",pct_premium,5.394419205192591,1.1594087533648771,100*(exp(b - se^2/2) - 1),reported,0.07808816134634139,0.016330223855698767,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.781818181818182,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Log lot size,lot_size,A_structural,log,m2,0.1691,0.006,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",elasticity,0.1691,0.006,b (log-log),reported,0.4191415176672579,0.014871963962173551,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.183333333333334,3727.0,m2,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Log lot size,lot_size,A_structural,log,m2,0.1692,0.0059,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",elasticity,0.1692,0.0059,b (log-log),reported,0.4251772874044693,0.01482592196032133,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.677966101694913,3727.0,m2,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Log lot size,lot_size,A_structural,log,m2,0.1646,0.006,,,,,,high,,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",elasticity,0.1646,0.006,b (log-log),reported,0.40988266850055105,0.014941045024321423,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.433333333333334,3727.0,m2,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Log lot size,lot_size,A_structural,log,m2,0.17,0.0059,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",elasticity,0.17,0.0059,b (log-log),reported,0.42682205768302484,0.014813236119587334,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.8135593220339,3727.0,m2,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Log lot size,lot_size,A_structural,log,m2,0.1693,0.006,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",elasticity,0.1693,0.006,b (log-log),reported,0.4195500324020521,0.01486887297349269,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.21666666666667,3727.0,m2,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Log lot size,lot_size,A_structural,log,m2,0.1786,0.0059,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",elasticity,0.1786,0.0059,b (log-log),reported,0.4442362344064352,0.01467521715004461,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.27118644067797,3727.0,m2,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Log size,living_area,A_structural,log,m3,0.4163,0.011,,,,,,high,Log of building volume in m3 (not floor area),log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",elasticity,0.4163,0.011,b (log-log),reported,0.5268891346007526,0.01392212462312822,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.84545454545455,3727.0,m3,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Log size,living_area,A_structural,log,m3,0.4155,0.0111,,,,,,high,Log of building volume in m3 (not floor area),log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",elasticity,0.4155,0.0111,b (log-log),reported,0.5227163959223781,0.013964264728612267,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.43243243243243,3727.0,m3,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Log size,living_area,A_structural,log,m3,0.4206,0.0113,,,,,,high,Log of building volume in m3 (not floor area),log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",elasticity,0.4206,0.0113,b (log-log),reported,0.5205680811138584,0.013985780591028535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.2212389380531,3727.0,m3,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,22,Log size,living_area,A_structural,log,m3,0.4165,0.0111,,,,,,high,Log of building volume in m3 (not floor area),log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",elasticity,0.4165,0.0111,b (log-log),reported,0.5236297983499207,0.013955079859985883,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.52252252252252,3727.0,m3,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,22,Log size,living_area,A_structural,log,m3,0.4158,0.0112,,,,,,high,Log of building volume in m3 (not floor area),log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",elasticity,0.4158,0.0112,b (log-log),reported,0.5195858205824543,0.013995577658786645,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.125,3727.0,m3,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,22,Log size,living_area,A_structural,log,m3,0.4223,0.0113,,,,,,high,Log of building volume in m3 (not floor area),log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",elasticity,0.4223,0.0113,b (log-log),reported,0.5220994373537756,0.013970456173567755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.37168141592921,3727.0,m3,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Log rooms,bedrooms,A_structural,log,count,0.1243,0.013,,,,,,high,Number of rooms (all rooms),log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",elasticity,0.1243,0.013,b (log-log),reported,0.1547340014688453,0.01618296073286395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.561538461538461,3727.0,count,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Log rooms,bedrooms,A_structural,log,count,0.1246,0.013,,,,,,high,Number of rooms (all rooms),log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",elasticity,0.1246,0.013,b (log-log),reported,0.15509848135249624,0.016182024539185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.584615384615386,3727.0,count,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Log rooms,bedrooms,A_structural,log,count,0.1223,0.0134,,,,,,high,Number of rooms (all rooms),log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",elasticity,0.1223,0.0134,b (log-log),reported,0.14785706861390796,0.016200202121229492,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.126865671641792,3727.0,count,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Log rooms,bedrooms,A_structural,log,count,0.1199,0.013,,,,,,high,Number of rooms (all rooms),log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",elasticity,0.1199,0.013,b (log-log),reported,0.14938110708912286,0.016196450309913235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.223076923076924,3727.0,count,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Log rooms,bedrooms,A_structural,log,count,0.1207,0.013,,,,,,high,Number of rooms (all rooms),log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",elasticity,0.1207,0.013,b (log-log),reported,0.15035535248369988,0.016194031336272563,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.284615384615385,3727.0,count,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,23,Log rooms,bedrooms,A_structural,log,count,0.1246,0.0131,,,,,,high,Number of rooms (all rooms),log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",elasticity,0.1246,0.0131,b (log-log),reported,0.15394268666671762,0.01618498551632425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.511450381679388,3727.0,count,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Log bathrooms,bathrooms,A_structural,log,count,0.1005,0.008,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",elasticity,0.1005,0.008,b (log-log),reported,0.2015537232544312,0.016044077472989547,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.5625,3727.0,count,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Log bathrooms,bathrooms,A_structural,log,count,0.0998,0.0078,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",elasticity,0.0998,0.0078,b (log-log),reported,0.20512640940909657,0.016031923781472477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.794871794871796,3727.0,count,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Log bathrooms,bathrooms,A_structural,log,count,0.1018,0.008,,,,,,high,,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",elasticity,0.1018,0.008,b (log-log),reported,0.20405299441639382,0.016035598775355115,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.725,3727.0,count,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Log bathrooms,bathrooms,A_structural,log,count,0.096,0.0077,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",elasticity,0.096,0.0077,b (log-log),reported,0.20009128207317384,0.016048988249619152,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.467532467532468,3727.0,count,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Log bathrooms,bathrooms,A_structural,log,count,0.0969,0.0077,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",elasticity,0.0969,0.0077,b (log-log),reported,0.20189101872499673,0.016042939568446594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.584415584415584,3727.0,count,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c3,6,3,23,Log bathrooms,bathrooms,A_structural,log,count,0.0969,0.0078,,,,,,high,,log house price (CHF),log,spatial_error,3737.0,,se,"Model 6, 'No GIS': location variables replaced by community dummies; rho 0.1453",elasticity,0.0969,0.0078,b (log-log),reported,0.19940623375587835,0.016051275782206924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.423076923076923,3727.0,count,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Road traffic noise,noise,E_environment,level,db,-0.005,0.001,,,,,,high,"Road traffic noise Lr 16h, dB above 50",log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",semi_elasticity,-0.5,0.1,100*b/1 (per dB),reported,-0.0816278935560424,0.01632557871120848,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Road traffic noise,noise,E_environment,level,db,-0.0051,0.0009,,,,,,high,"Road traffic noise Lr 16h, dB above 50",log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",semi_elasticity,-0.51,0.09,100*b/1 (per dB),reported,-0.09242406915919278,0.016310129851622255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.666666666666667,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Road traffic noise,noise,E_environment,level,db,-0.0053,0.0009,,,,,,high,"Road traffic noise Lr 16h, dB above 50",log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",semi_elasticity,-0.53,0.09,100*b/1 (per dB),reported,-0.0960157532081422,0.01630456186553358,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.888888888888889,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Road traffic noise,noise,E_environment,level,db,-0.0053,0.0009,,,,,,high,"Road traffic noise Lr 16h, dB above 50",log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",semi_elasticity,-0.53,0.09,100*b/1 (per dB),reported,-0.0960157532081422,0.01630456186553358,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.888888888888889,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Road traffic noise,noise,E_environment,level,db,-0.0054,0.0009,,,,,,high,"Road traffic noise Lr 16h, dB above 50",log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",semi_elasticity,-0.54,0.09,100*b/1 (per dB),reported,-0.0978101987120808,0.016301699785346797,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.000000000000001,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Log travel dist. to CBD,cbd_distance,D_location,log,minutes,-0.231,0.015,,,,,,high,Car travel time to Zurich main station,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",elasticity,-0.231,0.015,b (log-log),reported,-0.2445936248766915,0.015882702914070873,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.400000000000002,3727.0,minutes,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Log travel dist. to CBD,cbd_distance,D_location,log,minutes,-0.2354,0.0151,,,,,,high,Car travel time to Zurich main station,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",elasticity,-0.2354,0.0151,b (log-log),reported,-0.2474187699085575,0.0158709576279491,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.589403973509933,3727.0,minutes,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Log travel dist. to CBD,cbd_distance,D_location,log,minutes,-0.229,0.0133,,,,,,high,Car travel time to Zurich main station,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",elasticity,-0.229,0.0133,b (log-log),reported,-0.27144630805605924,0.015765222258277672,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.218045112781958,3727.0,minutes,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Log travel dist. to CBD,cbd_distance,D_location,log,minutes,-0.2335,0.0162,,,,,,high,Car travel time to Zurich main station,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",elasticity,-0.2335,0.0162,b (log-log),reported,-0.22978053000758497,0.015941946835644007,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.413580246913583,3727.0,minutes,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Log travel dist. to CBD,cbd_distance,D_location,log,minutes,-0.2307,0.0159,,,,,,high,Car travel time to Zurich main station,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",elasticity,-0.2307,0.0159,b (log-log),reported,-0.23122717924282335,0.015936333549895498,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.509433962264149,3727.0,minutes,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Low density (< 40%),density,F_neighbourhood,dummy,binary,-0.0034,0.006,,,,,,high,Maximum allowed built density category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,-0.3412165287575375,0.5979634640729387,100*(exp(b - se^2/2) - 1),reported,-0.009281737078453995,0.016379536020801166,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5666666666666667,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Low density (< 40%),density,F_neighbourhood,dummy,binary,-0.004,0.0059,,,,,,high,Maximum allowed built density category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,-0.40093460242015544,0.587644713712955,100*(exp(b - se^2/2) - 1),reported,-0.011104563833412308,0.016379231654283153,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6779661016949153,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Low density (< 40%),density,F_neighbourhood,dummy,binary,-0.0044,0.0056,,,,,,high,Maximum allowed built density category,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,-0.4405945218899143,0.5575414128582312,100*(exp(b - se^2/2) - 1),reported,-0.012869124056204903,0.0163788851624426,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7857142857142858,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Low density (< 40%),density,F_neighbourhood,dummy,binary,-0.0077,0.0059,,,,,,high,Maximum allowed built density category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,-0.7687702288432741,0.5854744457438733,100*(exp(b - se^2/2) - 1),reported,-0.021372720341008775,0.016376500001552177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.305084745762712,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Low density (< 40%),density,F_neighbourhood,dummy,binary,-0.0045,0.006,,,,,,high,Maximum allowed built density category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,-0.4507809191134693,0.5973060658977424,100*(exp(b - se^2/2) - 1),reported,-0.012284254245407904,0.016379005660543875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7499999999999999,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Middle density (40–50%),density,F_neighbourhood,dummy,binary,-0.0024,0.007,,,,,,high,Maximum allowed built density category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,-0.24215632737187853,0.6983220143881672,100*(exp(b - se^2/2) - 1),reported,-0.005615994276585901,0.016379983306708878,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3428571428571428,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,True
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Middle density (40–50%),density,F_neighbourhood,dummy,binary,-0.0029,0.0068,,,,,,high,Maximum allowed built density category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,-0.2918851844522563,0.6780308566379161,100*(exp(b - se^2/2) - 1),reported,-0.006985520834972782,0.016379841957867215,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4264705882352941,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Middle density (40–50%),density,F_neighbourhood,dummy,binary,-0.0034,0.0065,,,,,,high,Maximum allowed built density category,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,-0.34152796196927904,0.6477937527456835,100*(exp(b - se^2/2) - 1),reported,-0.008567811898222142,0.016379640393659977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5230769230769231,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Middle density (40–50%),density,F_neighbourhood,dummy,binary,-0.0065,0.0068,,,,,,high,Maximum allowed built density category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,-0.6501890638372254,0.6755943339263444,100*(exp(b - se^2/2) - 1),reported,-0.015655664948352504,0.016378234099814926,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9558823529411765,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Middle density (40–50%),density,F_neighbourhood,dummy,binary,-0.0027,0.0069,,,,,,high,Maximum allowed built density category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,-0.27200988089052247,0.6881395127879821,100*(exp(b - se^2/2) - 1),reported,-0.006409528102080653,0.01637990514976167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.391304347826087,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Higher density (> 50%),density,F_neighbourhood,dummy,binary,-0.0117,0.007,,,,,,high,Maximum allowed built density category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,-1.1656035880287186,0.691857725190424,100*(exp(b - se^2/2) - 1),reported,-0.02736814850500455,0.016374105943165115,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6714285714285715,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Higher density (> 50%),density,F_neighbourhood,dummy,binary,-0.0126,0.0072,,,,,,high,Maximum allowed built density category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,-1.2546547473644476,0.7109849143091207,100*(exp(b - se^2/2) - 1),reported,-0.02865365280678767,0.016373515889592953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.75,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Higher density (> 50%),density,F_neighbourhood,dummy,binary,-0.0132,0.007,,,,,,high,Maximum allowed built density category,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,-1.3137440495242236,0.6908207165535551,100*(exp(b - se^2/2) - 1),reported,-0.030873730875751997,0.016372433040171514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8857142857142857,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Higher density (> 50%),density,F_neighbourhood,dummy,binary,-0.0145,0.0072,,,,,,high,Maximum allowed built density category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,-1.442092780825055,0.7096353254873153,100*(exp(b - se^2/2) - 1),reported,-0.032970052348743034,0.016371336338686197,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.013888888888889,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,True
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Higher density (> 50%),density,F_neighbourhood,dummy,binary,-0.012,0.0073,,,,,,high,Maximum allowed built density category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,-1.1954613958118032,0.7212923503892092,100*(exp(b - se^2/2) - 1),reported,-0.026916668621506667,0.016374306744749892,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.643835616438356,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Lake view > 0–20 km2,view,E_environment,dummy,binary,0.0552,0.007,,,,,,high,Lake view area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,5.672605382517926,0.7397263607514554,100*(exp(b - se^2/2) - 1),reported,0.12810561397020753,0.016245277133903127,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.885714285714285,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Lake view > 0–20 km2,view,E_environment,dummy,binary,0.0514,0.0066,,,,,,high,Lake view area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,5.272097812498044,0.6948109783807992,100*(exp(b - se^2/2) - 1),reported,0.1265418567088346,0.016248565258332848,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.787878787878788,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Lake view > 0–20 km2,view,E_environment,dummy,binary,0.0563,0.0059,,,,,,high,Lake view area category,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,5.78965977878656,0.6241698562766487,100*(exp(b - se^2/2) - 1),reported,0.15443124979787595,0.016183736657326253,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.542372881355933,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Lake view > 0–20 km2,view,E_environment,dummy,binary,0.0545,0.0067,,,,,,high,Lake view area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,5.598877447968764,0.7075283591971957,100*(exp(b - se^2/2) - 1),reported,0.1320750247439219,0.016236746161179393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.134328358208954,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Lake view > 0–20 km2,view,E_environment,dummy,binary,0.0557,0.0067,,,,,,high,Lake view area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,5.7256721625196905,0.7083779028524803,100*(exp(b - se^2/2) - 1),reported,0.13493071358501896,0.016230444901609103,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.313432835820896,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Lake view 20–40 km2,view,E_environment,dummy,binary,0.139,0.012,,,,,,high,Lake view area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,14.904136604686302,1.3789489200043263,100*(exp(b - se^2/2) - 1),reported,0.18641201009888037,0.01609312317400406,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.583333333333334,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Lake view 20–40 km2,view,E_environment,dummy,binary,0.1346,0.0118,,,,,,high,Lake view area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,14.399941317664911,1.3500132922022055,100*(exp(b - se^2/2) - 1),reported,0.18366727393667404,0.016101588651209163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.40677966101695,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Lake view 20–40 km2,view,E_environment,dummy,binary,0.1411,0.0107,,,,,,high,Lake view area category,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,15.14738781979801,1.2321475819413379,100*(exp(b - se^2/2) - 1),reported,0.21113543125214343,0.01601097884052399,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.186915887850468,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Lake view 20–40 km2,view,E_environment,dummy,binary,0.1318,0.0123,,,,,,high,Lake view area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,14.079382181138755,1.4032825481215527,100*(exp(b - se^2/2) - 1),reported,0.17287880290268726,0.016133606037200706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.715447154471544,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Lake view 20–40 km2,view,E_environment,dummy,binary,0.1357,0.0122,,,,,,high,Lake view area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,14.52530076770051,1.3973126535043223,100*(exp(b - se^2/2) - 1),reported,0.1792458232862573,0.0161149524251462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.122950819672129,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Lake view > 40 km2,view,E_environment,dummy,binary,0.1121,0.014,,,,,,high,Lake view area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,11.85150976730036,1.5660746045334046,100*(exp(b - se^2/2) - 1),reported,0.13004514272275852,0.016241141820861903,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.007142857142858,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Lake view > 40 km2,view,E_environment,dummy,binary,0.1074,0.0138,,,,,,high,Lake view area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,11.32735062773611,1.5364637337742675,100*(exp(b - se^2/2) - 1),reported,0.12645759510473173,0.016248741270440393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.782608695652174,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Lake view > 40 km2,view,E_environment,dummy,binary,0.1103,0.012,,,,,,high,Lake view area category,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,11.653261087544076,1.339935604941055,100*(exp(b - se^2/2) - 1),reported,0.14888366805999664,0.01619767920870317,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.191666666666666,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Lake view > 40 km2,view,E_environment,dummy,binary,0.108,0.0146,,,,,,high,Lake view area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,11.392901650493869,1.6265097082642428,100*(exp(b - se^2/2) - 1),reported,0.12028909169995122,0.016261303137215626,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.397260273972603,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Lake view > 40 km2,view,E_environment,dummy,binary,0.1119,0.0144,,,,,,high,Lake view area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,11.82850651450702,1.6104974615299563,100*(exp(b - se^2/2) - 1),reported,0.12626931319421025,0.016249134137592738,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.770833333333334,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,View 50–100 km2,view,E_environment,dummy,binary,0.0359,0.009,,,,,,high,View on Alps area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,3.651020657593529,0.9328969674804429,100*(exp(b - se^2/2) - 1),reported,0.06519993688127489,0.016345388076085626,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9888888888888894,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,View 50–100 km2,view,E_environment,dummy,binary,0.0357,0.0091,,,,,,high,View on Alps area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,3.630198740971946,0.9430738557074607,100*(exp(b - se^2/2) - 1),reported,0.06412867560487417,0.016346525154183614,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9230769230769234,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,View 50–100 km2,view,E_environment,dummy,binary,0.0406,0.0084,,,,,,high,View on Alps area category,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,4.139870684582947,0.874805776353867,100*(exp(b - se^2/2) - 1),reported,0.0789242028602801,0.016329145419368297,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.833333333333333,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,View 50–100 km2,view,E_environment,dummy,binary,0.0319,0.0092,,,,,,high,View on Alps area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,3.237056787007919,0.949821118019643,100*(exp(b - se^2/2) - 1),reported,0.05670531911958078,0.016353885137935523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4673913043478257,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,View 50–100 km2,view,E_environment,dummy,binary,0.0344,0.0093,,,,,,high,View on Alps area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,3.4953765805249004,0.9625486267142113,100*(exp(b - se^2/2) - 1),reported,0.060478372629965714,0.016350257716822126,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.698924731182796,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,View 100–250 km2,view,E_environment,dummy,binary,0.0236,0.008,,,,,,high,View on Alps area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,2.3847920038109205,0.8191045469566129,100*(exp(b - se^2/2) - 1),reported,0.04826539607651095,0.016361151212376593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9499999999999997,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,View 100–250 km2,view,E_environment,dummy,binary,0.0244,0.0078,,,,,,high,View on Alps area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,2.4668945068514025,0.7992660904581054,100*(exp(b - se^2/2) - 1),reported,0.05117361876558323,0.016358779769325784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1282051282051286,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,View 100–250 km2,view,E_environment,dummy,binary,0.027,0.0071,,,,,,high,View on Alps area category,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,2.734190828435734,0.7294311399620775,100*(exp(b - se^2/2) - 1),reported,0.06217056009786972,0.01634855469240278,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8028169014084505,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,View 100–250 km2,view,E_environment,dummy,binary,0.0213,0.0081,,,,,,high,View on Alps area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,2.1494953521001614,0.8274380560122125,100*(exp(b - se^2/2) - 1),reported,0.04303406521771963,0.016365067054625773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6296296296296298,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,View 100–250 km2,view,E_environment,dummy,binary,0.0216,0.008,,,,,,high,View on Alps area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,2.180227052942474,0.8174679749802,100*(exp(b - se^2/2) - 1),reported,0.044183462129314885,0.016364245233079586,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,View > 250 km2,view,E_environment,dummy,binary,0.0163,0.009,,,,,,high,View on Alps area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,1.639240501609729,0.9147902127678722,100*(exp(b - se^2/2) - 1),reported,0.029653391532631013,0.016373038269550867,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8111111111111111,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,View > 250 km2,view,E_environment,dummy,binary,0.0183,0.009,,,,,,high,View on Alps area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,1.8427223966807071,0.916621623994164,100*(exp(b - se^2/2) - 1),reported,0.033288032832421544,0.016371163688076167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0333333333333337,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,View > 250 km2,view,E_environment,dummy,binary,0.0159,0.0081,,,,,,high,View on Alps area category,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,1.5993747396448876,0.8229819328706028,100*(exp(b - se^2/2) - 1),reported,0.032137199116066634,0.016371780681769792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9629629629629632,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,View > 250 km2,view,E_environment,dummy,binary,0.0135,0.0093,,,,,,high,View on Alps area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,1.3547704631972524,0.9426401288986916,100*(exp(b - se^2/2) - 1),reported,0.023771051176960403,0.016375613033017166,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4516129032258065,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,View > 250 km2,view,E_environment,dummy,binary,0.0137,0.0092,,,,,,high,View on Alps area category,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,1.3751372164790165,0.932690733028224,100*(exp(b - se^2/2) - 1),reported,0.024385063029903647,0.016375370793803908,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4891304347826089,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Near power line,hazard_site,E_environment,binary,binary,-0.0103,0.015,,,,,,high,Power line within 200 m,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,-1.0358477587250614,1.4846292950202462,100*(exp(b - se^2/2) - 1),reported,-0.011247054490002387,0.01637920556796464,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6866666666666666,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Near power line,hazard_site,E_environment,binary,binary,-0.0133,0.015,,,,,,high,Power line within 200 m,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,-1.332295321768684,1.4801820812911892,100*(exp(b - se^2/2) - 1),reported,-0.014522282643600688,0.016378514259700022,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8866666666666666,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Near power line,hazard_site,E_environment,binary,binary,-0.0118,0.014,,,,,,high,Power line within 200 m,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,-1.182749868323374,1.3835770857541565,100*(exp(b - se^2/2) - 1),reported,-0.01380488803043391,0.016378680714074133,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8428571428571429,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Near power line,hazard_site,E_environment,binary,binary,-0.009,0.0151,,,,,,high,Power line within 200 m,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,-0.9072598345397753,1.4964709719470544,100*(exp(b - se^2/2) - 1),reported,-0.009762592658409354,0.016379461015775695,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5960264900662251,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Near power line,hazard_site,E_environment,binary,binary,-0.0064,0.0154,,,,,,high,Power line within 200 m,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,-0.6497380146716969,1.5301754720238894,100*(exp(b - se^2/2) - 1),reported,-0.006807215418377473,0.016379862100470793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4155844155844156,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Near railway,transit_distance,D_location,binary,binary,-0.0243,0.008,,,,,,high,"Railway line within 100 m (nuisance proximity, not station access)",log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,-2.4038363298626186,0.7807942943787568,100*(exp(b - se^2/2) - 1),reported,-0.04969351234530489,0.016360004064297908,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0374999999999996,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Near railway,transit_distance,D_location,binary,binary,-0.0237,0.0082,,,,,,high,"Railway line within 100 m (nuisance proximity, not station access)",log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,-2.345419261386028,0.8007944843146316,100*(exp(b - se^2/2) - 1),reported,-0.047289926497936306,0.01636191549717628,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.890243902439024,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Near railway,transit_distance,D_location,binary,binary,-0.0247,0.0078,,,,,,high,"Railway line within 100 m (nuisance proximity, not station access)",log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,-2.4427128482865768,0.7609699881383156,100*(exp(b - se^2/2) - 1),reported,-0.051801124504128486,0.016358249843408994,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.166666666666667,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Near railway,transit_distance,D_location,binary,binary,-0.0244,0.008,,,,,,high,"Railway line within 100 m (nuisance proximity, not station access)",log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,-2.413595458265083,0.7807162188531602,100*(exp(b - se^2/2) - 1),reported,-0.049897504280637106,0.016359837469061344,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0500000000000003,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Near railway,transit_distance,D_location,binary,binary,-0.0228,0.0083,,,,,,high,"Railway line within 100 m (nuisance proximity, not station access)",log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,-2.257571214285381,0.8112901033277651,100*(exp(b - se^2/2) - 1),reported,-0.04495084408933207,0.016363684471116503,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.746987951807229,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Aspect: East,sunlight,E_environment,dummy,binary,-0.0032,0.007,,,,,,high,Orientation east (slope > 1%),log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,-0.3219306883109674,0.697763580180123,100*(exp(b - se^2/2) - 1),reported,-0.007487900527855812,0.016379782404684587,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.45714285714285713,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Aspect: East,sunlight,E_environment,dummy,binary,-0.0034,0.0068,,,,,,high,Orientation east (slope > 1%),log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,-0.3417267804226687,0.6776919259493304,100*(exp(b - se^2/2) - 1),reported,-0.00818984613512058,0.01637969227024116,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Aspect: East,sunlight,E_environment,dummy,binary,-0.0002,0.0064,,,,,,high,Orientation east (slope > 1%),log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,-0.02204556960709869,0.6398720127991467,100*(exp(b - se^2/2) - 1),reported,-0.0005118824835677614,0.016380239474168366,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.03125,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Aspect: East,sunlight,E_environment,dummy,binary,-0.0032,0.0068,,,,,,high,Orientation east (slope > 1%),log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,-0.321793132480408,0.6778274778892623,100*(exp(b - se^2/2) - 1),reported,-0.007708119998110557,0.016379754995984933,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4705882352941177,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Aspect: East,sunlight,E_environment,dummy,binary,-0.0031,0.0069,,,,,,high,Orientation east (slope > 1%),log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,-0.3118930997626168,0.6878643120266885,100*(exp(b - se^2/2) - 1),reported,-0.00735903971456922,0.01637979807436375,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4492753623188406,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Aspect: West,sunlight,E_environment,dummy,binary,0.0102,0.006,,,,,,high,Orientation west (slope > 1%),log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",pct_premium,1.0234012944043247,0.606151318391961,100*(exp(b - se^2/2) - 1),reported,0.02783562066105109,0.01637389450650064,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7000000000000002,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Aspect: West,sunlight,E_environment,dummy,binary,0.0093,0.0063,,,,,,high,Orientation west (slope > 1%),log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",pct_premium,0.9323349151155957,0.6358863290042145,100*(exp(b - se^2/2) - 1),reported,0.024173290773639725,0.01637545504020756,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.476190476190476,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Aspect: West,sunlight,E_environment,dummy,binary,0.0139,0.006,,,,,,high,Orientation west (slope > 1%),log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",pct_premium,1.3978802380213429,0.608398232497753,100*(exp(b - se^2/2) - 1),reported,0.03792026665566546,0.016368460426905956,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3166666666666664,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Aspect: West,sunlight,E_environment,dummy,binary,0.0093,0.0063,,,,,,high,Orientation west (slope > 1%),log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",pct_premium,0.9323349151155957,0.6358863290042145,100*(exp(b - se^2/2) - 1),reported,0.024173290773639725,0.01637545504020756,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.476190476190476,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Aspect: West,sunlight,E_environment,dummy,binary,0.0106,0.0065,,,,,,high,Orientation west (slope > 1%),log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",pct_premium,1.0635029139317798,0.6569266463693804,100*(exp(b - se^2/2) - 1),reported,0.026702868782990222,0.01637440066881476,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6307692307692307,3727.0,binary,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c1,5,1,19,Log tax revenue,public_services,F_neighbourhood,log,index,0.1559,0.01,,,,,,high,Communal per-capita tax revenue index,log house price (CHF),log,spatial_error,3737.0,,se,"Model 1, ML SAR error, W cut-off 300 m; rho 0.1852; residual SE 0.1279",elasticity,0.1559,0.01,b (log-log),reported,0.24742765031466277,0.015870920482018137,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.590000000000002,3727.0,index,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,19,Log tax revenue,public_services,F_neighbourhood,log,index,0.1568,0.0099,,,,,,high,Communal per-capita tax revenue index,log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",elasticity,0.1568,0.0099,b (log-log),reported,0.2511229602645681,0.015855339965683828,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.838383838383837,3727.0,index,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c3,5,3,19,Log tax revenue,public_services,F_neighbourhood,log,index,0.1549,0.0089,,,,,,high,Communal per-capita tax revenue index,log house price (CHF),log,OLS,3737.0,,se,"Model 3, OLS non-spatial; residual SE 0.1309",elasticity,0.1549,0.0089,b (log-log),reported,0.2741658708928448,0.01575259038700012,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.404494382022474,3727.0,index,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,ols,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c1,6,1,23,Log tax revenue,public_services,F_neighbourhood,log,index,0.1588,0.0107,,,,,,high,Communal per-capita tax revenue index,log house price (CHF),log,spatial_error,3737.0,,se,"Model 4, ML SAR error, W cut-off 600 m; rho 0.2579",elasticity,0.1588,0.0107,b (log-log),reported,0.2362212236093421,0.015916669348992194,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.841121495327103,3727.0,index,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T6-c2,6,2,23,Log tax revenue,public_services,F_neighbourhood,log,index,0.1599,0.0105,,,,,,high,Communal per-capita tax revenue index,log house price (CHF),log,spatial_error,3737.0,,se,"Model 5, ML SAR error, 4 nearest neighbours; rho 0.2233",elasticity,0.1599,0.0105,b (log-log),reported,0.24203121660334245,0.015893231859506543,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.228571428571426,3727.0,index,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,True
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Leq Evening,noise,E_environment,level,db,-0.0064,0.0019,,,,,,high,"Aircraft noise Leq evening (21-23h), dB(A) above 50",log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",semi_elasticity,-0.64,0.19,100*b/1 (per dB),reported,-0.05509175539172371,0.016355364881917973,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.368421052631579,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317,7670a6d2dc2183fc23719395205238727f178317:T5-c2,5,2,18,Leq 1h Peak,noise,E_environment,level,db,-0.0063,0.0023,,,,,,high,"Highest daytime 1-hour Leq in excess of Leq 16h, dB(A)",log house price (CHF),log,spatial_error,3737.0,,se,"Model 2, ML SAR error with three noise metrics; rho 0.1853; residual SE 0.1275",semi_elasticity,-0.63,0.22999999999999998,100*b/1 (per dB),reported,-0.04482252485039164,0.01636377891363504,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.739130434782609,3727.0,db,,2008.0,Switzerland,Europe,High income,1995.0,2005.0,single_family,transaction,journal,True,False,unknown,,2000.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,sizeland,lot_size,A_structural,level,ha,5.3e-05,,,0.01,,,,high,Land area in hectares; <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",semi_elasticity,5.3e-07,2.0575897605861608e-07,100*b/10000 (X per ha->m2),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,ha,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,sizeland,lot_size,A_structural,level,ha,4.8e-05,,,0.01,,,,high,Land area in hectares; <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",semi_elasticity,4.800000000000001e-07,1.863477519021429e-07,100*b/10000 (X per ha->m2),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,ha,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,sizehouse,living_area,A_structural,level,m2,0.002684,,,0.01,,,,high,Building size in m2; <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",semi_elasticity,0.2684,0.10419945127194821,100*b/1 (X per m2->m2),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,m2,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,sizehouse,living_area,A_structural,level,m2,0.002859,,,0.01,,,,high,Building size in m2; <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",semi_elasticity,0.2859,0.11099337972671385,100*b/1 (X per m2->m2),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,m2,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,bathrooms,bathrooms,A_structural,level,count,0.051512,,,0.01,,,,high,<0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",semi_elasticity,5.1512,1.9998219574964966,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,count,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,bathrooms,bathrooms,A_structural,level,count,0.055278,,,0.01,,,,high,<0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",semi_elasticity,5.5278,2.1460272978430526,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,count,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,age,age,A_structural,level,years,-0.010605,,,0.01,,,,high,<0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",semi_elasticity,-1.0605,0.41171206435879687,100*b/1 (per year),|b/z(p)| (two-sided normal),-0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,36157.0,years,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,age,age,A_structural,level,years,-0.010174,,,0.01,,,,high,<0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",semi_elasticity,-1.0174,0.394979589135917,100*b/1 (per year),|b/z(p)| (two-sided normal),-0.013545063381575939,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5758293035489004,36157.0,years,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,garage,garage,A_structural,level,count,0.027471,,,0.01,,,,high,"Basement garage capacity, number of cars; <0.01 printed; recorded as 0.01 upper bound",ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",semi_elasticity,2.7471,1.0664914776049514,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,count,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,garage,garage,A_structural,level,count,0.017696,,,0.01,,,,high,"Basement garage capacity, number of cars; <0.01 printed; recorded as 0.01 upper bound",ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",semi_elasticity,1.7696,0.6870020453458999,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,count,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,True
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,condvpoor,condition,A_structural,dummy,binary,-0.923445,,,0.01,,,,high,Condition very poor (reference: average); <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",pct_premium,-62.75705085911289,14.2379310919052,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,True
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,condvpoor,condition,A_structural,dummy,binary,-1.072054,,,0.01,,,,high,Condition very poor (reference: average); <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",pct_premium,-68.60947924079028,14.246639845677679,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,True
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,condpoor,condition,A_structural,dummy,binary,-0.49363,,,0.01,,,,high,Condition poor (reference: average); <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",pct_premium,-40.06998980352606,11.697786241953958,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,condpoor,condition,A_structural,dummy,binary,-0.514455,,,0.01,,,,high,Condition poor (reference: average); <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",pct_premium,-41.397911105367534,11.940027999778447,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,True
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,condfair,condition,A_structural,dummy,binary,-0.219315,,,0.01,,,,high,Condition fair (reference: average); <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",pct_premium,-19.9836905328614,6.837604271980134,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,condfair,condition,A_structural,dummy,binary,-0.211597,,,0.01,,,,high,Condition fair (reference: average); <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",pct_premium,-19.343523105885964,6.648091940789928,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,condgood,condition,A_structural,dummy,binary,0.135936,,,0.01,,,,high,Condition good (reference: average); <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",pct_premium,14.401438728137572,6.04579840246442,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,condgood,condition,A_structural,dummy,binary,0.124734,,,0.01,,,,high,Condition good (reference: average); <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",pct_premium,13.151961317861826,5.485788477563271,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,condvgood,condition,A_structural,dummy,binary,0.29111,,,0.01,,,,high,Condition very good (reference: average); <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",pct_premium,32.939465042156435,15.120547308183168,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,condvgood,condition,A_structural,dummy,binary,0.262003,,,0.01,,,,high,Condition very good (reference: average); <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",pct_premium,29.28252369919837,13.21830113773887,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,condexcellent,condition,A_structural,dummy,binary,0.441086,,,0.01,,,,high,Condition excellent (reference: average); <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",pct_premium,53.1770667670773,26.617509014697585,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,condexcellent,condition,A_structural,dummy,binary,0.465527,,,0.01,,,,high,Condition excellent (reference: average); <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",pct_premium,56.705101405866706,28.787476887854666,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,parkdist,green_space,E_environment,level,m,-5.1e-05,,,0.018,,,,high,Euclidean distance to closest park in metres,ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",semi_elasticity,-5.1000000000000005,2.155884731387404,100*b/0.001 (X per m->km),|b/z(p)| (two-sided normal),-0.01243984126469444,0.005258600753615238,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.365618126864293,36157.0,m,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,parkdist,green_space,E_environment,level,m,-2.8e-05,,,0.01,,,,high,Euclidean distance to closest park in metres; <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",semi_elasticity,-2.8,1.0870285527625,100*b/0.001 (X per m->km),|b/z(p)| (two-sided normal),-0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,36157.0,m,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c1,3,SDEM,11,parkfacility,green_space,E_environment,binary,binary,-0.037543,,,0.01,,,,high,Closest park has built recreational facilities =1; <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,spatial_error,36167.0,0.771,p,"Spatial Durbin error model (Bayesian), properties within 0-500 m of nearest park; p-values printed",pct_premium,-3.6949296481750715,1.403806264497365,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.013545063381575942,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,spatial,journal,True,True,False
79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831,79a14cd6c47cfe07a6fd907132f2ed86427b4831:T3-c2,3,SLX,11,parkfacility,green_space,E_environment,binary,binary,-0.043141,,,0.01,,,,high,Closest park has built recreational facilities =1; <0.01 printed; recorded as 0.01 upper bound,ln(appraised market value),log,other,36167.0,0.6657,p,"Spatial lag of X model, properties within 0-500 m of nearest park; p-values printed",pct_premium,-4.2357988770098,1.6041213900211928,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.013545063381575944,0.0052585252302681535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5758293035489013,36157.0,binary,,2018.0,United States,North America,High income,,,single_family,appraisal,journal,False,False,unknown,,2015.0,other,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c1,2,1,8,AREA,living_area,A_structural,level,m2,0.012,0.001,,,***,,,high,floor area of apartment (m2); enters with AREA2,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.851,se,,semi_elasticity,1.2,0.1,100*b/1 (X per m2->m2),reported,0.5168765907047376,0.0430730492253948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,395.0,m2,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c2,2,2,8,AREA,living_area,A_structural,level,m2,0.012,0.001,,,***,,,high,floor area of apartment (m2); enters with AREA2,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.861,se,,semi_elasticity,1.2,0.1,100*b/1 (X per m2->m2),reported,0.5168765907047376,0.0430730492253948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,395.0,m2,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c3,2,3,8,AREA,living_area,A_structural,level,m2,0.012,0.001,,,***,,,high,floor area of apartment (m2); enters with AREA2,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.894,se,,semi_elasticity,1.2,0.1,100*b/1 (X per m2->m2),reported,0.5168765907047376,0.0430730492253948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,395.0,m2,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c4,2,4,8,AREA,living_area,A_structural,level,m2,0.012,0.001,,,***,,,high,floor area of apartment (m2); enters with AREA2,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.908,se,,semi_elasticity,1.2,0.1,100*b/1 (X per m2->m2),reported,0.5168765907047376,0.0430730492253948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,395.0,m2,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c1,2,1,8,CNSTR_LQ,condition,A_structural,binary,binary,-0.14,0.021,,,***,,,high,1 = construction quality below average,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.851,se,,pct_premium,-13.08334369594455,1.8256522943374924,100*(exp(b - se^2/2) - 1),reported,-0.31802169777052086,0.04770325466557813,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.666666666666667,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c2,2,2,8,CNSTR_LQ,condition,A_structural,binary,binary,-0.104,0.023,,,***,,,high,1 = construction quality below average,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.861,se,,pct_premium,-9.901304514776887,2.0728181840687707,100*(exp(b - se^2/2) - 1),reported,-0.22184423491172459,0.049061705797785245,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.521739130434782,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c3,2,3,8,CNSTR_LQ,condition,A_structural,binary,binary,-0.104,0.025,,,***,,,high,1 = construction quality below average,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.894,se,,pct_premium,-9.905629148368133,2.253063243553012,100*(exp(b - se^2/2) - 1),reported,-0.20487252209478746,0.0492482024266316,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.159999999999999,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c4,2,4,8,CNSTR_LQ,condition,A_structural,binary,binary,-0.102,0.021,,,***,,,high,1 = construction quality below average,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.908,se,,pct_premium,-9.716954439611836,1.8963620585046412,100*(exp(b - se^2/2) - 1),reported,-0.23740261571889446,0.04887700911859592,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.857142857142857,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c1,2,1,8,AGE,age,A_structural,level,years,-0.001,0.001,,,,,,high,age of building in years,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.851,se,,semi_elasticity,-0.1,0.1,100*b/1 (per year),reported,-0.050251890762960605,0.050251890762960605,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,395.0,years,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c2,2,2,8,AGE,age,A_structural,level,years,-0.009,0.002,,,***,,,high,age of building in years,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.861,se,,semi_elasticity,-0.8999999999999999,0.2,100*b/1 (per year),reported,-0.2208298071653624,0.04907329048119165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.5,395.0,years,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c3,2,3,8,AGE,age,A_structural,level,years,-0.018,0.002,,,***,,,high,age of building in years,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.894,se,,semi_elasticity,-1.7999999999999998,0.2,100*b/1 (per year),reported,-0.4125143236626951,0.045834924851410566,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.0,395.0,years,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c4,2,4,8,AGE,age,A_structural,level,years,-0.018,0.002,,,***,,,high,age of building in years,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.908,se,,semi_elasticity,-1.7999999999999998,0.2,100*b/1 (per year),reported,-0.4125143236626951,0.045834924851410566,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.0,395.0,years,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c1,2,1,8,BATHROOM,bathrooms,A_structural,binary,binary,0.135,0.03,,,***,,,high,1 = more than one bathroom,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.851,se,,pct_premium,14.402185866532502,3.4336103530539432,100*(exp(b - se^2/2) - 1),reported,0.22082980716536244,0.04907329048119165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.500000000000001,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c2,2,2,8,BATHROOM,bathrooms,A_structural,binary,binary,0.144,0.03,,,***,,,high,1 = more than one bathroom,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.861,se,,pct_premium,15.436452759055562,3.4646523255747406,100*(exp(b - se^2/2) - 1),reported,0.23476444178167144,0.04890925870451489,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.8,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c3,2,3,8,BATHROOM,bathrooms,A_structural,binary,binary,0.123,0.033,,,***,,,high,1 = more than one bathroom,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.894,se,,pct_premium,13.026882199230826,3.731918589126715,100*(exp(b - se^2/2) - 1),reported,0.18432598624521515,0.0494533133828626,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.727272727272727,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c4,2,4,8,BATHROOM,bathrooms,A_structural,binary,binary,0.151,0.03,,,***,,,high,1 = more than one bathroom,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.908,se,,pct_premium,16.24734273214341,3.488989974245461,100*(exp(b - se^2/2) - 1),reported,0.24550379093011793,0.04877558760201018,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.033333333333333,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c1,2,1,8,BLW_GRND,floor_level,A_structural,binary,binary,-0.205,0.05,,,***,,,high,1 = apartment below ground floor,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.851,se,,pct_premium,-18.637035655598556,4.073236582057073,100*(exp(b - se^2/2) - 1),reported,-0.20203909408027115,0.04927782782445639,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.1,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c2,2,2,8,BLW_GRND,floor_level,A_structural,binary,binary,-0.191,0.045,,,***,,,high,1 = apartment below ground floor,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.861,se,,pct_premium,-17.470344777969693,3.717596646680372,100*(exp(b - se^2/2) - 1),reported,-0.20885158657961292,0.04920587118367843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.2444444444444445,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c3,2,3,8,BLW_GRND,floor_level,A_structural,binary,binary,-0.237,0.057,,,***,,,high,1 = apartment below ground floor,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.894,se,,pct_premium,-21.22893878191845,4.497250341700376,100*(exp(b - se^2/2) - 1),reported,-0.20477319025688645,0.04924924828963092,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.157894736842105,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c4,2,4,8,BLW_GRND,floor_level,A_structural,binary,binary,-0.266,0.051,,,***,,,high,1 = apartment below ground floor,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.908,se,,pct_premium,-23.455697872582903,3.908839550255198,100*(exp(b - se^2/2) - 1),reported,-0.2538344748026419,0.048667512086220804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.215686274509805,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,True
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c1,2,1,8,GROUND,floor_level,A_structural,binary,binary,-0.075,0.016,,,***,,,high,1 = apartment on ground floor,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.851,se,,pct_premium,-7.23752572379468,1.4843895781256844,100*(exp(b - se^2/2) - 1),reported,-0.22955538898594324,0.04897181631700122,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.6875,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c2,2,2,8,GROUND,floor_level,A_structural,binary,binary,-0.078,0.016,,,***,,,high,1 = apartment on ground floor,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.861,se,,pct_premium,-7.515396132607299,1.4799430824696629,100*(exp(b - se^2/2) - 1),reported,-0.23822597202185103,0.04886686605576431,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.875,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c3,2,3,8,GROUND,floor_level,A_structural,binary,binary,-0.086,0.015,,,***,,,high,1 = apartment on ground floor,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.894,se,,pct_premium,-8.250899232442798,1.3763913468302262,100*(exp(b - se^2/2) - 1),reported,-0.27717286423410936,0.04834410422687954,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.733333333333333,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c4,2,4,8,GROUND,floor_level,A_structural,binary,binary,-0.088,0.014,,,***,,,high,1 = apartment on ground floor,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.908,se,,pct_premium,-8.432886344525315,1.2820652274126558,100*(exp(b - se^2/2) - 1),reported,-0.3015467461141932,0.04797334597271255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.285714285714286,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c1,2,1,8,NRTH_WST,sunlight,E_environment,binary,binary,-0.011,0.014,,,,,,high,1 = faces north and/or west (less sunlight),"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.851,se,,pct_premium,-1.103664438263896,1.3846843902855162,100*(exp(b - se^2/2) - 1),reported,-0.03950271872126122,0.05027618746342336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7857142857142857,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c2,2,2,8,NRTH_WST,sunlight,E_environment,binary,binary,-0.013,0.014,,,,,,high,1 = faces north and/or west (less sunlight),"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.861,se,,pct_premium,-1.3012594485121265,1.3819177890284027,100*(exp(b - se^2/2) - 1),reported,-0.046670588265470755,0.05026063351666081,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9285714285714285,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c3,2,3,8,NRTH_WST,sunlight,E_environment,binary,binary,-0.014,0.012,,,,,,high,1 = faces north and/or west (less sunlight),"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.894,se,,pct_premium,-1.3973452204421477,1.1833170531154342,100*(exp(b - se^2/2) - 1),reported,-0.058600493179042173,0.05022899415346472,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1666666666666667,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c4,2,4,8,NRTH_WST,sunlight,E_environment,binary,binary,-0.019,0.011,,,*,,,high,1 = faces north and/or west (less sunlight),"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.908,se,,pct_premium,-1.887999731296497,1.0792972984670866,100*(exp(b - se^2/2) - 1),reported,-0.08658215639762232,0.05012651159862344,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7272727272727273,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c1,2,1,8,POOL,pool,C_exterior,binary,binary,0.233,0.045,,,***,,,high,"swimming pool in apartment complex (shared, not private)","log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.851,se,,pct_premium,26.110396493024357,5.680716656972676,100*(exp(b - se^2/2) - 1),reported,0.25210722338654795,0.04869023627637192,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.177777777777778,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c2,2,2,8,POOL,pool,C_exterior,binary,binary,0.234,0.046,,,***,,,high,"swimming pool in apartment complex (shared, not private)","log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.861,se,,pct_premium,26.23082633247449,5.812764664155778,100*(exp(b - se^2/2) - 1),reported,0.2479592783916354,0.04874413164963772,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.086956521739131,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,True
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c3,2,3,8,POOL,pool,C_exterior,binary,binary,0.217,0.039,,,***,,,high,"swimming pool in apartment complex (shared, not private)","log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.894,se,,pct_premium,24.139965861825562,4.845141998337279,100*(exp(b - se^2/2) - 1),reported,0.26959454874375655,0.048452476502334134,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.564102564102564,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c4,2,4,8,POOL,pool,C_exterior,binary,binary,0.19,0.041,,,***,,,high,"swimming pool in apartment complex (shared, not private)","log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.908,se,,pct_premium,20.823365038207186,4.957923350394731,100*(exp(b - se^2/2) - 1),reported,0.2270780274301531,0.04900104802440146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.634146341463414,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c1,2,1,8,DISTANCE,cbd_distance,D_location,level,km,-0.018,0.003,,,***,,,high,km from CBD (Anitpark); Table 1 mislabels it 'Binary' but it is continuous (mean 5.77 km),"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.851,se,,semi_elasticity,-1.7999999999999998,0.3,100*b/1 (X per km->km),reported,-0.28900983051545276,0.04816830508590881,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.999999999999999,395.0,km,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c2,2,2,8,DISTANCE,cbd_distance,D_location,level,km,-0.018,0.003,,,***,,,high,km from CBD (Anitpark); Table 1 mislabels it 'Binary' but it is continuous (mean 5.77 km),"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.861,se,,semi_elasticity,-1.7999999999999998,0.3,100*b/1 (X per km->km),reported,-0.28900983051545276,0.04816830508590881,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.999999999999999,395.0,km,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c3,2,3,8,DISTANCE,cbd_distance,D_location,level,km,-0.03,0.003,,,***,,,high,km from CBD (Anitpark); Table 1 mislabels it 'Binary' but it is continuous (mean 5.77 km),"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.894,se,,semi_elasticity,-3.0,0.3,100*b/1 (X per km->km),reported,-0.44946657497549475,0.044946657497549475,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.0,395.0,km,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c4,2,4,8,DISTANCE,cbd_distance,D_location,level,km,-0.01,0.005,,,**,,,high,km from CBD (Anitpark); Table 1 mislabels it 'Binary' but it is continuous (mean 5.77 km),"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.908,se,,semi_elasticity,-1.0,0.5,100*b/1 (X per km->km),reported,-0.10012523486435178,0.05006261743217589,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,395.0,km,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c3,2,3,8,SCHOOL,school_quality,F_neighbourhood,binary,binary,0.2,0.029,,,***,,,high,1 = high-quality public primary school (top-100 SBS) within 1 km; mixes proximity and quality,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.894,se,,pct_premium,22.08892662695998,3.5420679986644927,100*(exp(b - se^2/2) - 1),reported,0.32782700674805615,0.04753491597846814,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.8965517241379315,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,True
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c4,2,4,8,SCHOOL,school_quality,F_neighbourhood,binary,binary,0.151,0.028,,,***,,,high,1 = high-quality public primary school (top-100 SBS) within 1 km; mixes proximity and quality,"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.908,se,,pct_premium,16.254085273553677,3.2563906426290967,100*(exp(b - se^2/2) - 1),reported,0.26187469303726163,0.04855954572876376,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.392857142857142,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c3,2,3,8,AIR,air_pollution,E_environment,binary,binary,0.141,0.02,,,***,,,high,1 = air perceived clean by agents (sign reversed relative to pollution),"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.894,se,,pct_premium,15.119438608210501,2.302849295969488,100*(exp(b - se^2/2) - 1),reported,0.33431382116572006,0.04742040016535038,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.049999999999999,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa,7a87d94cbb2a1bb3af93865c70eaef38f5783daa:T2-c4,2,4,8,AIR,air_pollution,E_environment,binary,binary,0.091,0.022,,,***,,,high,1 = air perceived clean by agents (sign reversed relative to pollution),"log(PRICE), sale price of apartment (TL)",log,OLS,405.0,0.908,se,,pct_premium,9.50039822282729,2.4095918115686237,100*(exp(b - se^2/2) - 1),reported,0.20375693365673614,0.049259918026903236,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.136363636363637,395.0,binary,,2014.0,Turkey,Asia,Upper middle income,,,condo_apartment,transaction,journal,False,False,robust,,2011.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,log size in sq.m.,living_area,A_structural,log,m2,0.939,0.002,,,***,,,high,"apartment size in m2, log; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01",log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,elasticity,0.939,0.002,b (log-log),reported,0.8979398850703288,0.0019125450161242353,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),469.49999999999994,52956.0,m2,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Floors,floor_level,A_structural,level,count,0.002,0.0004,,,***,,,high,floor level of apartment (integer); all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,semi_elasticity,0.2,0.04,100*b/1 (per unit count),reported,0.021722506143937486,0.004344501228787497,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,52956.0,count,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Age (relative to 2017),age,A_structural,level,years,-0.0002,3e-05,,,***,,,high,building age relative to 2017; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,semi_elasticity,-0.02,0.003,100*b/1 (per year),reported,-0.028958028100483903,0.004343704215072586,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.666666666666667,52956.0,years,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Bathtub,bathroom_quality,B_interior,binary,binary,-0.032,0.002,,,***,,,high,dwelling has a bathtub; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,pct_premium,-3.1495354932029596,0.19370131641583954,100*(exp(b - se^2/2) - 1),reported,-0.06936097533661631,0.004335060958538519,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.0,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Refurbished,renovation,A_structural,binary,binary,-0.015,0.002,,,***,,,high,refurbished dwelling; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,pct_premium,-1.4890030618846306,0.19702238792061252,100*(exp(b - se^2/2) - 1),reported,-0.032574153958821656,0.0043432205278428875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.5,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Built-in kitchen,kitchen_quality,B_interior,binary,binary,0.084,0.002,,,***,,,high,built-in kitchen; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,pct_premium,8.76267185532138,0.21752577876176524,100*(exp(b - se^2/2) - 1),reported,0.17954621161490197,0.004274909800354809,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.0,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Balcony,terrace_balcony,C_exterior,binary,binary,0.011,0.002,,,***,,,high,all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,pct_premium,1.1058700325296877,0.2022121444889439,100*(exp(b - se^2/2) - 1),reported,0.023893572955169647,0.004344285991849026,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.5,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Parking,parking,A_structural,binary,binary,0.053,0.002,,,***,,,high,parking space included; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,pct_premium,5.442753626217445,0.2108859290238712,100*(exp(b - se^2/2) - 1),reported,0.11440042072715684,0.004316997008571956,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.5,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Elevator,accessibility,B_interior,binary,binary,0.053,0.002,,,***,,,high,all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,pct_premium,5.442753626217445,0.2108859290238712,100*(exp(b - se^2/2) - 1),reported,0.11440042072715684,0.004316997008571956,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.5,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Terrace,terrace_balcony,C_exterior,binary,binary,0.041,0.002,,,***,,,high,all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,pct_premium,4.185002184335218,0.2083704211090959,100*(exp(b - se^2/2) - 1),reported,0.08873191033744966,0.004328385870119495,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.5,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,log Purchasing Power,income,F_neighbourhood,log,currency,0.406,0.011,,,***,,,high,"household purchasing power EUR per household at ZIP level, log; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01",log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,elasticity,0.406,0.011,b (log-log),reported,0.15836541373350263,0.004290688549429874,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),36.909090909090914,52956.0,currency,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,CBD_distance,cbd_distance,D_location,level,km,-0.019,0.001,,,***,,,high,all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,semi_elasticity,-1.9,0.1,100*b/1 (X per km->km),reported,-0.08228501421715072,0.004330790221955301,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-19.0,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Bakery_distance,commercial_distance,D_location,level,km,-0.011,0.003,,,***,,,high,distance to nearest bakery; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,semi_elasticity,-1.0999999999999999,0.3,100*b/1 (X per km->km),reported,-0.015931575331981546,0.004344975090540422,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.6666666666666665,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Convenience store_distance,commercial_distance,D_location,level,km,-0.036,0.002,,,***,,,high,distance to nearest convenience store; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,semi_elasticity,-3.5999999999999996,0.2,100*b/1 (X per km->km),reported,-0.07798128673650545,0.004332293707583636,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-18.0,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Department store_distance,commercial_distance,D_location,level,km,-0.006,0.001,,,***,,,high,distance to nearest department store; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,semi_elasticity,-0.6,0.1,100*b/1 (X per km->km),reported,-0.026064301757134343,0.004344050292855724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Supermarket_distance,commercial_distance,D_location,level,km,-0.018,0.006,,,***,,,high,distance to nearest supermarket; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,semi_elasticity,-1.7999999999999998,0.6,100*b/1 (X per km->km),reported,-0.013035472159055678,0.004345157386351893,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.9999999999999996,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Bus station_distance,transit_distance,D_location,level,km,-0.028,0.001,,,***,,,high,distance to nearest bus station; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,semi_elasticity,-2.8000000000000003,0.1,100*b/1 (X per km->km),reported,-0.12078394222604698,0.0043137122223588205,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-28.0,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Railway station_distance,transit_distance,D_location,level,km,-0.02,0.002,,,***,,,high,distance to nearest railway station; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,semi_elasticity,-2.0,0.2,100*b/1 (X per km->km),reported,-0.04341429447794924,0.004341429447794924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.0,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,Park_distance,green_space,E_environment,level,km,-0.024,0.006,,,***,,,high,distance to nearest park; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,semi_elasticity,-2.4,0.6,100*b/1 (X per km->km),reported,-0.01737948112335037,0.0043448702808375934,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c1,2,OLS,11,School_distance,school_distance,D_location,level,km,-0.003,0.005,,,***,,,medium,distance to nearest school; all coefficients printed ***; stars * p<0.1 ** p<0.05 *** p<0.01; printed *** inconsistent with beta/SE = -0.6,log monthly asking rent (EUR/month),log,OLS,52966.0,0.88,se,OLS; year and month controls; apartment coordinates as location controls; adj R2 0.880,semi_elasticity,-0.3,0.5,100*b/1 (X per km->km),reported,-0.0026073071010466837,0.004345511835077806,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,ols,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,log size in sq.m.,living_area,A_structural,log,m2,0.928,0.008,,,***,,,high,"apartment size in m2, log; SAR; all printed ***; SE decimal comma in source",log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",elasticity,0.928,0.008,b (log-log),reported,0.4501266326538799,0.0038804020056368953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),116.0,52956.0,m2,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Floors,floor_level,A_structural,level,count,0.003,0.002,,,***,,,medium,floor level of apartment (integer); SAR; all printed ***; SE decimal comma in source; printed *** inconsistent with beta/SE ratio,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",semi_elasticity,0.3,0.2,100*b/1 (per unit count),reported,0.006518151438010669,0.0043454342920071125,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5,52956.0,count,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Age (relative to 2017),age,A_structural,level,years,-0.0,0.0001,,,***,,,medium,building age relative to 2017; SAR; all printed ***; SE decimal comma in source; printed *** inconsistent with beta/SE ratio,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",semi_elasticity,-0.0,0.01,100*b/1 (per year),reported,-0.0,0.0043455266056571734,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.0,52956.0,years,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Bathtub,bathroom_quality,B_interior,binary,binary,-0.032,0.006,,,***,,,high,dwelling has a bathtub; SAR; all printed ***; SE decimal comma in source,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",pct_premium,-3.15108508823827,0.5811039492475186,100*(exp(b - se^2/2) - 1),reported,-0.023169920061469982,0.004344360011525622,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.333333333333333,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Refurbished,renovation,A_structural,binary,binary,-0.013,0.007,,,***,,,medium,refurbished dwelling; SAR; all printed ***; SE decimal comma in source; printed *** inconsistent with beta/SE ratio,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",pct_premium,-1.2940048244774238,0.6909588945142013,100*(exp(b - se^2/2) - 1),reported,-0.00807000090432483,0.004345385102328754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.857142857142857,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Built-in kitchen,kitchen_quality,B_interior,binary,binary,0.077,0.007,,,***,,,high,built-in kitchen; SAR; all printed ***; SE decimal comma in source,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",pct_premium,8.001561568587379,0.7560294534748203,100*(exp(b - se^2/2) - 1),reported,0.047746275676795756,0.004340570516072341,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.0,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Balcony,terrace_balcony,C_exterior,binary,binary,0.012,0.007,,,***,,,medium,SAR; all printed ***; SE decimal comma in source; printed *** inconsistent with beta/SE ratio,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",pct_premium,1.2047493398746223,0.7084506022062544,100*(exp(b - se^2/2) - 1),reported,0.007449267486690175,0.0043454060339026025,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7142857142857142,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Parking,parking,A_structural,binary,binary,0.048,0.008,,,***,,,high,parking space included; SAR; all printed ***; SE decimal comma in source,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",pct_premium,4.913708240066983,0.8393365242595766,100*(exp(b - se^2/2) - 1),reported,0.026064301757134343,0.004344050292855724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Elevator,accessibility,B_interior,binary,binary,0.048,0.009,,,***,,,high,SAR; all printed ***; SE decimal comma in source,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",pct_premium,4.912816477336945,0.9442535897920236,100*(exp(b - se^2/2) - 1),reported,0.023169920061469985,0.004344360011525622,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.333333333333334,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Terrace,terrace_balcony,C_exterior,binary,binary,0.041,0.009,,,***,,,high,SAR; all printed ***; SE decimal comma in source,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",pct_premium,4.180991138964241,0.9376668949909315,100*(exp(b - se^2/2) - 1),reported,0.019792409996508314,0.00434467536508719,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.555555555555556,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,log Purchasing Power,income,F_neighbourhood,log,currency,0.313,0.04,,,***,,,high,"household purchasing power EUR per household at ZIP level, log; SAR; all printed ***; SE decimal comma in source",log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",elasticity,0.313,0.04,b (log-log),reported,0.033984104224788404,0.004343016514349956,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.825,52956.0,currency,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,CBD_distance,cbd_distance,D_location,level,km,-0.014,0.002,,,***,,,high,SAR; all printed ***; SE decimal comma in source,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",semi_elasticity,-1.4000000000000001,0.2,100*b/1 (X per km->km),reported,-0.0304046228469153,0.0043435175495593285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Bakery_distance,commercial_distance,D_location,level,km,-0.016,0.009,,,***,,,medium,distance to nearest bakery; SAR; all printed ***; SE decimal comma in source; printed *** inconsistent with beta/SE ratio,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",semi_elasticity,-1.6,0.8999999999999999,100*b/1 (X per km->km),reported,-0.007725150111422797,0.004345396937675323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.777777777777778,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Convenience store_distance,commercial_distance,D_location,level,km,-0.035,0.007,,,***,,,high,distance to nearest convenience store; SAR; all printed ***; SE decimal comma in source,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",semi_elasticity,-3.5000000000000004,0.7000000000000001,100*b/1 (X per km->km),reported,-0.021722506143937486,0.004344501228787497,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Department store_distance,commercial_distance,D_location,level,km,-0.008,0.005,,,***,,,medium,distance to nearest department store; SAR; all printed ***; SE decimal comma in source; printed *** inconsistent with beta/SE ratio,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",semi_elasticity,-0.8,0.5,100*b/1 (X per km->km),reported,-0.006952674517917867,0.004345421573698667,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Supermarket_distance,commercial_distance,D_location,level,km,-0.029,0.02,,,***,,,medium,distance to nearest supermarket; SAR; all printed ***; SE decimal comma in source; printed *** inconsistent with beta/SE ratio,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",semi_elasticity,-2.9000000000000004,2.0,100*b/1 (X per km->km),reported,-0.006300888498074322,0.0043454403434995325,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.45,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Bus station_distance,transit_distance,D_location,level,km,-0.017,0.004,,,***,,,high,distance to nearest bus station; SAR; all printed ***; SE decimal comma in source,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",semi_elasticity,-1.7000000000000002,0.4,100*b/1 (X per km->km),reported,-0.018465339216936005,0.004344785698102589,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.25,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Railway station_distance,transit_distance,D_location,level,km,-0.02,0.007,,,***,,,high,distance to nearest railway station; SAR; all printed ***; SE decimal comma in source,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",semi_elasticity,-2.0,0.7000000000000001,100*b/1 (X per km->km),reported,-0.012414833453986323,0.004345191708895213,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.857142857142857,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,Park_distance,green_space,E_environment,level,km,-0.019,0.02,,,***,,,medium,distance to nearest park; SAR; all printed ***; SE decimal comma in source; printed *** inconsistent with beta/SE ratio,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",semi_elasticity,-1.9,2.0,100*b/1 (X per km->km),reported,-0.004128215098073798,0.004345489576919787,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.95,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c3,2,SAR,11,School_distance,school_distance,D_location,level,km,0.008,0.006,,,***,,,medium,distance to nearest school; SAR; all printed ***; SE decimal comma in source; printed *** inconsistent with beta/SE ratio,log monthly asking rent (EUR/month),log,spatial_lag,52966.0,0.885,se,"spatial autoregressive model, rho 0.131; SEs printed with comma decimal separator; R2 0.885",semi_elasticity,0.8,0.6,100*b/1 (X per km->km),reported,0.005793938221318773,0.004345453665989081,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3333333333333333,52956.0,km,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,spatial,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c2,2,GAM,11,Floors,floor_level,A_structural,level,count,0.003,0.0003,,,***,,,high,floor level of apartment (integer); GAM parametric term,log monthly asking rent (EUR/month),log,other,52966.0,0.898,se,"generalised additive model; only parametric (linear) terms extracted - size, age and all distance variables enter as smooth splines (edf reported, not coefficients); adj R2 0.898",semi_elasticity,0.3,0.03,100*b/1 (per unit count),reported,0.04341429447794925,0.004341429447794924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.000000000000002,52956.0,count,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,other,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c2,2,GAM,11,Bathtub,bathroom_quality,B_interior,binary,binary,-0.016,0.001,,,***,,,high,dwelling has a bathtub; GAM parametric term,log monthly asking rent (EUR/month),log,other,52966.0,0.898,se,"generalised additive model; only parametric (linear) terms extracted - size, age and all distance variables enter as smooth splines (edf reported, not coefficients); adj R2 0.898",pct_premium,-1.587317200825189,0.09841273200552851,100*(exp(b - se^2/2) - 1),reported,-0.06936097533661631,0.004335060958538519,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.0,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,other,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c2,2,GAM,11,Refurbished,renovation,A_structural,binary,binary,0.005,0.002,,,***,,,high,refurbished dwelling; GAM parametric term,log monthly asking rent (EUR/month),log,other,52966.0,0.898,se,"generalised additive model; only parametric (linear) terms extracted - size, age and all distance variables enter as smooth splines (edf reported, not coefficients); adj R2 0.898",pct_premium,0.5010510836369386,0.2010025041718802,100*(exp(b - se^2/2) - 1),reported,0.010863175483441883,0.004345270193376753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,other,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c2,2,GAM,11,Built-in kitchen,kitchen_quality,B_interior,binary,binary,0.077,0.002,,,***,,,high,built-in kitchen; GAM parametric term,log monthly asking rent (EUR/month),log,other,52966.0,0.898,se,"generalised additive model; only parametric (linear) terms extracted - size, age and all distance variables enter as smooth splines (edf reported, not coefficients); adj R2 0.898",pct_premium,8.003991631060758,0.2160084152785201,100*(exp(b - se^2/2) - 1),reported,0.16500938728063141,0.0042859581111852315,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),38.5,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,other,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c2,2,GAM,11,Balcony,terrace_balcony,C_exterior,binary,binary,0.025,0.002,,,***,,,high,GAM parametric term,log monthly asking rent (EUR/month),log,other,52966.0,0.898,se,"generalised additive model; only parametric (linear) terms extracted - size, age and all distance variables enter as smooth splines (edf reported, not coefficients); adj R2 0.898",pct_premium,2.5313069896238494,0.20506302410488578,100*(exp(b - se^2/2) - 1),reported,0.05423912354005741,0.0043391298832045925,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.5,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,other,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c2,2,GAM,11,Parking,parking,A_structural,binary,binary,0.032,0.002,,,***,,,high,parking space included; GAM parametric term,log monthly asking rent (EUR/month),log,other,52966.0,0.898,se,"generalised additive model; only parametric (linear) terms extracted - size, age and all distance variables enter as smooth splines (edf reported, not coefficients); adj R2 0.898",pct_premium,3.251544027217279,0.20650350106102366,100*(exp(b - se^2/2) - 1),reported,0.06936097533661631,0.004335060958538519,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.0,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,other,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c2,2,GAM,11,Elevator,accessibility,B_interior,binary,binary,0.02,0.002,,,***,,,high,GAM parametric term,log monthly asking rent (EUR/month),log,other,52966.0,0.898,se,"generalised additive model; only parametric (linear) terms extracted - size, age and all distance variables enter as smooth splines (edf reported, not coefficients); adj R2 0.898",pct_premium,2.019929962611622,0.20404026800535116,100*(exp(b - se^2/2) - 1),reported,0.04341429447794924,0.004341429447794924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.0,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,other,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c2,2,GAM,11,Terrace,terrace_balcony,C_exterior,binary,binary,0.02,0.002,,,***,,,high,GAM parametric term,log monthly asking rent (EUR/month),log,other,52966.0,0.898,se,"generalised additive model; only parametric (linear) terms extracted - size, age and all distance variables enter as smooth splines (edf reported, not coefficients); adj R2 0.898",pct_premium,2.019929962611622,0.20404026800535116,100*(exp(b - se^2/2) - 1),reported,0.04341429447794924,0.004341429447794924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.0,52956.0,binary,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,other,journal,True,True,False
7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678,7b29c36e620db272e042f7b9f343c676a2038678:T2-c2,2,GAM,11,log Purchasing Power,income,F_neighbourhood,log,currency,0.069,0.002,,,***,,,high,"household purchasing power EUR per household at ZIP level, log; GAM parametric term",log monthly asking rent (EUR/month),log,other,52966.0,0.898,se,"generalised additive model; only parametric (linear) terms extracted - size, age and all distance variables enter as smooth splines (edf reported, not coefficients); adj R2 0.898",elasticity,0.069,0.002,b (log-log),reported,0.14826372356909787,0.004297499233886895,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.5,52956.0,currency,,2022.0,Germany,Europe,High income,2013.0,2019.0,rental,rent,journal,True,False,OLS,XGBoost;permutation feature importance;partial dependence plots;accumulated local effects;H-statistic interactions,2016.0,other,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m1,3,Model 1,3,AREA,lot_size,A_structural,level,m2 (land area),0.0142,,9.426,,***,,,high,Land area of the property in m2,"LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7824,t,All 10 variables; adjusted R2 0.7739; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426)),semi_elasticity,1.4200000000000002,0.15064714619138553,100*b/1 (X per m2->m2),|b/t|,0.5278792386170951,0.05600246537418788,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.426,230.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m2,3,Model 2,3,AREA,lot_size,A_structural,level,m2 (land area),0.0143,,9.426,,***,,,high,Land area of the property in m2,"LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7918,t,USE dropped; adjusted R2 0.7846; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426)),semi_elasticity,1.43,0.1517080415870995,100*b/1 (X per m2->m2),|b/t|,0.5278792386170951,0.05600246537418788,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.426,230.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m3,3,Model 3,3,AREA,lot_size,A_structural,level,m2 (land area),0.0145,,9.864,,***,,,high,Land area of the property in m2,"LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7824,t,"USE, TERRACE dropped; adjusted R2 0.7758; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",semi_elasticity,1.4500000000000002,0.1469991889699919,100*b/1 (X per m2->m2),|b/t|,0.5452316507926622,0.055274903770545634,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.864,230.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m4,3,Model 4,3,AREA,lot_size,A_structural,level,m2 (land area),0.0141,,10.124,,***,,,high,Land area of the property in m2,"LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7784,t,"USE, TERRACE, NOF dropped; adjusted R2 0.7727; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",semi_elasticity,1.41,0.13927301461872776,100*b/1 (X per m2->m2),|b/t|,0.5552126230909014,0.05484123104414275,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.124,230.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m5,3,Model 5,3,AREA,lot_size,A_structural,level,m2 (land area),0.0148,,10.012,,***,,,high,"Land area of the property in m2; printed with typo '0,.0148'-style decimal separator","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7689,t,"USE, TERRACE, NOF, SHAPE dropped; adjusted R2 0.764; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",semi_elasticity,1.48,0.14782261286456252,100*b/1 (X per m2->m2),|b/t|,0.5509420345150962,0.055028169647932085,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.012,230.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,True
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m6,3,Model 6,3,AREA,lot_size,A_structural,level,m2 (land area),0.0146,,9.942,,***,,,high,"Land area of the property in m2; printed with typo '0,.0148'-style decimal separator","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7846,t,"Final model: AREA, HAREA, DIS1, DIS2, LOCATION only; adjusted R2 0.7809; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",semi_elasticity,1.46,0.1468517400925367,100*b/1 (X per m2->m2),|b/t|,0.5482507287844379,0.05514491337602474,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.942,230.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,True
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m1,3,Model 1,3,HAREA,living_area,A_structural,level,m2 (house/floor area),0.0008,,1.432,,,,,medium,House area in m2 (descriptive stats garbled: mean 2.780),"LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7824,t,All 10 variables; adjusted R2 0.7739; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426)),semi_elasticity,0.08,0.0558659217877095,100*b/1 (X per m2->m2),|b/t|,0.09400515020095578,0.065646054609606,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.432,230.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m2,3,Model 2,3,HAREA,living_area,A_structural,level,m2 (house/floor area),0.0008,,1.42,,,,,medium,House area in m2 (descriptive stats garbled: mean 2.780),"LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7918,t,USE dropped; adjusted R2 0.7846; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426)),semi_elasticity,0.08,0.056338028169014086,100*b/1 (X per m2->m2),|b/t|,0.0932242723927969,0.06565089605126544,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.42,230.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m3,3,Model 3,3,HAREA,living_area,A_structural,level,m2 (house/floor area),0.0008,,1.274,,,,,medium,House area in m2 (descriptive stats garbled: mean 2.780),"LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7824,t,"USE, TERRACE dropped; adjusted R2 0.7758; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",semi_elasticity,0.08,0.06279434850863422,100*b/1 (X per m2->m2),|b/t|,0.08371022622152519,0.0657066139886383,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.274,230.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m4,3,Model 4,3,HAREA,living_area,A_structural,level,m2 (house/floor area),0.0009,,2.524,,*,,,medium,House area in m2 (descriptive stats garbled: mean 2.780),"LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7784,t,"USE, TERRACE, NOF dropped; adjusted R2 0.7727; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",semi_elasticity,0.09,0.03565768621236133,100*b/1 (X per m2->m2),|b/t|,0.16416956363090401,0.06504340872856736,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.524,230.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m5,3,Model 5,3,HAREA,living_area,A_structural,level,m2 (house/floor area),0.0012,,2.788,,*,,,medium,"House area in m2 (descriptive stats garbled: mean 2.780); printed with typo '0,.0148'-style decimal separator","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7689,t,"USE, TERRACE, NOF, SHAPE dropped; adjusted R2 0.764; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",semi_elasticity,0.12,0.0430416068866571,100*b/1 (X per m2->m2),|b/t|,0.18080546443203704,0.06485131435869336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.788,230.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m6,3,Model 6,3,HAREA,living_area,A_structural,level,m2 (house/floor area),0.0012,,2.982,,*,,,medium,"House area in m2 (descriptive stats garbled: mean 2.780); printed with typo '0,.0148'-style decimal separator","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7846,t,"Final model: AREA, HAREA, DIS1, DIS2, LOCATION only; adjusted R2 0.7809; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",semi_elasticity,0.12,0.04024144869215291,100*b/1 (X per m2->m2),|b/t|,0.1929330106771,0.06469919875154258,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.982,230.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m1,3,Model 1,3,DIS1,cbd_distance,D_location,level,km,-0.045,,-1.984,,*,,,high,"Distance from property to Hanoi city centre, km","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7824,t,All 10 variables; adjusted R2 0.7739; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426)),semi_elasticity,-4.5,2.2681451612903225,100*b/1 (X per km->km),|b/t|,-0.1297158065328419,0.06538095087340821,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.984,230.0,km,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m2,3,Model 2,3,DIS1,cbd_distance,D_location,level,km,-0.065,,-1.928,,*,,,high,"Distance from property to Hanoi city centre, km","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7918,t,USE dropped; adjusted R2 0.7846; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426)),semi_elasticity,-6.5,3.3713692946058096,100*b/1 (X per km->km),|b/t|,-0.1261135372709713,0.06541158572145814,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.928,230.0,km,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m3,3,Model 3,3,DIS1,cbd_distance,D_location,level,km,-0.0665,,-1.948,,*,,,high,"Distance from property to Hanoi city centre, km","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7824,t,"USE, TERRACE dropped; adjusted R2 0.7758; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",semi_elasticity,-6.65,3.4137577002053385,100*b/1 (X per km->km),|b/t|,-0.12740064242800633,0.06540074046612233,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.948,230.0,km,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m4,3,Model 4,3,DIS1,cbd_distance,D_location,level,km,-0.0648,,-2.114,,*,,,high,"Distance from property to Hanoi city centre, km","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7784,t,"USE, TERRACE, NOF dropped; adjusted R2 0.7727; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",semi_elasticity,-6.4799999999999995,3.0652790917691584,100*b/1 (X per km->km),|b/t|,-0.13805822044457158,0.06530663218759299,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.114,230.0,km,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m5,3,Model 5,3,DIS1,cbd_distance,D_location,level,km,-0.0684,,-2.682,,*,,,high,"Distance from property to Hanoi city centre, km","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7689,t,"USE, TERRACE, NOF, SHAPE dropped; adjusted R2 0.764; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",semi_elasticity,-6.84,2.550335570469799,100*b/1 (X per km->km),|b/t|,-0.17414368330670243,0.06493053068855423,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.682,230.0,km,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m6,3,Model 6,3,DIS1,cbd_distance,D_location,level,km,-0.084,,-2.683,,*,,,high,"Distance from property to Hanoi city centre, km","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7846,t,"Final model: AREA, HAREA, DIS1, DIS2, LOCATION only; adjusted R2 0.7809; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",semi_elasticity,-8.4,3.130823704808051,100*b/1 (X per km->km),|b/t|,-0.17420664368466754,0.06492979637892939,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.683,230.0,km,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m1,3,Model 1,3,NOF,storeys,A_structural,dummy,"binary (1 = number of floors <= 4, 0 = > 4)",-0.1193,,-0.742,,,,,high,"Number of floors entered as a dummy (<=4 floors), not a count","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7824,t,All 10 variables; adjusted R2 0.7739; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426)),pct_premium,-12.385648616931988,14.270040533076951,100*(exp(b - se^2/2) - 1),|b/t|,-0.04886757754474413,0.06585926892822658,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.742,230.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m2,3,Model 2,3,NOF,storeys,A_structural,dummy,"binary (1 = number of floors <= 4, 0 = > 4)",-0.1428,,-0.846,,,,,high,"Number of floors entered as a dummy (<=4 floors), not a count","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7918,t,USE dropped; adjusted R2 0.7846; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426)),pct_premium,-14.533505349861608,14.633243263604982,100*(exp(b - se^2/2) - 1),|b/t|,-0.05569699616281447,0.06583569286384688,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.846,230.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m3,3,Model 3,3,NOF,storeys,A_structural,dummy,"binary (1 = number of floors <= 4, 0 = > 4)",-0.1464,,-0.846,,,,,high,"Number of floors entered as a dummy (<=4 floors), not a count","LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7824,t,"USE, TERRACE dropped; adjusted R2 0.7758; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426))",pct_premium,-14.902547811271749,14.948237918534149,100*(exp(b - se^2/2) - 1),|b/t|,-0.05569699616281447,0.06583569286384688,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.846,230.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m1,3,Model 1,3,TERRACE,terrace_balcony,C_exterior,binary,binary,-0.0426,,-0.492,,,,,high,Terrace dummy,"LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7824,t,All 10 variables; adjusted R2 0.7739; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426)),pct_premium,-4.529082415458396,8.297429124377965,100*(exp(b - se^2/2) - 1),|b/t|,-0.03242446118077492,0.06590337638368886,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.492,230.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f,7de41ea5f998e11b3cc730af7771c0a4b73baa2f:T3-m2,3,Model 2,3,TERRACE,terrace_balcony,C_exterior,binary,binary,-0.0428,,-0.548,,,,,high,Terrace dummy,"LogPRICE: natural log of real estate price (VND; scale not stated, mean 8.20)",log,OLS,240.0,0.7918,t,USE dropped; adjusted R2 0.7846; table note says 'Robust standard errors in parentheses' but the parenthesised values are t-statistics (e.g. 0.0142 with (9.426)),pct_premium,-4.481474786895823,7.48299416722531,100*(exp(b - se^2/2) - 1),|b/t|,-0.03611048345247726,0.06589504279649136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.548,230.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2021.0,2021.0,unknown,transaction,journal,False,False,robust,,2021.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T4-log,4,Log-linear model,7,House age,age,A_structural,level,years,0.0018017,0.0008823,2.04,,*,,,high,,log monthly house rent (PKR),log,OLS,163.0,0.9466,none,Houses around existing (unimproved) slum sites,semi_elasticity,0.18017,0.08823,100*b/1 (per year),reported,0.16272599908685828,0.07976764661120504,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.04,153.0,years,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T5-log,5,Log-linear model,8,House age,age,A_structural,level,years,0.0045487,0.0010464,-4.35,,**,,,medium,printed coefficient sign disagrees with printed t-value sign,log monthly house rent (PKR),log,OLS,173.0,0.9193,none,Houses around upgraded slum sites,semi_elasticity,0.45487,0.10464000000000001,100*b/1 (per year),reported,-0.322512126789416,0.07414071880216459,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.35,163.0,years,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T6-log,6,Log-linear model,9,House age,age,A_structural,level,years,0.0013215,0.0010493,-1.26,,,,,medium,printed coefficient sign disagrees with printed t-value sign,log monthly house rent (PKR),log,OLS,168.0,0.8683,none,Houses around evicted/demolished slum sites,semi_elasticity,0.13215,0.10493,100*b/1 (per year),reported,-0.0997403696318052,0.07915902351730572,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.26,158.0,years,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T4-log,4,Log-linear model,7,Bedrooms,bedrooms,A_structural,level,count,0.0420453,0.0145349,2.89,,**,,,high,,log monthly house rent (PKR),log,OLS,163.0,0.9466,none,Houses around existing (unimproved) slum sites,semi_elasticity,4.20453,1.45349,100*b/1 (per unit count),reported,0.22751526028282973,0.07872500355807256,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.89,153.0,count,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T5-log,5,Log-linear model,8,Bedrooms,bedrooms,A_structural,level,count,0.0488116,0.0163849,2.98,,**,,,high,,log monthly house rent (PKR),log,OLS,173.0,0.9193,none,Houses around upgraded slum sites,semi_elasticity,4.8811599999999995,1.63849,100*b/1 (per unit count),reported,0.22730191059781765,0.07627580892544217,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.98,163.0,count,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T6-log,6,Log-linear model,9,Bedrooms,bedrooms,A_structural,level,count,0.0443812,0.0113403,3.91,,**,,,high,,log monthly house rent (PKR),log,OLS,168.0,0.8683,none,Houses around evicted/demolished slum sites,semi_elasticity,4.4381200000000005,1.1340299999999999,100*b/1 (per unit count),reported,0.29702457792147885,0.07596536519730918,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.91,158.0,count,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T4-log,4,Log-linear model,7,Bathrooms,bathrooms,A_structural,level,count,0.0181466,0.0162802,1.11,,,,,high,,log monthly house rent (PKR),log,OLS,163.0,0.9466,none,Houses around existing (unimproved) slum sites,semi_elasticity,1.81466,1.6280200000000002,100*b/1 (per unit count),reported,0.08937902088908324,0.08052164044061552,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.11,153.0,count,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T5-log,5,Log-linear model,8,Bathrooms,bathrooms,A_structural,level,count,0.0122106,0.0154639,0.79,,,,,high,,log monthly house rent (PKR),log,OLS,173.0,0.9193,none,Houses around upgraded slum sites,semi_elasticity,1.22106,1.54639,100*b/1 (per unit count),reported,0.06175945514506461,0.07817652550008178,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.79,163.0,count,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T6-log,6,Log-linear model,9,Bathrooms,bathrooms,A_structural,level,count,0.0222714,0.0126296,1.76,,,,,high,,log monthly house rent (PKR),log,OLS,168.0,0.8683,none,Houses around evicted/demolished slum sites,semi_elasticity,2.22714,1.2629599999999999,100*b/1 (per unit count),reported,0.13866540760576157,0.07878716341236454,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.76,158.0,count,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T4-log,4,Log-linear model,7,Garage,garage,A_structural,dummy,binary,0.0537868,0.0185684,2.9,,**,,,high,Garage/parking space dummy,log monthly house rent (PKR),log,OLS,163.0,0.9466,none,Houses around existing (unimproved) slum sites,pct_premium,5.5077693411637485,1.9594482297672722,100*(exp(b - se^2/2) - 1),reported,0.2282615590111986,0.0787108824176547,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9,153.0,binary,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T5-log,5,Log-linear model,8,Garage,garage,A_structural,dummy,binary,0.0643446,0.0260102,2.47,,*,,,high,Garage/parking space dummy,log monthly house rent (PKR),log,OLS,173.0,0.9193,none,Houses around upgraded slum sites,pct_premium,6.609915220956553,2.773883366555522,100*(exp(b - se^2/2) - 1),reported,0.18994330645012425,0.0769001240688762,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.47,163.0,binary,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T6-log,6,Log-linear model,9,Garage,garage,A_structural,dummy,binary,0.0337009,0.0144664,2.33,,*,,,high,Garage/parking space dummy,log monthly house rent (PKR),log,OLS,168.0,0.8683,none,Houses around evicted/demolished slum sites,pct_premium,3.4166989540794113,1.4962238879788965,100*(exp(b - se^2/2) - 1),reported,0.18226005300227388,0.07822319871342226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.33,158.0,binary,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T4-log,4,Log-linear model,7,Lawn,garden,C_exterior,dummy,binary,0.0913645,0.0178169,5.13,,**,,,high,Dummy: presence of a lawn,log monthly house rent (PKR),log,OLS,163.0,0.9466,none,Houses around existing (unimproved) slum sites,pct_premium,9.549441185101749,1.9521412598029204,100*(exp(b - se^2/2) - 1),reported,0.3830952383473862,0.07467743437570881,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.13,153.0,binary,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T5-log,5,Log-linear model,8,Lawn,garden,C_exterior,dummy,binary,0.0558746,0.0248359,2.25,,*,,,high,Dummy: presence of a lawn,log monthly house rent (PKR),log,OLS,173.0,0.9193,none,Houses around upgraded slum sites,pct_premium,5.713898576677501,2.626309671468175,100*(exp(b - se^2/2) - 1),reported,0.17355898767151737,0.07713732785400773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.25,163.0,binary,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T6-log,6,Log-linear model,9,Lawn,garden,C_exterior,dummy,binary,0.0295001,0.013772,2.14,,*,,,high,Dummy: presence of a lawn,log monthly house rent (PKR),log,OLS,168.0,0.8683,none,Houses around evicted/demolished slum sites,pct_premium,2.9841869819116074,1.4184327323751555,100*(exp(b - se^2/2) - 1),reported,0.16783431021534648,0.0784272477641806,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.14,158.0,binary,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T4-log,4,Log-linear model,7,Distance to CBD,cbd_distance,D_location,level,km,0.0122385,0.0037342,3.28,,**,,,high,Distance from home to city centre (km); printed sign positive in all tables although expected negative and t-values negative in Tables 5-6,log monthly house rent (PKR),log,OLS,163.0,0.9466,none,Houses around existing (unimproved) slum sites,semi_elasticity,1.2238499999999999,0.37342,100*b/1 (X per km->km),reported,0.2563138361018776,0.07814446222618218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.28,153.0,km,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T5-log,5,Log-linear model,8,Distance to CBD,cbd_distance,D_location,level,km,0.1300239,0.0184405,-7.05,,**,,,medium,Distance from home to city centre (km); printed sign positive in all tables although expected negative and t-values negative in Tables 5-6; printed coefficient sign disagrees with printed t-value sign,log monthly house rent (PKR),log,OLS,173.0,0.9193,none,Houses around upgraded slum sites,semi_elasticity,13.00239,1.8440499999999997,100*b/1 (X per km->km),reported,-0.48339574109390737,0.06856677178636984,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.05,163.0,km,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,True
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T6-log,6,Log-linear model,9,Distance to CBD,cbd_distance,D_location,level,km,0.0184054,0.0090552,-2.03,,*,,,medium,Distance from home to city centre (km); printed sign positive in all tables although expected negative and t-values negative in Tables 5-6; printed coefficient sign disagrees with printed t-value sign,log monthly house rent (PKR),log,OLS,168.0,0.8683,none,Houses around evicted/demolished slum sites,semi_elasticity,1.8405399999999998,0.9055199999999999,100*b/1 (X per km->km),reported,-0.15943238206501587,0.0785381192438502,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.03,158.0,km,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T4-log,4,Log-linear model,7,Distance to school,school_distance,D_location,level,km,0.0751735,0.0418278,1.8,,,,,high,,log monthly house rent (PKR),log,OLS,163.0,0.9466,none,Houses around existing (unimproved) slum sites,semi_elasticity,7.51735,4.18278,100*b/1 (X per km->km),reported,0.1440046082211958,0.08000256012288656,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8,153.0,km,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T5-log,5,Log-linear model,8,Distance to school,school_distance,D_location,level,km,0.0511055,0.0245488,-2.08,,*,,,medium,printed coefficient sign disagrees with printed t-value sign,log monthly house rent (PKR),log,OLS,173.0,0.9193,none,Houses around upgraded slum sites,semi_elasticity,5.11055,2.4548799999999997,100*b/1 (X per km->km),reported,-0.160798169784715,0.0773068123964976,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.08,163.0,km,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T6-log,6,Log-linear model,9,Distance to school,school_distance,D_location,level,km,-0.0361071,0.0188677,-1.91,,,,,high,,log monthly house rent (PKR),log,OLS,168.0,0.8683,none,Houses around evicted/demolished slum sites,semi_elasticity,-3.61071,1.88677,100*b/1 (X per km->km),reported,-0.15022702439526833,0.07865289235354363,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.91,158.0,km,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T4-log,4,Log-linear model,7,Distance to park,green_space,E_environment,level,km,0.1086817,0.0262206,4.14,,**,,,high,Distance from housing unit to park (km),log monthly house rent (PKR),log,OLS,163.0,0.9466,none,Houses around existing (unimproved) slum sites,semi_elasticity,10.868170000000001,2.62206,100*b/1 (X per km->km),reported,0.3173932142056196,0.07666502758589847,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.14,153.0,km,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T5-log,5,Log-linear model,8,Distance to park,green_space,E_environment,level,km,0.086923,0.0276121,-3.15,,**,,,medium,Distance from housing unit to park (km); printed coefficient sign disagrees with printed t-value sign,log monthly house rent (PKR),log,OLS,173.0,0.9193,none,Houses around upgraded slum sites,semi_elasticity,8.6923,2.76121,100*b/1 (X per km->km),reported,-0.23954372623574144,0.07604562737642585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.15,163.0,km,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T6-log,6,Log-linear model,9,Distance to park,green_space,E_environment,level,km,-0.0778371,0.0301056,-2.59,,*,,,high,Distance from housing unit to park (km),log monthly house rent (PKR),log,OLS,168.0,0.8683,none,Houses around evicted/demolished slum sites,semi_elasticity,-7.783710000000001,3.01056,100*b/1 (X per km->km),reported,-0.20180981551282587,0.07791884768834975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.59,158.0,km,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T4-log,4,Log-linear model,7,Distance to slums,hazard_site,E_environment,level,km,0.1864864,0.0428089,4.36,,**,,,high,Distance to existing (unimproved) slum site (km),log monthly house rent (PKR),log,OLS,163.0,0.9466,none,Houses around existing (unimproved) slum sites,semi_elasticity,18.64864,4.280889999999999,100*b/1 (X per km->km),reported,0.3324376061259826,0.07624715736834464,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.36,153.0,km,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,True
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T5-log,5,Log-linear model,8,Distance to upgraded slums,hazard_site,E_environment,level,km,0.1258162,0.0472052,2.67,,**,,,high,Distance to government-upgraded slum site (km),log monthly house rent (PKR),log,OLS,173.0,0.9193,none,Houses around upgraded slum sites,semi_elasticity,12.58162,4.7205200000000005,100*b/1 (X per km->km),reported,0.20470206056405732,0.07666743841350461,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.67,163.0,km,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T6-log,6,Log-linear model,9,Distance to evicted slums,hazard_site,E_environment,level,km,0.0792828,0.0408651,1.94,,*,,,high,Distance to evicted/demolished slum site (km),log monthly house rent (PKR),log,OLS,168.0,0.8683,none,Houses around evicted/demolished slum sites,semi_elasticity,7.92828,4.0865100000000005,100*b/1 (X per km->km),reported,0.1525321276461744,0.07862480806503837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.94,158.0,km,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T4-log,4,Log-linear model,7,Visibility,hazard_site,E_environment,dummy,binary,0.151787,0.0322262,4.71,,**,,,high,Dummy: slum site visible from the house; Table 4 printed positive although text reports a ~15% rent discount,log monthly house rent (PKR),log,OLS,163.0,0.9466,none,Houses around existing (unimproved) slum sites,pct_premium,16.330807586160123,3.750847045618006,100*(exp(b - se^2/2) - 1),reported,0.3558554028352483,0.07555316408391685,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.71,153.0,binary,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T5-log,5,Log-linear model,8,Visibility,hazard_site,E_environment,dummy,binary,-0.1080642,0.0330988,-3.26,,**,,,high,Dummy: slum site visible from the house; Table 4 printed positive although text reports a ~15% rent discount,log monthly house rent (PKR),log,OLS,173.0,0.9193,none,Houses around upgraded slum sites,pct_premium,-10.292155244643531,2.970848894251641,100*(exp(b - se^2/2) - 1),reported,-0.2474048556487383,0.0758910600149504,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.26,163.0,binary,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,7e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8:T6-log,6,Log-linear model,9,Visibility,hazard_site,E_environment,dummy,binary,-0.0676483,0.0295386,-2.29,,*,,,high,Dummy: slum site visible from the house; Table 4 printed positive although text reports a ~15% rent discount,log monthly house rent (PKR),log,OLS,168.0,0.8683,none,Houses around evicted/demolished slum sites,pct_premium,-6.581852830077917,2.7606453907486252,100*(exp(b - se^2/2) - 1),reported,-0.17923248880455112,0.07826746236006597,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.29,158.0,binary,,2021.0,Pakistan,Asia,Lower middle income,,,single_family,rent,journal,False,False,unknown,,2018.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,Rooms,bedrooms,A_structural,level,count,0.012,0.004,,,***,,,high,"Total rooms, mapped to bedrooms (closest leaf, synonym 'rooms'); bedrooms entered separately",LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,1.2,0.4,100*b/1 (per unit count),reported,0.022110286009454527,0.007370095336484842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,Rooms,bedrooms,A_structural,level,count,0.012,0.004,,,***,,,high,"Total rooms, mapped to bedrooms (closest leaf, synonym 'rooms'); bedrooms entered separately",LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,1.2,0.4,100*b/1 (per unit count),reported,0.022110286009454527,0.007370095336484842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,Rooms,bedrooms,A_structural,level,count,0.012,0.004,,,***,,,high,"Total rooms, mapped to bedrooms (closest leaf, synonym 'rooms'); bedrooms entered separately",LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,1.2,0.4,100*b/1 (per unit count),reported,0.022110286009454527,0.007370095336484842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,Rooms,bedrooms,A_structural,level,count,0.012,0.004,,,***,,,high,"Total rooms, mapped to bedrooms (closest leaf, synonym 'rooms'); bedrooms entered separately",LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,1.2,0.4,100*b/1 (per unit count),reported,0.022110286009454527,0.007370095336484842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,Rooms,bedrooms,A_structural,level,count,0.012,0.004,,,***,,,high,"Total rooms, mapped to bedrooms (closest leaf, synonym 'rooms'); bedrooms entered separately",LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,1.2,0.4,100*b/1 (per unit count),reported,0.022110286009454527,0.007370095336484842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,Rooms,bedrooms,A_structural,level,count,0.012,0.004,,,***,,,high,"Total rooms, mapped to bedrooms (closest leaf, synonym 'rooms'); bedrooms entered separately",LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,1.2,0.4,100*b/1 (per unit count),reported,0.022110286009454527,0.007370095336484842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,Bedrooms,bedrooms,A_structural,level,count,0.006,0.011,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,0.6,1.0999999999999999,100*b/1 (per unit count),reported,0.004021002485894134,0.007371837890805911,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5454545454545455,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,Bedrooms,bedrooms,A_structural,level,count,0.006,0.011,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,0.6,1.0999999999999999,100*b/1 (per unit count),reported,0.004021002485894134,0.007371837890805911,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5454545454545455,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,Bedrooms,bedrooms,A_structural,level,count,0.006,0.011,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,0.6,1.0999999999999999,100*b/1 (per unit count),reported,0.004021002485894134,0.007371837890805911,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5454545454545455,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,Bedrooms,bedrooms,A_structural,level,count,0.006,0.011,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,0.6,1.0999999999999999,100*b/1 (per unit count),reported,0.004021002485894134,0.007371837890805911,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5454545454545455,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,Bedrooms,bedrooms,A_structural,level,count,0.006,0.011,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,0.6,1.0999999999999999,100*b/1 (per unit count),reported,0.004021002485894134,0.007371837890805911,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5454545454545455,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,Bedrooms,bedrooms,A_structural,level,count,0.007,0.011,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,0.7000000000000001,1.0999999999999999,100*b/1 (per unit count),reported,0.004691155871979544,0.007371816370253567,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6363636363636365,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,Full baths,bathrooms,A_structural,level,count,0.125,0.021,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,12.5,2.1,100*b/1 (per unit count),reported,0.04383815763717279,0.00736481048304503,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.952380952380952,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,Full baths,bathrooms,A_structural,level,count,0.125,0.021,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,12.5,2.1,100*b/1 (per unit count),reported,0.04383815763717279,0.00736481048304503,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.952380952380952,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,Full baths,bathrooms,A_structural,level,count,0.125,0.021,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,12.5,2.1,100*b/1 (per unit count),reported,0.04383815763717279,0.00736481048304503,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.952380952380952,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,Full baths,bathrooms,A_structural,level,count,0.125,0.021,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,12.5,2.1,100*b/1 (per unit count),reported,0.04383815763717279,0.00736481048304503,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.952380952380952,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,Full baths,bathrooms,A_structural,level,count,0.124,0.021,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,12.4,2.1,100*b/1 (per unit count),reported,0.04348811830496353,0.0073649232613244705,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.904761904761904,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,Full baths,bathrooms,A_structural,level,count,0.124,0.021,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,12.4,2.1,100*b/1 (per unit count),reported,0.04348811830496353,0.0073649232613244705,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.904761904761904,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,Half baths,bathrooms,A_structural,level,count,0.034,0.015,,,**,,,high,half bathrooms,LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,3.4000000000000004,1.5,100*b/1 (per unit count),reported,0.016707302028437038,0.0073708685419575145,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.266666666666667,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,Half baths,bathrooms,A_structural,level,count,0.033,0.015,,,**,,,high,half bathrooms,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,3.3000000000000003,1.5,100*b/1 (per unit count),reported,0.01621604196584575,0.007370928166293523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,Half baths,bathrooms,A_structural,level,count,0.033,0.015,,,**,,,high,half bathrooms,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,3.3000000000000003,1.5,100*b/1 (per unit count),reported,0.01621604196584575,0.007370928166293523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,Half baths,bathrooms,A_structural,level,count,0.033,0.015,,,**,,,high,half bathrooms,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,3.3000000000000003,1.5,100*b/1 (per unit count),reported,0.01621604196584575,0.007370928166293523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,Half baths,bathrooms,A_structural,level,count,0.033,0.015,,,**,,,high,half bathrooms,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,3.3000000000000003,1.5,100*b/1 (per unit count),reported,0.01621604196584575,0.007370928166293523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,Half baths,bathrooms,A_structural,level,count,0.033,0.015,,,**,,,high,half bathrooms,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,3.3000000000000003,1.5,100*b/1 (per unit count),reported,0.01621604196584575,0.007370928166293523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,Fireplaces,fireplace,B_interior,level,count,0.086,0.012,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,8.6,1.2,100*b/1 (per unit count),reported,0.05275835339702551,0.007361630706561699,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.166666666666666,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,Fireplaces,fireplace,B_interior,level,count,0.086,0.012,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,8.6,1.2,100*b/1 (per unit count),reported,0.05275835339702551,0.007361630706561699,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.166666666666666,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,Fireplaces,fireplace,B_interior,level,count,0.086,0.012,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,8.6,1.2,100*b/1 (per unit count),reported,0.05275835339702551,0.007361630706561699,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.166666666666666,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,Fireplaces,fireplace,B_interior,level,count,0.086,0.012,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,8.6,1.2,100*b/1 (per unit count),reported,0.05275835339702551,0.007361630706561699,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.166666666666666,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,Fireplaces,fireplace,B_interior,level,count,0.086,0.012,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,8.6,1.2,100*b/1 (per unit count),reported,0.05275835339702551,0.007361630706561699,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.166666666666666,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,Fireplaces,fireplace,B_interior,level,count,0.086,0.012,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,8.6,1.2,100*b/1 (per unit count),reported,0.05275835339702551,0.007361630706561699,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.166666666666666,18401.0,count,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,Acreage,lot_size,A_structural,level,acres,0.007,0.019,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,0.00017297376702701575,0.0004695002247876141,100*b/4046.86 (X per acre->m2),reported,0.0027159522150879915,0.007371870298095975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.368421052631579,18401.0,acre,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,Acreage,lot_size,A_structural,level,acres,0.006,0.019,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,0.0001482632288802992,0.0004695002247876141,100*b/4046.86 (X per acre->m2),reported,0.002327961319418908,0.007371877511493207,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.31578947368421056,18401.0,acre,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,Acreage,lot_size,A_structural,level,acres,0.007,0.019,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,0.00017297376702701575,0.0004695002247876141,100*b/4046.86 (X per acre->m2),reported,0.0027159522150879915,0.007371870298095975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.368421052631579,18401.0,acre,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,Acreage,lot_size,A_structural,level,acres,0.007,0.019,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,0.00017297376702701575,0.0004695002247876141,100*b/4046.86 (X per acre->m2),reported,0.0027159522150879915,0.007371870298095975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.368421052631579,18401.0,acre,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,Acreage,lot_size,A_structural,level,acres,0.007,0.019,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,0.00017297376702701575,0.0004695002247876141,100*b/4046.86 (X per acre->m2),reported,0.0027159522150879915,0.007371870298095975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.368421052631579,18401.0,acre,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,Acreage,lot_size,A_structural,level,acres,0.007,0.019,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,0.00017297376702701575,0.0004695002247876141,100*b/4046.86 (X per acre->m2),reported,0.0027159522150879915,0.007371870298095975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.368421052631579,18401.0,acre,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,Property age,age,A_structural,level,years,0.039,0.001,,,***,,,high,positive sign as printed; year built also included in the same model,LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,3.9,0.1,100*b/1 (per year),reported,0.2763109774319011,0.007084896857228233,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),39.0,18401.0,years,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,Property age,age,A_structural,level,years,0.039,0.001,,,***,,,high,positive sign as printed; year built also included in the same model,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,3.9,0.1,100*b/1 (per year),reported,0.2763109774319011,0.007084896857228233,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),39.0,18401.0,years,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,Property age,age,A_structural,level,years,0.039,0.001,,,***,,,high,positive sign as printed; year built also included in the same model,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,3.9,0.1,100*b/1 (per year),reported,0.2763109774319011,0.007084896857228233,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),39.0,18401.0,years,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,Property age,age,A_structural,level,years,0.039,0.001,,,***,,,high,positive sign as printed; year built also included in the same model,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,3.9,0.1,100*b/1 (per year),reported,0.2763109774319011,0.007084896857228233,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),39.0,18401.0,years,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,Property age,age,A_structural,level,years,0.042,0.001,,,***,,,high,positive sign as printed; year built also included in the same model,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,4.2,0.1,100*b/1 (per year),reported,0.2957673139345615,0.007042078903203845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.0,18401.0,years,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,Property age,age,A_structural,level,years,0.042,0.001,,,***,,,high,positive sign as printed; year built also included in the same model,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",semi_elasticity,4.2,0.1,100*b/1 (per year),reported,0.2957673139345615,0.007042078903203845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.0,18401.0,years,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,Carport,garage,A_structural,binary,binary,0.066,0.017,,,***,,,high,carport indicator,LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,6.807236955724605,1.8159854191821887,100*(exp(b - se^2/2) - 1),reported,0.028608593325339986,0.007368880098951208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8823529411764706,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,Carport,garage,A_structural,binary,binary,0.066,0.017,,,***,,,high,carport indicator,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,6.807236955724605,1.8159854191821887,100*(exp(b - se^2/2) - 1),reported,0.028608593325339986,0.007368880098951208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8823529411764706,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,Carport,garage,A_structural,binary,binary,0.066,0.017,,,***,,,high,carport indicator,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,6.807236955724605,1.8159854191821887,100*(exp(b - se^2/2) - 1),reported,0.028608593325339986,0.007368880098951208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8823529411764706,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,Carport,garage,A_structural,binary,binary,0.066,0.017,,,***,,,high,carport indicator,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,6.807236955724605,1.8159854191821887,100*(exp(b - se^2/2) - 1),reported,0.028608593325339986,0.007368880098951208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8823529411764706,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,Carport,garage,A_structural,binary,binary,0.066,0.017,,,***,,,high,carport indicator,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,6.807236955724605,1.8159854191821887,100*(exp(b - se^2/2) - 1),reported,0.028608593325339986,0.007368880098951208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8823529411764706,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,Carport,garage,A_structural,binary,binary,0.065,0.017,,,***,,,high,carport indicator,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,6.7004831045906155,1.8141703414531276,100*(exp(b - se^2/2) - 1),reported,0.028175476543229556,0.00736897078822927,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8235294117647056,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,Covered garage,garage,A_structural,binary,binary,0.074,0.008,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,7.677234822976331,0.8614454443969759,100*(exp(b - se^2/2) - 1),reported,0.06803206462294246,0.007354817797074861,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.25,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,Covered garage,garage,A_structural,binary,binary,0.073,0.008,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,7.569611408829036,0.8605844295317628,100*(exp(b - se^2/2) - 1),reported,0.06711688201818963,0.007355274741719412,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.125,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,Covered garage,garage,A_structural,binary,binary,0.073,0.008,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,7.569611408829036,0.8605844295317628,100*(exp(b - se^2/2) - 1),reported,0.06711688201818963,0.007355274741719412,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.125,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,Covered garage,garage,A_structural,binary,binary,0.073,0.008,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,7.569611408829036,0.8605844295317628,100*(exp(b - se^2/2) - 1),reported,0.06711688201818963,0.007355274741719412,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.125,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,Covered garage,garage,A_structural,binary,binary,0.073,0.008,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,7.569611408829036,0.8605844295317628,100*(exp(b - se^2/2) - 1),reported,0.06711688201818963,0.007355274741719412,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.125,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,Covered garage,garage,A_structural,binary,binary,0.073,0.008,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,7.569611408829036,0.8605844295317628,100*(exp(b - se^2/2) - 1),reported,0.06711688201818963,0.007355274741719412,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.125,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,No pool,pool,C_exterior,binary,binary,0.088,0.04,,,**,,,high,"indicator for no pool, printed together with in-ground and above-ground pool indicators (reference category unclear)",LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,9.111488087360954,4.36795248811279,100*(exp(b - se^2/2) - 1),reported,0.016216041965845748,0.007370928166293523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1999999999999997,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,No pool,pool,C_exterior,binary,binary,0.089,0.04,,,**,,,high,"indicator for no pool, printed together with in-ground and above-ground pool indicators (reference category unclear)",LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,9.220654149382156,4.372322625305321,100*(exp(b - se^2/2) - 1),reported,0.01640026588464889,0.0073709060155725354,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2249999999999996,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,No pool,pool,C_exterior,binary,binary,0.089,0.04,,,**,,,high,"indicator for no pool, printed together with in-ground and above-ground pool indicators (reference category unclear)",LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,9.220654149382156,4.372322625305321,100*(exp(b - se^2/2) - 1),reported,0.01640026588464889,0.0073709060155725354,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2249999999999996,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,No pool,pool,C_exterior,binary,binary,0.089,0.04,,,**,,,high,"indicator for no pool, printed together with in-ground and above-ground pool indicators (reference category unclear)",LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,9.220654149382156,4.372322625305321,100*(exp(b - se^2/2) - 1),reported,0.01640026588464889,0.0073709060155725354,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2249999999999996,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,No pool,pool,C_exterior,binary,binary,0.088,0.04,,,**,,,high,"indicator for no pool, printed together with in-ground and above-ground pool indicators (reference category unclear)",LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,9.111488087360954,4.36795248811279,100*(exp(b - se^2/2) - 1),reported,0.016216041965845748,0.007370928166293523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1999999999999997,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,No pool,pool,C_exterior,binary,binary,0.089,0.04,,,**,,,high,"indicator for no pool, printed together with in-ground and above-ground pool indicators (reference category unclear)",LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,9.220654149382156,4.372322625305321,100*(exp(b - se^2/2) - 1),reported,0.01640026588464889,0.0073709060155725354,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2249999999999996,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,In-ground pool,pool,C_exterior,binary,binary,0.105,0.04,,,**,,,high,reference category unclear (no-pool indicator also reported),LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,10.982239720005428,4.442842441422821,100*(exp(b - se^2/2) - 1),reported,0.01934760869203614,0.007370517596966148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.625,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,In-ground pool,pool,C_exterior,binary,binary,0.106,0.039,,,**,,,high,reference category unclear (no-pool indicator also reported),LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,11.097665740474794,4.336105318375471,100*(exp(b - se^2/2) - 1),reported,0.0200324186312036,0.007370418175631514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.717948717948718,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,In-ground pool,pool,C_exterior,binary,binary,0.106,0.04,,,**,,,high,reference category unclear (no-pool indicator also reported),LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,11.093277469346962,4.447287506026123,100*(exp(b - se^2/2) - 1),reported,0.019531801668709634,0.0073704911957394835,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.65,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,In-ground pool,pool,C_exterior,binary,binary,0.106,0.04,,,**,,,high,reference category unclear (no-pool indicator also reported),LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,11.093277469346962,4.447287506026123,100*(exp(b - se^2/2) - 1),reported,0.019531801668709634,0.0073704911957394835,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.65,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,In-ground pool,pool,C_exterior,binary,binary,0.106,0.039,,,**,,,high,reference category unclear (no-pool indicator also reported),LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,11.097665740474794,4.336105318375471,100*(exp(b - se^2/2) - 1),reported,0.0200324186312036,0.007370418175631514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.717948717948718,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,In-ground pool,pool,C_exterior,binary,binary,0.107,0.04,,,**,,,high,reference category unclear (no-pool indicator also reported),LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,11.204426311975224,4.451737017917303,100*(exp(b - se^2/2) - 1),reported,0.019715992656676538,0.0073704645445519775,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.675,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,Above ground pool,pool,C_exterior,binary,binary,0.124,0.044,,,***,,,high,reference category unclear,LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,13.092060982797872,4.980869832396371,100*(exp(b - se^2/2) - 1),reported,0.020770865438215227,0.0073703070909795975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8181818181818183,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,Above ground pool,pool,C_exterior,binary,binary,0.122,0.044,,,***,,,high,reference category unclear,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,12.866102894240194,4.970918047833402,100*(exp(b - se^2/2) - 1),reported,0.020435992537675172,0.007370357964407439,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.772727272727273,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,Above ground pool,pool,C_exterior,binary,binary,0.122,0.044,,,***,,,high,reference category unclear,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,12.866102894240194,4.970918047833402,100*(exp(b - se^2/2) - 1),reported,0.020435992537675172,0.007370357964407439,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.772727272727273,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,Above ground pool,pool,C_exterior,binary,binary,0.123,0.044,,,***,,,high,reference category unclear,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,12.979025449001602,4.975891452168953,100*(exp(b - se^2/2) - 1),reported,0.020603429854737797,0.0073703326309631145,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7954545454545454,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,Above ground pool,pool,C_exterior,binary,binary,0.122,0.044,,,***,,,high,reference category unclear,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,12.866102894240194,4.970918047833402,100*(exp(b - se^2/2) - 1),reported,0.020435992537675172,0.007370357964407439,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.772727272727273,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,Above ground pool,pool,C_exterior,binary,binary,0.122,0.044,,,***,,,high,reference category unclear,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,12.866102894240194,4.970918047833402,100*(exp(b - se^2/2) - 1),reported,0.020435992537675172,0.007370357964407439,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.772727272727273,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,Townhouse,dwelling_type,A_structural,binary,binary,-0.213,0.022,,,***,,,high,townhouse vs other,LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,-19.203941290619888,1.7779435018762744,100*(exp(b - se^2/2) - 1),reported,-0.0711922691358488,0.007353192117317717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.681818181818182,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,Townhouse,dwelling_type,A_structural,binary,binary,-0.21,0.022,,,***,,,high,townhouse vs other,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,-18.96118916837244,1.7832853411344116,100*(exp(b - se^2/2) - 1),reported,-0.07019453684973942,0.007353713384258415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.545454545454545,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,Townhouse,dwelling_type,A_structural,binary,binary,-0.21,0.022,,,***,,,high,townhouse vs other,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,-18.96118916837244,1.7832853411344116,100*(exp(b - se^2/2) - 1),reported,-0.07019453684973942,0.007353713384258415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.545454545454545,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,Townhouse,dwelling_type,A_structural,binary,binary,-0.21,0.022,,,***,,,high,townhouse vs other,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,-18.96118916837244,1.7832853411344116,100*(exp(b - se^2/2) - 1),reported,-0.07019453684973942,0.007353713384258415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.545454545454545,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,Townhouse,dwelling_type,A_structural,binary,binary,-0.21,0.022,,,***,,,high,townhouse vs other,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,-18.96118916837244,1.7832853411344116,100*(exp(b - se^2/2) - 1),reported,-0.07019453684973942,0.007353713384258415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.545454545454545,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,Townhouse,dwelling_type,A_structural,binary,binary,-0.21,0.022,,,***,,,high,townhouse vs other,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,-18.96118916837244,1.7832853411344116,100*(exp(b - se^2/2) - 1),reported,-0.07019453684973942,0.007353713384258415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.545454545454545,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,Condominium,dwelling_type,A_structural,binary,binary,-0.458,0.181,,,**,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,-37.77295663842525,11.449109319353276,100*(exp(b - se^2/2) - 1),reported,-0.018650507096749182,0.007370615250025332,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5303867403314917,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,True
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,Condominium,dwelling_type,A_structural,binary,binary,-0.457,0.181,,,**,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,-37.71069847116822,11.460564155135952,100*(exp(b - se^2/2) - 1),reported,-0.018609799583862385,0.007370620841748559,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5248618784530388,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,Condominium,dwelling_type,A_structural,binary,binary,-0.456,0.18,,,**,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,-37.63712253105928,11.408649067773881,100*(exp(b - se^2/2) - 1),reported,-0.018672217732377466,0.007370612262780578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5333333333333337,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,Condominium,dwelling_type,A_structural,binary,binary,-0.457,0.18,,,**,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,-37.6994542374807,11.397246121129676,100*(exp(b - se^2/2) - 1),reported,-0.01871315125476493,0.007370606621132793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.538888888888889,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,Condominium,dwelling_type,A_structural,binary,binary,-0.458,0.18,,,**,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,-37.761723643351175,11.38585457173254,100*(exp(b - se^2/2) - 1),reported,-0.018754084683055006,0.007370600967139521,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5444444444444447,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,True
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,Condominium,dwelling_type,A_structural,binary,binary,-0.458,0.18,,,**,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,-37.761723643351175,11.38585457173254,100*(exp(b - se^2/2) - 1),reported,-0.018754084683055006,0.007370600967139521,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5444444444444447,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,True
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,RING1,green_space,E_environment,dummy,binary (<=0.25 miles of greenline),0.002,0.021,,,,,,high,within 0.25 miles of a greenline; reference RING3 (0.51-1 mile),LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,0.17810842497096857,2.1042042028014007,100*(exp(b - se^2/2) - 1),reported,0.0007020853019307911,0.007371895670273306,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.09523809523809523,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,RING1,green_space,E_environment,dummy,binary (<=0.25 miles of greenline),0.002,0.021,,,,,,high,within 0.25 miles of a greenline; reference RING3 (0.51-1 mile),LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,0.17810842497096857,2.1042042028014007,100*(exp(b - se^2/2) - 1),reported,0.0007020853019307911,0.007371895670273306,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.09523809523809523,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,RING1,green_space,E_environment,dummy,binary (<=0.25 miles of greenline),0.002,0.021,,,,,,high,within 0.25 miles of a greenline; reference RING3 (0.51-1 mile),LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,0.17810842497096857,2.1042042028014007,100*(exp(b - se^2/2) - 1),reported,0.0007020853019307911,0.007371895670273306,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.09523809523809523,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,RING1,green_space,E_environment,dummy,binary (<=0.25 miles of greenline),0.003,0.021,,,,,,high,within 0.25 miles of a greenline; reference RING3 (0.51-1 mile),LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,0.2783366391506892,2.106309459457092,100*(exp(b - se^2/2) - 1),reported,0.00105312762845146,0.007371893399160221,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.14285714285714285,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,RING1,green_space,E_environment,dummy,binary (<=0.25 miles of greenline),0.002,0.021,,,,,,high,within 0.25 miles of a greenline; reference RING3 (0.51-1 mile),LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,0.17810842497096857,2.1042042028014007,100*(exp(b - se^2/2) - 1),reported,0.0007020853019307911,0.007371895670273306,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.09523809523809523,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,RING1,green_space,E_environment,dummy,binary (<=0.25 miles of greenline),0.002,0.021,,,,,,high,within 0.25 miles of a greenline; reference RING3 (0.51-1 mile),LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,0.17810842497096857,2.1042042028014007,100*(exp(b - se^2/2) - 1),reported,0.0007020853019307911,0.007371895670273306,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.09523809523809523,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c1,8,1,30,RING2,green_space,E_environment,dummy,binary (0.26-0.50 miles of greenline),0.021,0.014,,,,,,high,0.26-0.50 miles of a greenline; reference RING3,LNSP (natural log of sale price),log,OLS,18411.0,0.84,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,2.112197678021621,1.42971087229254,100*(exp(b - se^2/2) - 1),reported,0.011057170238340774,0.007371446825560516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c2,8,2,30,RING2,green_space,E_environment,dummy,binary (0.26-0.50 miles of greenline),0.021,0.014,,,,,,high,0.26-0.50 miles of a greenline; reference RING3,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,2.112197678021621,1.42971087229254,100*(exp(b - se^2/2) - 1),reported,0.011057170238340774,0.007371446825560516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,30,RING2,green_space,E_environment,dummy,binary (0.26-0.50 miles of greenline),0.021,0.014,,,,,,high,0.26-0.50 miles of a greenline; reference RING3,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,2.112197678021621,1.42971087229254,100*(exp(b - se^2/2) - 1),reported,0.011057170238340774,0.007371446825560516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,30,RING2,green_space,E_environment,dummy,binary (0.26-0.50 miles of greenline),0.02,0.014,,,,,,high,0.26-0.50 miles of a greenline; reference RING3,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,2.0101365194280074,1.428281876037458,100*(exp(b - se^2/2) - 1),reported,0.010530698171885962,0.007371488720320173,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4285714285714286,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,30,RING2,green_space,E_environment,dummy,binary (0.26-0.50 miles of greenline),0.02,0.014,,,,,,high,0.26-0.50 miles of a greenline; reference RING3,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,2.0101365194280074,1.428281876037458,100*(exp(b - se^2/2) - 1),reported,0.010530698171885962,0.007371488720320173,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4285714285714286,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,30,RING2,green_space,E_environment,dummy,binary (0.26-0.50 miles of greenline),0.02,0.014,,,,,,high,0.26-0.50 miles of a greenline; reference RING3,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",pct_premium,2.0101365194280074,1.428281876037458,100*(exp(b - se^2/2) - 1),reported,0.010530698171885962,0.007371488720320173,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4285714285714286,18401.0,binary,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c3,8,3,31,Log Violent crime density,crime,F_neighbourhood,log,"crimes per square mile at census-tract level, natural log",0.007,0.028,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",elasticity,0.007,0.028,b (log-log),reported,0.0018429712419178142,0.007371884967671256,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.25,18401.0,crimes per sq mile at census-tract level natural log,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,31,Log Violent crime density,crime,F_neighbourhood,log,"crimes per square mile at census-tract level, natural log",0.026,0.027,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",elasticity,0.026,0.027,b (log-log),reported,0.007098685384026303,0.007371711744950393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9629629629629629,18401.0,crimes per sq mile at census-tract level natural log,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,True
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c4,8,4,31,Log Property crime density,crime,F_neighbourhood,log,"crimes per square mile at census-tract level, natural log",-0.006,0.015,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",elasticity,-0.006,0.015,b (log-log),reported,-0.0029487461749551744,0.007371865437387936,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4,18401.0,crimes per sq mile at census-tract level natural log,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,31,Log Property crime density,crime,F_neighbourhood,log,"crimes per square mile at census-tract level, natural log",-0.004,0.013,,,,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",elasticity,-0.004,0.013,b (log-log),reported,-0.0022682703146921527,0.007371878522749496,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3076923076923077,18401.0,crimes per sq mile at census-tract level natural log,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c5,8,5,31,Log Other crime density,crime,F_neighbourhood,log,"crimes per square mile at census-tract level, natural log",-0.04,0.017,,,**,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.841,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",elasticity,-0.04,0.017,b (log-log),reported,-0.01734303233243199,0.007370788741283596,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3529411764705883,18401.0,crimes per sq mile at census-tract level natural log,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384,7f45f70c2c2271b7539c0915321311343666b384:T8-c6,8,6,31,Log Other crime density,crime,F_neighbourhood,log,"crimes per square mile at census-tract level, natural log",-0.047,0.017,,,***,,,high,,LNSP (natural log of sale price),log,OLS,18411.0,0.842,se,"Full sample; adj. R2; year and census-tract FE; col1 no greenline dummies, col2 + SFG/WR, col3 + violent crime, col4 + property crime, col5 + other crime, col6 all three crime densities",elasticity,-0.047,0.017,b (log-log),reported,-0.020376896602738743,0.007370366856309758,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.764705882352941,18401.0,crimes per sq mile at census-tract level natural log,,2026.0,United States,North America,High income,2006.0,2022.0,mixed,transaction,journal,True,True,unknown,,2014.0,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,16,D_TR,flood_risk,E_environment,binary,binary,0.214,,5.01,,***,,,high,"Treatment group: house within radius of roads inundated by the 30 Sep 2017 pluvial flood (flood exposure indicator); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,23.749321512474133,5.290723515485006,100*(exp(b - se^2/2) - 1),|b/t|,0.10264970892022152,0.020488963856331643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.01,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,16,CBD (km),cbd_distance,D_location,level,km,-0.129,,-6.31,,***,,,high,"Geodesic distance to District 1 (city centre); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",semi_elasticity,-12.9,2.0443740095087164,100*b/1 (X per km->km),|b/t|,-0.12888785694104277,0.02042596781949965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.31,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,16,Nearest_river (km),water_proximity,E_environment,level,km,-0.041,,-0.81,,,,,high,"Distance to nearest river; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",semi_elasticity,-4.1000000000000005,5.061728395061729,100*b/1 (X per km->km),|b/t|,-0.01668187222611673,0.020594903982860163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.81,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,16,Large_parks (km),green_space,E_environment,level,km,-0.144,,-4.58,,***,,,high,"Distance to large parks; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",semi_elasticity,-14.399999999999999,3.144104803493449,100*b/1 (X per km->km),|b/t|,-0.0939207837262962,0.020506721337619258,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.58,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,16,Hospital (1 km),hospital_distance,D_location,binary,binary,0.02,,0.49,,,,,high,"1 if a hospital within 1 km; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,1.9351880175747516,4.164087102150024,100*(exp(b - se^2/2) - 1),|b/t|,0.010092393374267402,0.020596721171974287,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.49,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,16,School (1 km),school_distance,D_location,binary,binary,0.314,,11.73,,***,,,high,"1 if a school within 1 km; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,36.83993664891898,3.664376617867655,100*(exp(b - se^2/2) - 1),|b/t|,0.2348541134113629,0.020021663547430766,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.73,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,16,Area (m2),living_area,A_structural,level,m2,0.006,,33.09,,***,,,high,"Floor area in square metres; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",semi_elasticity,0.6,0.01813236627379873,100*b/1 (X per m2->m2),|b/t|,0.5632025836340586,0.01702032588800419,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.09,2357.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,16,Number_of_bedrooms,bedrooms,A_structural,level,count,0.017,,1.05,,,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",semi_elasticity,1.7000000000000002,1.6190476190476193,100*b/1 (per unit count),|b/t|,0.021622602260741416,0.02059295453403944,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.05,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,16,Number_of_bathrooms,bathrooms,A_structural,level,count,0.091,,5.76,,***,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",semi_elasticity,9.1,1.5798611111111112,100*b/1 (per unit count),|b/t|,0.11781684737954615,0.02045431378117121,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.76,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,17,Floor_level,floor_level,A_structural,level,count,-0.01,,-7.01,,***,,,high,"Floor level of the unit (0-38); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",semi_elasticity,-1.0,0.14265335235378032,100*b/1 (per unit count),|b/t|,-0.14290833602310246,0.02038635321299607,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.01,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,17,Balcony_or_Terrace,terrace_balcony,C_exterior,binary,binary,-0.02,,-0.47,,,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,-2.068838425557884,4.171058184284066,100*(exp(b - se^2/2) - 1),|b/t|,-0.009680498375311505,0.020596805053854268,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.47,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,17,Garden,garden,C_exterior,binary,binary,0.05,,1.2,,,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,5.035893062297259,4.380296234900102,100*(exp(b - se^2/2) - 1),|b/t|,0.02470977722860051,0.02059148102383376,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,17,Swimming_pool,pool,C_exterior,binary,binary,-0.314,,-7.88,,***,,,high,"Private or shared (apartment) pool; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,-27.006071550598985,2.9109514573865414,100*(exp(b - se^2/2) - 1),|b/t|,-0.16021375874273858,0.020331695271921135,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.88,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,True
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,17,Washing_machine,appliances,B_interior,binary,binary,0.084,,2.25,,**,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,8.687120136188465,4.060481203552952,100*(exp(b - se^2/2) - 1),|b/t|,0.0462952917881912,0.02057568523919609,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.25,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,18,Direction: 1 (north),sunlight,E_environment,binary,binary,0.165,,3.1,,***,,,high,"Orientation the house faces (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,17.772369897591677,6.277414986689661,100*(exp(b - se^2/2) - 1),|b/t|,0.063723312903259,0.020555907388148068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,18,Direction: 2 (northeast),sunlight,E_environment,binary,binary,0.094,,1.44,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,9.6221652613103,7.1711538969593285,100*(exp(b - se^2/2) - 1),|b/t|,0.029647750475658454,0.02058871560809615,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.44,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,18,Direction: 3 (east),sunlight,E_environment,binary,binary,-0.084,,-1.45,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,-8.211025804522286,5.326360380137274,100*(exp(b - se^2/2) - 1),|b/t|,-0.029853454771357153,0.02058858949748769,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.45,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,18,Direction: 4 (southeast),sunlight,E_environment,binary,binary,0.076,,1.64,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,7.780464302909196,5.0000704656069255,100*(exp(b - se^2/2) - 1),|b/t|,0.03376108604687994,0.020586028077365818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.64,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,18,Direction: 5 (south),sunlight,E_environment,binary,binary,0.108,,2.5,,**,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,11.30086900113616,4.81268626006954,100*(exp(b - se^2/2) - 1),|b/t|,0.05142628773229594,0.020570515092918375,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,18,Direction: 6 (southwest),sunlight,E_environment,binary,binary,0.281,,3.25,,***,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,31.951230336853964,11.451429621717148,100*(exp(b - se^2/2) - 1),|b/t|,0.06679325907436817,0.020551772022882515,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.25,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,18,Direction: 7 (west),sunlight,E_environment,binary,binary,0.255,,3.7,,***,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,28.740052869814114,8.89372198169154,100*(exp(b - se^2/2) - 1),|b/t|,0.0759913815451199,0.020538211228410784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.7,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c1,6,1,18,Direction: 8 (northwest),sunlight,E_environment,binary,binary,0.119,,1.68,,*,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,OLS,2367.0,0.647,t,"OLS model, Eq. (2); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates",pct_premium,12.354775740614565,7.978453587875833,100*(exp(b - se^2/2) - 1),|b/t|,0.034583554026863084,0.020585448825513743,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.68,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,ols,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,16,D_TR,flood_risk,E_environment,binary,binary,0.19,,4.51,,***,,,high,"Treatment group: house within radius of roads inundated by the 30 Sep 2017 pluvial flood (flood exposure indicator); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,20.817697395446523,5.0943996353631436,100*(exp(b - se^2/2) - 1),|b/t|,0.09249768934738291,0.020509465487224595,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.51,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,16,CBD (km),cbd_distance,D_location,level,km,-0.195,,-5.95,,***,,,high,"Geodesic distance to District 1 (city centre); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-19.5,3.2773109243697482,100*b/1 (X per km->km),|b/t|,-0.1216465627350336,0.020444800459669513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.95,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,True
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,16,Nearest_river (km),water_proximity,E_environment,level,km,-0.274,,-3.79,,***,,,high,"Distance to nearest river; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-27.400000000000002,7.229551451187335,100*b/1 (X per km->km),|b/t|,-0.07782875613234232,0.020535291855499294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.79,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,True
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,16,Large_parks (km),green_space,E_environment,level,km,-0.372,,-8.4,,***,,,high,"Distance to large parks; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-37.2,4.428571428571428,100*b/1 (X per km->km),|b/t|,-0.17048818983729322,0.020296213075868243,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.4,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,16,Hospital (1 km),hospital_distance,D_location,binary,binary,0.032,,0.7,,,,,high,"1 if a hospital within 1 km; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,3.143919333210321,4.72008002425197,100*(exp(b - se^2/2) - 1),|b/t|,0.014416940643244223,0.02059562949034889,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,16,School (1 km),school_distance,D_location,binary,binary,0.37,,10.74,,***,,,high,"1 if a school within 1 km; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,44.6875749487059,4.98754010638203,100*(exp(b - se^2/2) - 1),|b/t|,0.2159978937055385,0.020111535726772673,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.74,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,16,Area (m2),living_area,A_structural,level,m2,0.005,,29.35,,***,,,high,"Floor area in square metres; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,0.5,0.017035775127768313,100*b/1 (X per m2->m2),|b/t|,0.5173525305585203,0.017627002744753668,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.35,2357.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,16,Number_of_bedrooms,bedrooms,A_structural,level,count,0.039,,2.77,,***,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,3.9,1.407942238267148,100*b/1 (per unit count),|b/t|,0.05696318077687092,0.020564325190206106,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.77,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,16,Number_of_bathrooms,bathrooms,A_structural,level,count,0.049,,3.63,,***,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,4.9,1.3498622589531681,100*b/1 (per unit count),|b/t|,0.07456177608021554,0.02054043418187756,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.63,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,17,Floor_level,floor_level,A_structural,level,count,-0.006,,-4.86,,***,,,high,"Floor level of the unit (0-38); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-0.6,0.12345679012345678,100*b/1 (per unit count),|b/t|,-0.09960732264650994,0.0204953338778827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.86,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,17,Balcony_or_Terrace,terrace_balcony,C_exterior,binary,binary,0.022,,0.62,,,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,2.160043082350138,3.627316654572523,100*(exp(b - se^2/2) - 1),|b/t|,0.012769576283608359,0.02059609078001348,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.62,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,17,Garden,garden,C_exterior,binary,binary,0.037,,1.06,,,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,3.706104810930677,3.62213601613319,100*(exp(b - se^2/2) - 1),|b/t|,0.021828434147279824,0.020592862403094176,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.06,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,17,Swimming_pool,pool,C_exterior,binary,binary,-0.286,,-8.38,,***,,,high,"Private or shared (apartment) pool; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-24.917478463175,2.563975037718489,100*(exp(b - se^2/2) - 1),|b/t|,-0.1700940233752271,0.020297616154561705,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.38,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,17,Washing_machine,appliances,B_interior,binary,binary,0.094,,3.0,,***,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,9.802060748348218,3.4421538705404773,100*(exp(b - se^2/2) - 1),|b/t|,0.061675671210559474,0.02055855707018649,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,18,Direction: 1 (north),sunlight,E_environment,binary,binary,0.084,,1.88,,*,,,high,"Orientation the house faces (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,8.654377603179132,4.859618461699011,100*(exp(b - se^2/2) - 1),|b/t|,0.03869480677969587,0.02058234403175312,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.88,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,18,Direction: 2 (northeast),sunlight,E_environment,binary,binary,0.111,,2.05,,**,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,11.575810296945832,6.0502846176021885,100*(exp(b - se^2/2) - 1),|b/t|,0.04218783549425878,0.020579431948418915,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.05,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,18,Direction: 3 (east),sunlight,E_environment,binary,binary,0.032,,0.67,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,3.134052246298924,4.9314268910095205,100*(exp(b - se^2/2) - 1),|b/t|,0.01379919204520835,0.020595809022699026,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.67,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,18,Direction: 4 (southeast),sunlight,E_environment,binary,binary,0.086,,2.2,,**,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,8.89739802484064,4.260152010647321,100*(exp(b - se^2/2) - 1),|b/t|,0.04526863966912196,0.020576654395055436,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,18,Direction: 5 (south),sunlight,E_environment,binary,binary,0.039,,1.07,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,3.908004528474418,3.7898176506874908,100*(exp(b - se^2/2) - 1),|b/t|,0.022034263258132666,0.020592769400123986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.07,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,18,Direction: 6 (southwest),sunlight,E_environment,binary,binary,0.195,,2.71,,***,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,21.21688428316224,8.744857651863375,100*(exp(b - se^2/2) - 1),|b/t|,0.055733196159096436,0.020565755040256987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.71,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,18,Direction: 7 (west),sunlight,E_environment,binary,binary,0.241,,4.21,,***,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,27.04377482010898,7.284502838700314,100*(exp(b - se^2/2) - 1),|b/t|,0.08639239542539648,0.020520759008407715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.21,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c2,6,2,18,Direction: 8 (northwest),sunlight,E_environment,binary,binary,0.14,,2.36,,**,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.598,t,"SEM model, Eq. (3); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,14.825161205608195,6.823658128814062,100*(exp(b - se^2/2) - 1),|b/t|,0.04855340559396772,0.020573476946596492,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.36,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,16,D_TR,flood_risk,E_environment,binary,binary,0.213,,5.02,,***,,,high,"Treatment group: house within radius of roads inundated by the 30 Sep 2017 pluvial flood (flood exposure indicator); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,23.627130294944987,5.250257583961891,100*(exp(b - se^2/2) - 1),|b/t|,0.10285243324455957,0.02048853251883657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.02,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,16,CBD (km),cbd_distance,D_location,level,km,-0.139,,-6.79,,***,,,high,"Geodesic distance to District 1 (city centre); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-13.900000000000002,2.0471281296023562,100*b/1 (X per km->km),|b/t|,-0.13851075038580152,0.020399226860942785,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.79,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,16,Nearest_river (km),water_proximity,E_environment,level,km,0.013,,0.24,,,,,high,"Distance to nearest river; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,1.3,5.416666666666667,100*b/1 (X per km->km),|b/t|,0.00494340444675543,0.020597518528147625,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.24,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,16,Large_parks (km),green_space,E_environment,level,km,-0.177,,-5.46,,***,,,high,"Distance to large parks; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-17.7,3.2417582417582413,100*b/1 (X per km->km),|b/t|,-0.11175927422624948,0.020468731543269135,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.46,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,16,Hospital (1 km),hospital_distance,D_location,binary,binary,0.026,,0.62,,,,,high,"1 if a hospital within 1 km; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,2.5438891317917323,4.304010429082176,100*(exp(b - se^2/2) - 1),|b/t|,0.012769576283608359,0.02059609078001348,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.62,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,16,School (1 km),school_distance,D_location,binary,binary,0.332,,12.24,,***,,,high,"1 if a school within 1 km; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,39.32402359718672,3.7804407328934273,100*(exp(b - se^2/2) - 1),|b/t|,0.2444668914496389,0.019972785249153503,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.24,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,16,Area (m2),living_area,A_structural,level,m2,0.006,,32.93,,***,,,high,"Floor area in square metres; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,0.6,0.018220467658669907,100*b/1 (X per m2->m2),|b/t|,0.5613388574172153,0.01704642749520848,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.93,2357.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,16,Number_of_bedrooms,bedrooms,A_structural,level,count,0.018,,1.09,,,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,1.7999999999999998,1.6513761467889905,100*b/1 (per unit count),|b/t|,0.02244591304829364,0.020592580778251046,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.09,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,16,Number_of_bathrooms,bathrooms,A_structural,level,count,0.084,,5.3,,***,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,8.4,1.5849056603773586,100*b/1 (per unit count),|b/t|,0.1085234230482258,0.02047611755626902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.3,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,17,Floor_level,floor_level,A_structural,level,count,-0.01,,-6.63,,***,,,high,"Floor level of the unit (0-38); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-1.0,0.1508295625942685,100*b/1 (per unit count),|b/t|,-0.13530733689554178,0.02040834643974989,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.63,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,17,Balcony_or_Terrace,terrace_balcony,C_exterior,binary,binary,-0.023,,-0.56,,,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-2.3561422317477376,4.013756629783102,100*(exp(b - se^2/2) - 1),|b/t|,-0.011533984039828969,0.020596400071123157,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.56,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,17,Garden,garden,C_exterior,binary,binary,0.053,,1.27,,,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,5.351185615182685,4.4003756843563675,100*(exp(b - se^2/2) - 1),|b/t|,0.026150222366114233,0.020590726272530894,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.27,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,17,Swimming_pool,pool,C_exterior,binary,binary,-0.294,,-7.33,,***,,,high,"Private or shared (apartment) pool; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-25.532274674571596,2.9892399520372015,100*(exp(b - se^2/2) - 1),|b/t|,-0.14928968012719454,0.020366941354323945,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.33,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,17,Washing_machine,appliances,B_interior,binary,binary,0.081,,2.17,,**,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,8.361572234181569,4.047651733728461,100*(exp(b - se^2/2) - 1),|b/t|,0.04465257933256283,0.02057722549887688,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.17,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,18,Direction: 1 (north),sunlight,E_environment,binary,binary,0.142,,2.66,,***,,,high,"Orientation the house faces (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,15.093551522635341,6.152852785423109,100*(exp(b - se^2/2) - 1),|b/t|,0.0547080148751838,0.020566922885407443,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.66,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,18,Direction: 2 (northeast),sunlight,E_environment,binary,binary,0.073,,1.13,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,7.348815648920537,6.94940966325428,100*(exp(b - se^2/2) - 1),|b/t|,0.023269178171121428,0.020592193071788875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.13,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,18,Direction: 3 (east),sunlight,E_environment,binary,binary,-0.12,,-2.04,,**,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-11.461270108003617,5.217179039512692,100*(exp(b - se^2/2) - 1),|b/t|,-0.041982404779292035,0.02057961018592747,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.04,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,18,Direction: 4 (southeast),sunlight,E_environment,binary,binary,0.062,,1.33,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,6.280692324267956,4.959824464145721,100*(exp(b - se^2/2) - 1),|b/t|,0.027384760335620602,0.02059004536512827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.33,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,18,Direction: 5 (south),sunlight,E_environment,binary,binary,0.1,,2.32,,**,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,10.41447422519215,4.763667750326068,100*(exp(b - se^2/2) - 1),|b/t|,0.047732357608403116,0.02057429207258755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.32,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,18,Direction: 6 (southwest),sunlight,E_environment,binary,binary,0.26,,3.01,,***,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,29.21007172505017,11.20271835658142,100*(exp(b - se^2/2) - 1),|b/t|,0.06188047085719505,0.020558295965845533,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.01,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,18,Direction: 7 (west),sunlight,E_environment,binary,binary,0.211,,3.02,,***,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,23.190193379605905,8.628030030395834,100*(exp(b - se^2/2) - 1),|b/t|,0.0620852626878607,0.020558034002602883,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.02,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c3,6,3,18,Direction: 8 (northwest),sunlight,E_environment,binary,binary,0.089,,1.26,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_lag,2367.0,0.647,t,"SAR model, Eq. (4); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,9.035720546748705,7.720966540717729,100*(exp(b - se^2/2) - 1),|b/t|,0.025944454252219327,0.02059083670811058,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.26,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,16,D_TR,flood_risk,E_environment,binary,binary,0.082,,1.83,,*,,,high,"Treatment group: house within radius of roads inundated by the 30 Sep 2017 pluvial flood (flood exposure indicator); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,8.43666548064923,4.863791060438417,100*(exp(b - se^2/2) - 1),|b/t|,0.03766716962373732,0.020583152799856456,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.83,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,16,CBD (km),cbd_distance,D_location,level,km,-0.112,,-5.56,,***,,,high,"Geodesic distance to District 1 (city centre); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-11.200000000000001,2.0143884892086334,100*b/1 (X per km->km),|b/t|,-0.11377988410891823,0.020464007933258675,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.56,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,16,Nearest_river (km),water_proximity,E_environment,level,km,-0.03,,-0.56,,,,,high,"Distance to nearest river; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-3.0,5.357142857142856,100*b/1 (X per km->km),|b/t|,-0.011533984039828969,0.020596400071123157,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.56,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,16,Large_parks (km),green_space,E_environment,level,km,-0.105,,-3.25,,***,,,high,"Distance to large parks; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-10.5,3.230769230769231,100*b/1 (X per km->km),|b/t|,-0.06679325907436817,0.020551772022882515,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.25,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,16,Hospital (1 km),hospital_distance,D_location,binary,binary,-0.16,,-3.21,,***,,,high,"1 if a hospital within 1 km; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-14.891410726549559,4.247445677090149,100*(exp(b - se^2/2) - 1),|b/t|,-0.06597478859482717,0.02055289364324834,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.21,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,True
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,16,School (1 km),school_distance,D_location,binary,binary,0.355,,12.45,,***,,,high,"1 if a school within 1 km; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,42.56009930225457,4.066619536304622,100*(exp(b - se^2/2) - 1),|b/t|,0.24840441918169118,0.01995216218326837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.45,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,16,Area (m2),living_area,A_structural,level,m2,0.006,,32.98,,***,,,high,"Floor area in square metres; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,0.6,0.01819284414796847,100*b/1 (X per m2->m2),|b/t|,0.5619221923922351,0.017038271449127805,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.98,2357.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,16,Number_of_bedrooms,bedrooms,A_structural,level,count,0.022,,1.32,,,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,2.1999999999999997,1.6666666666666667,100*b/1 (per unit count),|b/t|,0.0271790125560731,0.020590161027328104,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.32,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,16,Number_of_bathrooms,bathrooms,A_structural,level,count,0.074,,4.68,,***,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,7.3999999999999995,1.5811965811965811,100*b/1 (per unit count),|b/t|,0.09595277535049955,0.02050272977574777,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.68,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,17,Floor_level,floor_level,A_structural,level,count,-0.009,,-6.52,,***,,,high,"Floor level of the unit (0-38); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-0.8999999999999999,0.13803680981595093,100*b/1 (per unit count),|b/t|,-0.13310251984071303,0.02041449690808482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.52,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,17,Balcony_or_Terrace,terrace_balcony,C_exterior,binary,binary,-0.046,,-1.12,,,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-4.5763210321931975,3.922493773283292,100*(exp(b - se^2/2) - 1),|b/t|,-0.02306336626289044,0.02059229130615218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.12,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,17,Garden,garden,C_exterior,binary,binary,0.054,,1.32,,,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,5.460176648417692,4.3178915542707825,100*(exp(b - se^2/2) - 1),|b/t|,0.0271790125560731,0.020590161027328104,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.32,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,17,Swimming_pool,pool,C_exterior,binary,binary,-0.226,,-5.57,,***,,,high,"Private or shared (apartment) pool; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-20.293826604449492,3.23670181286252,100*(exp(b - se^2/2) - 1),|b/t|,-0.11398186788735401,0.02046353103902226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.57,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,17,Washing_machine,appliances,B_interior,binary,binary,0.074,,1.99,,**,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,7.606256215718532,4.004206211392978,100*(exp(b - se^2/2) - 1),|b/t|,0.040955171851186335,0.020580488367430316,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.99,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,18,Direction: 1 (north),sunlight,E_environment,binary,binary,0.127,,2.4,,**,,,high,"Orientation the house faces (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,13.382844772357494,6.008248385760365,100*(exp(b - se^2/2) - 1),|b/t|,0.049374355166881816,0.020572647986200756,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,18,Direction: 2 (northeast),sunlight,E_environment,binary,binary,0.087,,1.35,,,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,8.863373598870684,7.030223047073344,100*(exp(b - se^2/2) - 1),|b/t|,0.027796245427691938,0.020589811427919956,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.35,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,18,Direction: 3 (east),sunlight,E_environment,binary,binary,-0.133,,-2.27,,**,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-12.603627793026838,5.1293769713861925,100*(exp(b - se^2/2) - 1),|b/t|,-0.04670591174566217,0.02057529151791285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.27,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,True
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,18,Direction: 4 (southeast),sunlight,E_environment,binary,binary,0.052,,1.13,,,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,5.226100345212892,4.847392797406634,100*(exp(b - se^2/2) - 1),|b/t|,0.023269178171121428,0.020592193071788875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.13,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,18,Direction: 5 (south),sunlight,E_environment,binary,binary,0.086,,2.0,,**,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,8.879926793999227,4.686167211712053,100*(exp(b - se^2/2) - 1),|b/t|,0.04116062893098295,0.020580314465491474,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,18,Direction: 6 (southwest),sunlight,E_environment,binary,binary,0.23,,2.69,,***,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,25.40078674521553,10.76126402541933,100*(exp(b - se^2/2) - 1),|b/t|,0.05532314461545527,0.020566224764109766,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.69,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,18,Direction: 7 (west),sunlight,E_environment,binary,binary,0.196,,2.83,,***,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,21.36127660371998,8.425416022810106,100*(exp(b - se^2/2) - 1),|b/t|,0.0581929060754883,0.020562864337628373,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.83,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c4,6,4,18,Direction: 8 (northwest),sunlight,E_environment,binary,binary,0.041,,0.58,,,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.658,t,"SLX model, Eq. (5); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,3.9252273024305007,7.364816608166321,100*(exp(b - se^2/2) - 1),|b/t|,0.011945854271080587,0.020596300467380323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.58,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,16,D_TR,flood_risk,E_environment,binary,binary,0.104,,2.21,,**,,,high,"Treatment group: house within radius of roads inundated by the 30 Sep 2017 pluvial flood (flood exposure indicator); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,10.837251153020633,5.221649199602741,100*(exp(b - se^2/2) - 1),|b/t|,0.04547398167262297,0.020576462295304514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.21,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,16,CBD (km),cbd_distance,D_location,level,km,-0.127,,-5.76,,***,,,high,"Geodesic distance to District 1 (city centre); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-12.7,2.204861111111111,100*b/1 (X per km->km),|b/t|,-0.11781684737954615,0.02045431378117121,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.76,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,16,Nearest_river (km),water_proximity,E_environment,level,km,-0.044,,-0.81,,,,,high,"Distance to nearest river; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-4.3999999999999995,5.432098765432098,100*b/1 (X per km->km),|b/t|,-0.01668187222611673,0.020594903982860163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.81,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,16,Large_parks (km),green_space,E_environment,level,km,-0.128,,-3.65,,***,,,high,"Distance to large parks; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-12.8,3.5068493150684934,100*b/1 (X per km->km),|b/t|,-0.07497028208647921,0.020539803311364166,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.65,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,16,Hospital (1 km),hospital_distance,D_location,binary,binary,-0.152,,-3.03,,***,,,high,"1 if a hospital within 1 km; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-14.209187396453304,4.309116127810256,100*(exp(b - se^2/2) - 1),|b/t|,-0.06229004667708934,0.020557771180557537,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.03,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,16,School (1 km),school_distance,D_location,binary,binary,0.365,,12.49,,***,,,high,"1 if a school within 1 km; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,43.98990357518549,4.209668638706679,100*(exp(b - se^2/2) - 1),|b/t|,0.24915303708821432,0.01994820152827977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.49,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,16,Area (m2),living_area,A_structural,level,m2,0.006,,32.96,,***,,,high,"Floor area in square metres; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,0.6,0.01820388349514563,100*b/1 (X per m2->m2),|b/t|,0.5616889589003728,0.01704153394722005,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.96,2357.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,16,Number_of_bedrooms,bedrooms,A_structural,level,count,0.022,,1.38,,,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,2.1999999999999997,1.5942028985507246,100*b/1 (per unit count),|b/t|,0.028413446507244575,0.02058945399075694,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.38,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,16,Number_of_bathrooms,bathrooms,A_structural,level,count,0.072,,4.56,,***,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,7.199999999999999,1.5789473684210527,100*b/1 (per unit count),|b/t|,0.09351424368598915,0.02050750958026078,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.56,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,17,Floor_level,floor_level,A_structural,level,count,-0.009,,-6.34,,***,,,high,"Floor level of the unit (0-38); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-0.8999999999999999,0.14195583596214512,100*b/1 (per unit count),|b/t|,-0.1294903849480182,0.020424350938173217,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.34,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,17,Balcony_or_Terrace,terrace_balcony,C_exterior,binary,binary,-0.046,,-1.1,,,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-4.5792742580215595,3.9938118418884434,100*(exp(b - se^2/2) - 1),|b/t|,-0.022651733675362246,0.02059248515942022,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,True
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,17,Garden,garden,C_exterior,binary,binary,0.052,,1.28,,,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,5.250686033639651,4.2793389539605435,100*(exp(b - se^2/2) - 1),|b/t|,0.02635598715614808,0.020590614965740685,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.28,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,17,Swimming_pool,pool,C_exterior,binary,binary,-0.228,,-5.61,,***,,,high,"Private or shared (apartment) pool; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-20.453296733596627,3.235585227138743,100*(exp(b - se^2/2) - 1),|b/t|,-0.11478966143245657,0.020461615228601883,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.61,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,17,Washing_machine,appliances,B_interior,binary,binary,0.073,,1.96,,*,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,7.498467835819556,4.0065474078965995,100*(exp(b - se^2/2) - 1),|b/t|,0.04033876954344126,0.020581004869102686,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.96,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,18,Direction: 1 (north),sunlight,E_environment,binary,binary,0.123,,2.34,,**,,,high,"Orientation the house faces (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,12.932319133211667,5.944392469082956,100*(exp(b - se^2/2) - 1),|b/t|,0.04814289379973707,0.02057388623920388,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.34,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,18,Direction: 2 (northeast),sunlight,E_environment,binary,binary,0.089,,1.38,,,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,9.080978492975845,7.049578145872709,100*(exp(b - se^2/2) - 1),|b/t|,0.028413446507244575,0.02058945399075694,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.38,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,18,Direction: 3 (east),sunlight,E_environment,binary,binary,-0.133,,-2.28,,**,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-12.60231480748929,5.106879703967832,100*(exp(b - se^2/2) - 1),|b/t|,-0.046911212859032304,0.020575093359224698,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.28,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,18,Direction: 4 (southeast),sunlight,E_environment,binary,binary,0.052,,1.13,,,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,5.226100345212892,4.847392797406634,100*(exp(b - se^2/2) - 1),|b/t|,0.023269178171121428,0.020592193071788875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.13,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,18,Direction: 5 (south),sunlight,E_environment,binary,binary,0.084,,1.95,,*,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,8.662024812539748,4.6851706194841745,100*(exp(b - se^2/2) - 1),|b/t|,0.04013329183771814,0.02058117530139392,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.95,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,18,Direction: 6 (southwest),sunlight,E_environment,binary,binary,0.23,,2.69,,***,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,25.40078674521553,10.76126402541933,100*(exp(b - se^2/2) - 1),|b/t|,0.05532314461545527,0.020566224764109766,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.69,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,18,Direction: 7 (west),sunlight,E_environment,binary,binary,0.193,,2.8,,***,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,21.000492036823193,8.36022782675679,100*(exp(b - se^2/2) - 1),|b/t|,0.05757807618639667,0.020563598637998812,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c5,6,5,18,Direction: 8 (northwest),sunlight,E_environment,binary,binary,0.039,,0.56,,,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,other,2367.0,0.656,t,"SDM model, Eq. (6); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,3.7252028856397335,7.241258725420741,100*(exp(b - se^2/2) - 1),|b/t|,0.011533984039828969,0.020596400071123157,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.56,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,other,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,16,D_TR,flood_risk,E_environment,binary,binary,0.029,,0.66,,,,,high,"Treatment group: house within radius of roads inundated by the 30 Sep 2017 pluvial flood (flood exposure indicator); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,2.843133420101429,4.523229278754362,100*(exp(b - se^2/2) - 1),|b/t|,0.013593272299561506,0.020595867120547735,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.66,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,16,CBD (km),cbd_distance,D_location,level,km,-0.138,,-4.75,,***,,,high,"Geodesic distance to District 1 (city centre); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-13.8,2.905263157894737,100*b/1 (X per km->km),|b/t|,-0.09737445759535235,0.020499885809547865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.75,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,16,Nearest_river (km),water_proximity,E_environment,level,km,-0.031,,-0.41,,,,,high,"Distance to nearest river; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-3.1,7.560975609756097,100*b/1 (X per km->km),|b/t|,-0.008444784651066562,0.02059703573430869,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.41,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,16,Large_parks (km),green_space,E_environment,level,km,-0.322,,-7.48,,***,,,high,"Distance to large parks; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-32.2,4.304812834224599,100*b/1 (X per km->km),|b/t|,-0.1522745765545354,0.020357563710499387,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.48,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,16,Hospital (1 km),hospital_distance,D_location,binary,binary,-0.045,,-0.73,,,,,high,"1 if a hospital within 1 km; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-4.5817170993797784,5.893135161984863,100*(exp(b - se^2/2) - 1),|b/t|,-0.015034672733201368,0.02059544210027585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.73,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,16,School (1 km),school_distance,D_location,binary,binary,0.372,,9.62,,***,,,high,"1 if a school within 1 km; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,44.95488024091308,5.609516310198078,100*(exp(b - se^2/2) - 1),|b/t|,0.19437142298768795,0.02020492962449979,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.62,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,True
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,16,Area (m2),living_area,A_structural,level,m2,0.004,,28.22,,***,,,high,"Floor area in square metres; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,0.4,0.01417434443656981,100*b/1 (X per m2->m2),|b/t|,0.502538864130175,0.017807897382359144,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.22,2357.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,16,Number_of_bedrooms,bedrooms,A_structural,level,count,0.057,,4.27,,***,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,5.7,1.3348946135831383,100*b/1 (per unit count),|b/t|,0.08761425550809765,0.02051856100892217,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.27,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,16,Number_of_bathrooms,bathrooms,A_structural,level,count,0.007,,0.56,,,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,0.7000000000000001,1.25,100*b/1 (per unit count),|b/t|,0.011533984039828969,0.020596400071123157,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.56,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,17,Floor_level,floor_level,A_structural,level,count,-0.005,,-3.83,,***,,,high,"Floor level of the unit (0-38); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-0.5,0.13054830287206268,100*b/1 (per unit count),|b/t|,-0.0786451136985841,0.02053397224506112,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.83,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,17,Balcony_or_Terrace,terrace_balcony,C_exterior,binary,binary,-0.004,,-0.12,,,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-0.4545194751389592,3.3200266311466384,100*(exp(b - se^2/2) - 1),|b/t|,-0.0024717248742887133,0.02059770728573928,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.12,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,17,Garden,garden,C_exterior,binary,binary,0.032,,0.98,,,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,3.196720535362796,3.3714857316085496,100*(exp(b - se^2/2) - 1),|b/t|,0.020181703530428006,0.020593575031048982,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.98,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,17,Swimming_pool,pool,C_exterior,binary,binary,-0.135,,-3.98,,***,,,high,"Private or shared (apartment) pool; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-12.678656593955463,2.9636092481880567,100*(exp(b - se^2/2) - 1),|b/t|,-0.08170503268252559,0.020528902684051654,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.98,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,17,Washing_machine,appliances,B_interior,binary,binary,0.074,,2.48,,**,,,high,"; spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,7.632754546796328,3.2130525647871075,100*(exp(b - se^2/2) - 1),|b/t|,0.05101595248436874,0.02057094858240675,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.48,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,18,Direction: 1 (north),sunlight,E_environment,binary,binary,0.014,,0.34,,,,,high,"Orientation the house faces (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,1.3239120396641546,4.175699536805556,100*(exp(b - se^2/2) - 1),|b/t|,0.0070030701379996535,0.020597265111763685,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.34,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,18,Direction: 2 (northeast),sunlight,E_environment,binary,binary,0.053,,1.03,,,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,5.303463468073333,5.425705940905424,100*(exp(b - se^2/2) - 1),|b/t|,0.021210930265106457,0.020593136179715005,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.03,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,18,Direction: 3 (east),sunlight,E_environment,binary,binary,-0.069,,-1.46,,,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-6.771504633213943,4.410927460643558,100*(exp(b - se^2/2) - 1),|b/t|,-0.03005915527406505,0.02058846251648291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.46,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,18,Direction: 4 (southeast),sunlight,E_environment,binary,binary,0.055,,1.47,,,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,5.580135855441659,3.9530431161328017,100*(exp(b - se^2/2) - 1),|b/t|,0.03026485195774136,0.020588334665130176,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.47,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,18,Direction: 5 (south),sunlight,E_environment,binary,binary,0.003,,0.1,,,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,0.2553254015325246,3.0090135135101312,100*(exp(b - se^2/2) - 1),|b/t|,0.0020597726511340734,0.02059772651134073,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.1,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,18,Direction: 6 (southwest),sunlight,E_environment,binary,binary,0.116,,1.7,,*,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,12.038454745399285,7.66279536279162,100*(exp(b - se^2/2) - 1),|b/t|,0.03499476177307857,0.020585153984163867,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,18,Direction: 7 (west),sunlight,E_environment,binary,binary,0.108,,1.96,,**,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,11.235777317560313,6.138630433762168,100*(exp(b - se^2/2) - 1),|b/t|,0.04033876954344126,0.020581004869102686,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.96,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c6,6,6,18,Direction: 8 (northwest),sunlight,E_environment,binary,binary,0.061,,1.07,,,,,high,"Orientation (base: unknown); spatial Durbin/SLX type model, coefficient of X (not W*X); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,spatial_error,2367.0,0.571,t,"SDEM model, Eq. (7); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,6.1173071292907055,6.0595171743382155,100*(exp(b - se^2/2) - 1),|b/t|,0.022034263258132666,0.020592769400123986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.07,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,16,D_TR,flood_risk,E_environment,binary,binary,0.184,,4.52,,***,,,high,"Treatment group: house within radius of roads inundated by the 30 Sep 2017 pluvial flood (flood exposure indicator); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,20.102028231234435,4.893161757737157,100*(exp(b - se^2/2) - 1),|b/t|,0.09270102345841659,0.02050907598637535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.52,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,16,CBD (km),cbd_distance,D_location,level,km,-0.191,,-6.54,,***,,,high,"Geodesic distance to District 1 (city centre); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-19.1,2.9204892966360854,100*b/1 (X per km->km),|b/t|,-0.13350354367644793,0.02041338588324892,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.54,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,16,Nearest_river (km),water_proximity,E_environment,level,km,0.067,,0.91,,,,,high,"Distance to nearest river; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,6.7,7.362637362637363,100*b/1 (X per km->km),|b/t|,0.018740679034882125,0.020594152785584754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.91,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,True
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,16,Large_parks (km),green_space,E_environment,level,km,-0.483,,-11.72,,***,,,high,"Distance to large parks; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-48.3,4.121160409556314,100*b/1 (X per km->km),|b/t|,-0.234664926675515,0.02002260466514633,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.72,2357.0,km,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,True
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,16,Hospital (1 km),hospital_distance,D_location,binary,binary,0.117,,2.7,,***,,,high,"1 if a hospital within 1 km; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,12.306450175576877,4.87118419532566,100*(exp(b - se^2/2) - 1),|b/t|,0.05552817389934227,0.020565990333089725,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,True
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,16,School (1 km),school_distance,D_location,binary,binary,0.355,,11.03,,***,,,high,"1 if a school within 1 km; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,42.54421759389213,4.5901553242966955,100*(exp(b - se^2/2) - 1),|b/t|,0.22154755139343865,0.020085906744645395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.03,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,16,Area (m2),living_area,A_structural,level,m2,0.004,,28.67,,***,,,high,"Floor area in square metres; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,0.4,0.013951866062085802,100*b/1 (X per m2->m2),|b/t|,0.5084925019342756,0.0177360482014048,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.67,2357.0,m2,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,16,Number_of_bedrooms,bedrooms,A_structural,level,count,0.057,,4.23,,***,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,5.7,1.3475177304964538,100*b/1 (per unit count),|b/t|,0.08679972571386285,0.020520029719589324,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.23,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,16,Number_of_bathrooms,bathrooms,A_structural,level,count,0.014,,1.06,,,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,1.4000000000000001,1.320754716981132,100*b/1 (per unit count),|b/t|,0.021828434147279824,0.020592862403094176,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.06,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,17,Floor_level,floor_level,A_structural,level,count,-0.005,,-3.97,,***,,,high,"Floor level of the unit (0-38); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",semi_elasticity,-0.5,0.12594458438287154,100*b/1 (per unit count),|b/t|,-0.08150110897979958,0.02052924659440795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.97,2357.0,count,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,17,Balcony_or_Terrace,terrace_balcony,C_exterior,binary,binary,0.007,,0.21,,,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,0.6465254555727551,3.3567485242228288,100*(exp(b - se^2/2) - 1),|b/t|,0.004325491278010889,0.020597577514337568,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.21,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,17,Garden,garden,C_exterior,binary,binary,0.033,,0.98,,,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,3.296473252778087,3.4803232443839884,100*(exp(b - se^2/2) - 1),|b/t|,0.020181703530428006,0.020593575031048982,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.98,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,17,Swimming_pool,pool,C_exterior,binary,binary,-0.185,,-5.49,,***,,,high,"Private or shared (apartment) pool; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-16.936745430952037,2.8006246359315714,100*(exp(b - se^2/2) - 1),|b/t|,-0.11236560392612475,0.020467323119512708,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.49,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,17,Washing_machine,appliances,B_interior,binary,binary,0.08,,2.62,,***,,,high,"; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,8.278218585820984,3.307746771526591,100*(exp(b - se^2/2) - 1),|b/t|,0.053887745104861835,0.020567841643077036,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.62,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,18,Direction: 1 (north),sunlight,E_environment,binary,binary,0.028,,0.64,,,,,high,"Orientation the house faces (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,2.7411948422199517,4.499231119343734,100*(exp(b - se^2/2) - 1),|b/t|,0.013181427645894146,0.020595980696709603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.64,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,18,Direction: 2 (northeast),sunlight,E_environment,binary,binary,0.053,,1.01,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,5.29788781340903,5.533145662507511,100*(exp(b - se^2/2) - 1),|b/t|,0.02079924748024231,0.020593314336873576,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.01,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,18,Direction: 3 (east),sunlight,E_environment,binary,binary,-0.049,,-1.04,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,-4.8875138149258035,4.486238014925648,100*(exp(b - se^2/2) - 1),|b/t|,-0.02141676762464164,0.020593045792924654,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.04,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,18,Direction: 4 (southeast),sunlight,E_environment,binary,binary,0.056,,1.47,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,5.6830544277114425,4.028943557091853,100*(exp(b - se^2/2) - 1),|b/t|,0.03026485195774136,0.020588334665130176,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.47,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,18,Direction: 5 (south),sunlight,E_environment,binary,binary,0.016,,0.46,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,1.5514199864070433,3.534360644890765,100*(exp(b - se^2/2) - 1),|b/t|,0.009474549014873825,0.020596845684508314,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.46,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,18,Direction: 6 (southwest),sunlight,E_environment,binary,binary,0.126,,1.8,,*,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,13.150657845664181,7.939975177981175,100*(exp(b - se^2/2) - 1),|b/t|,0.03705052975432005,0.020583627641288915,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,18,Direction: 7 (west),sunlight,E_environment,binary,binary,0.13,,2.32,,**,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,13.704190331828192,6.38136594104314,100*(exp(b - se^2/2) - 1),|b/t|,0.047732357608403116,0.02057429207258755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.32,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T6-c7,6,7,18,Direction: 8 (northwest),sunlight,E_environment,binary,binary,0.069,,1.2,,,,,high,"Orientation (base: unknown); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,0.599,t,"SAC model, Eq. (8); listings July 2017-January 2018 (Oct. missing), District 7 HCMC, houses on arterial roads; direct (own-coefficient) estimates; pseudo R2",pct_premium,6.966645438105812,6.160758202602992,100*(exp(b - se^2/2) - 1),|b/t|,0.02470977722860051,0.02059148102383376,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T7-total,7,Total effect,22,D_TR,flood_risk,E_environment,binary,binary,0.191,,4.52,,***,,,high,"Total effect of treatment-group indicator (direct 0.184 + spillover 0.007); stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,2367.0,,t,SAC decomposition: total effect (direct + spillover) of flood DiD variables; same sample as Table 6,pct_premium,20.937922202209847,5.114994587334695,100*(exp(b - se^2/2) - 1),|b/t|,0.09270102345841659,0.02050907598637535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.52,2357.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T8-c5m,8,5 months,24,D_TR = 1,flood_risk,E_environment,binary,binary,0.324,,12.9,,***,,,high,"Flood-affected treatment group indicator; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,3780.0,0.747,t,"Price-recovery SAC model, Panel A direct effects; post period extended to 5 months after the 30 Sep 2017 flood; other controls (location, structure, neighbourhood, facilities, direction, legal status) included but not reported; pseudo R2",pct_premium,38.221126993484745,3.47269556206753,100*(exp(b - se^2/2) - 1),|b/t|,0.20560778150316553,0.015938587713423682,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.9,3770.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,True
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T8-c6m,8,6 months,24,D_TR = 1,flood_risk,E_environment,binary,binary,0.306,,12.54,,***,,,high,"Flood-affected treatment group indicator; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,4389.0,0.751,t,"Price-recovery SAC model, Panel A direct effects; post period extended to 6 months after the 30 Sep 2017 flood; other controls (location, structure, neighbourhood, facilities, direction, legal status) included but not reported; pseudo R2",pct_premium,35.757805913717775,3.3137367288967714,100*(exp(b - se^2/2) - 1),|b/t|,0.1861868349566933,0.014847435004520999,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.54,4379.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T8-c7m,8,7 months,24,D_TR = 1,flood_risk,E_environment,binary,binary,0.3,,12.18,,***,,,high,"Flood-affected treatment group indicator; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,4850.0,0.752,t,"Price-recovery SAC model, Panel A direct effects; post period extended to 7 months after the 30 Sep 2017 flood; other controls (location, structure, neighbourhood, facilities, direction, legal status) included but not reported; pseudo R2",pct_premium,34.94494145730407,3.3247753881182343,100*(exp(b - se^2/2) - 1),|b/t|,0.17245219443148344,0.014158636652831154,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.18,4840.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T8-c8m,8,8 months,24,D_TR = 1,flood_risk,E_environment,binary,binary,0.323,,13.87,,***,,,high,"Flood-affected treatment group indicator; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,5644.0,0.764,t,"Price-recovery SAC model, Panel A direct effects; post period extended to 8 months after the 30 Sep 2017 flood; other controls (location, structure, neighbourhood, facilities, direction, legal status) included but not reported; pseudo R2",pct_premium,38.08908607853976,3.2166453377254403,100*(exp(b - se^2/2) - 1),|b/t|,0.1817093076055691,0.013100887354402966,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.87,5634.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T8-c9m,8,9 months,24,D_TR = 1,flood_risk,E_environment,binary,binary,0.32,,13.96,,***,,,high,"Flood-affected treatment group indicator; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,6117.0,0.768,t,"Price-recovery SAC model, Panel A direct effects; post period extended to 9 months after the 30 Sep 2017 flood; other controls (location, structure, neighbourhood, facilities, direction, legal status) included but not reported; pseudo R2",pct_premium,37.67660078635,3.1567398609420216,100*(exp(b - se^2/2) - 1),|b/t|,0.17585320932154466,0.012596934765153629,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.96,6107.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d,819ec939f0241cca8513d3a72e45a56254da737d:T8-c10m,8,10 months,24,D_TR = 1,flood_risk,E_environment,binary,binary,0.319,,13.98,,***,,,high,"Flood-affected treatment group indicator; stars: * p<0.10, ** p<0.05, *** p<0.01",Ln_Price: natural log of listing price (VND),log,SAC,6183.0,0.77,t,"Price-recovery SAC model, Panel A direct effects; post period extended to 10 months after the 30 Sep 2017 flood; other controls (location, structure, neighbourhood, facilities, direction, legal status) included but not reported; pseudo R2",pct_premium,37.539321161728246,3.1392322792920355,100*(exp(b - se^2/2) - 1),|b/t|,0.1751824625822494,0.012530934376412688,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.98,6173.0,binary,,2022.0,Vietnam,Asia,Lower middle income,2017.0,2018.0,mixed,listing,journal,False,False,unknown,,2017.5,spatial,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T3-M1,3,Model 1,8,Ln_PARCEL_AREA,lot_size,A_structural,log,m2,0.761,,9.7,,***,,,high,Log parcel area (sq m),Ln nominal selling price of the building (NIS),log,OLS,63.0,0.861,t,All buildings (designated + non-designated); adj. R2; year dummy 2009,elasticity,0.761,0.07845360824742269,b (log-log),|b/t|,0.7997977173045793,0.08245337291799784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.7,53.0,m2,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T3-M2,3,Model 2,8,Ln_PARCEL_AREA,lot_size,A_structural,log,m2,0.913,,8.74,,***,,,high,"Log parcel area (sq m); model includes Ln_PARCEL_AREA x DESIGNATED interaction, main effect refers to non-designated buildings",Ln nominal selling price of the building (NIS),log,OLS,63.0,0.869,t,All buildings; includes interactions Ln_PARCEL_AREA x DESIGNATED and Ln_BUILD_%_USED x DESIGNATED; adj. R2,elasticity,0.913,0.10446224256292906,b (log-log),|b/t|,0.7683606300861865,0.08791311557050191,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.74,53.0,m2,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,True
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T3-M3,3,Model 3,8,Ln_PARCEL_AREA,lot_size,A_structural,log,m2,1.014,,11.49,,***,,,high,"Log parcel area (sq m); model includes Ln_PARCEL_AREA x DESIGNATED interaction, main effect refers to non-designated buildings",Ln nominal selling price of the building (NIS),log,OLS,63.0,0.851,t,"All buildings, stepwise; includes interactions with DESIGNATED; adj. R2",elasticity,1.014,0.08825065274151436,b (log-log),|b/t|,0.8447157134217734,0.0735174685310508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.49,53.0,m2,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,True
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T3-M4,3,Model 4,8,Ln_PARCEL_AREA,lot_size,A_structural,log,m2,0.881,,8.22,,***,,,high,Log parcel area (sq m),Ln nominal selling price of the building (NIS),log,OLS,28.0,0.876,t,Non-designated buildings only; adj. R2,elasticity,0.881,0.10717761557177614,b (log-log),|b/t|,0.888618011652937,0.10810438097967599,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.22,18.0,m2,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T3-M5,3,Model 5,8,Ln_PARCEL_AREA,lot_size,A_structural,log,m2,0.901,,9.13,,***,,,high,Log parcel area (sq m),Ln nominal selling price of the building (NIS),log,OLS,28.0,0.872,t,"Non-designated buildings only, stepwise; adj. R2",elasticity,0.901,0.09868565169769988,b (log-log),|b/t|,0.9068680843847836,0.0993283772601077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.13,18.0,m2,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T3-M1,3,Model 1,8,LOCATION_MAIN_ROAD,highway_distance,D_location,binary,binary,-0.111,,-1.55,,,,,high,"Dummy: located on a main transportation artery (negative externality), not a distance",Ln nominal selling price of the building (NIS),log,OLS,63.0,0.861,t,All buildings (designated + non-designated); adj. R2; year dummy 2009,pct_premium,-10.735311688827842,6.4089162020079,100*(exp(b - se^2/2) - 1),|b/t|,-0.20824137224001543,0.1343492724129132,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.55,53.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T3-M2,3,Model 2,8,LOCATION_MAIN_ROAD,highway_distance,D_location,binary,binary,-0.12,,-1.71,,*,,,high,"Dummy: located on a main transportation artery (negative externality), not a distance",Ln nominal selling price of the building (NIS),log,OLS,63.0,0.869,t,All buildings; includes interactions Ln_PARCEL_AREA x DESIGNATED and Ln_BUILD_%_USED x DESIGNATED; adj. R2,pct_premium,-11.526073755682742,6.224003064681807,100*(exp(b - se^2/2) - 1),|b/t|,-0.22866337464643094,0.13372127172305903,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.71,53.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T3-M4,3,Model 4,8,LOCATION_MAIN_ROAD,highway_distance,D_location,binary,binary,-0.079,,-0.87,,,,,high,"Dummy: located on a main transportation artery (negative externality), not a distance",Ln nominal selling price of the building (NIS),log,OLS,28.0,0.876,t,Non-designated buildings only; adj. R2,pct_premium,-7.976180743006145,8.390707359903661,100*(exp(b - se^2/2) - 1),|b/t|,-0.20088093498583928,0.23089762642050493,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.87,18.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M6,4,Model 6,9,Ln_TOTAL_APT_AREA,living_area,A_structural,log,m2,0.702,,22.84,,***,,,high,Log total apartment area (sq m),Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,All apartments; adj. R2; transaction-year dummies,elasticity,0.702,0.03073555166374781,b (log-log),|b/t|,0.8347417977944027,0.0365473641766376,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.84,227.0,m2,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M7,4,Model 7,9,Ln_TOTAL_APT_AREA,living_area,A_structural,log,m2,0.7,,22.79,,***,,,high,Log total apartment area (sq m),Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,"All apartments, stepwise; adj. R2; transaction-year dummies",elasticity,0.7,0.030715225976305396,b (log-log),|b/t|,0.8341864584989062,0.036603179398811164,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.79,227.0,m2,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M8,4,Model 8,9,Ln_TOTAL_APT_AREA,living_area,A_structural,log,m2,0.708,,16.37,,***,,,high,Log total apartment area (sq m),Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.895,t,Apartments in non-designated buildings; adj. R2; transaction-year dummies,elasticity,0.708,0.0432498472816127,b (log-log),|b/t|,0.8144612252404024,0.0497532819328285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.37,136.0,m2,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M9,4,Model 9,9,Ln_TOTAL_APT_AREA,living_area,A_structural,log,m2,0.721,,17.07,,***,,,high,Log total apartment area (sq m),Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.894,t,"Apartments in non-designated buildings, stepwise; adj. R2; transaction-year dummies",elasticity,0.721,0.042237844171060336,b (log-log),|b/t|,0.8257031361677261,0.04837159555757034,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.07,136.0,m2,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M6,4,Model 6,9,PARKING,parking,A_structural,binary,binary,0.116,,4.43,,***,,,high,Parking spot within the building's plot,Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,All apartments; adj. R2; transaction-year dummies,pct_premium,12.261094170060293,2.9405760985882066,100*(exp(b - se^2/2) - 1),|b/t|,0.28208842443236587,0.06367684524432637,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.43,227.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M7,4,Model 7,9,PARKING,parking,A_structural,binary,binary,0.126,,5.01,,***,,,high,Parking spot within the building's plot,Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,"All apartments, stepwise; adj. R2; transaction-year dummies",pct_premium,13.392350404509612,2.8526856926878477,100*(exp(b - se^2/2) - 1),|b/t|,0.31553767189726445,0.06298157123697894,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.01,227.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M8,4,Model 8,9,PARKING,parking,A_structural,binary,binary,0.123,,4.43,,***,,,high,Parking spot within the building's plot,Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.895,t,Apartments in non-designated buildings; adj. R2; transaction-year dummies,pct_premium,13.044860080493436,3.139927399018988,100*(exp(b - se^2/2) - 1),|b/t|,0.35511104760481876,0.08016050736000424,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.43,136.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M9,4,Model 9,9,PARKING,parking,A_structural,binary,binary,0.128,,4.67,,***,,,high,Parking spot within the building's plot,Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.894,t,"Apartments in non-designated buildings, stepwise; adj. R2; transaction-year dummies",pct_premium,13.612616348209695,3.115177394972671,100*(exp(b - se^2/2) - 1),|b/t|,0.37175013444658306,0.07960388317913984,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.67,136.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M6,4,Model 6,9,ELEVATOR1,accessibility,B_interior,binary,binary,0.07,,2.93,,***,,,high,Elevator in building when apartment is on 2nd floor or higher,Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,All apartments; adj. R2; transaction-year dummies,pct_premium,7.220214738838737,2.562306235078333,100*(exp(b - se^2/2) - 1),|b/t|,0.19089471066534605,0.06515177838407715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.93,227.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M7,4,Model 7,9,ELEVATOR1,accessibility,B_interior,binary,binary,0.085,,3.98,,***,,,high,Elevator in building when apartment is on 2nd floor or higher,Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,"All apartments, stepwise; adj. R2; transaction-year dummies",pct_premium,8.846880642932131,2.3251495143056258,100*(exp(b - se^2/2) - 1),|b/t|,0.25540100524668813,0.06417110684590153,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.98,227.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M8,4,Model 8,9,ELEVATOR1,accessibility,B_interior,binary,binary,0.044,,1.48,,,,,high,Elevator in building when apartment is on 2nd floor or higher,Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.895,t,Apartments in non-designated buildings; adj. R2; transaction-year dummies,pct_premium,4.452064952062296,3.1067042983169952,100*(exp(b - se^2/2) - 1),|b/t|,0.12589914432601668,0.08506698940947073,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.48,136.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M9,4,Model 9,9,ELEVATOR1,accessibility,B_interior,binary,binary,0.056,,2.01,,**,,,high,Elevator in building when apartment is on 2nd floor or higher,Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.894,t,"Apartments in non-designated buildings, stepwise; adj. R2; transaction-year dummies",pct_premium,5.718729998214389,2.9465408104104593,100*(exp(b - se^2/2) - 1),|b/t|,0.16985168175475968,0.08450332425609935,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.01,136.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M6,4,Model 6,9,FLOOR,floor_level,A_structural,level,count,0.023,,2.93,,***,,,high,Floor on which the apartment is located,Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,All apartments; adj. R2; transaction-year dummies,semi_elasticity,2.3,0.7849829351535836,100*b/1 (per unit count),|b/t|,0.19089471066534605,0.06515177838407715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.93,227.0,count,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M7,4,Model 7,9,FLOOR,floor_level,A_structural,level,count,0.023,,2.92,,***,,,high,Floor on which the apartment is located,Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,"All apartments, stepwise; adj. R2; transaction-year dummies",semi_elasticity,2.3,0.7876712328767124,100*b/1 (per unit count),|b/t|,0.19026681769766302,0.06515986907454213,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.92,227.0,count,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M8,4,Model 8,9,FLOOR,floor_level,A_structural,level,count,0.021,,2.26,,**,,,high,Floor on which the apartment is located,Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.895,t,Apartments in non-designated buildings; adj. R2; transaction-year dummies,semi_elasticity,2.1,0.929203539823009,100*b/1 (per unit count),|b/t|,0.19025375472848016,0.08418307731348679,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.26,136.0,count,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M9,4,Model 9,9,FLOOR,floor_level,A_structural,level,count,0.019,,2.04,,**,,,high,Floor on which the apartment is located,Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.894,t,"Apartments in non-designated buildings, stepwise; adj. R2; transaction-year dummies",semi_elasticity,1.9,0.9313725490196079,100*b/1 (per unit count),|b/t|,0.17231204797842015,0.08446669018550007,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.04,136.0,count,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M6,4,Model 6,9,Ln_UNITS_PER_DUNAM,density,F_neighbourhood,log,count,-0.112,,-3.16,,***,,,high,Log number of apartments per dunam (1 dunam = 1000 sq m) of the building's plot,Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,All apartments; adj. R2; transaction-year dummies,elasticity,-0.112,0.035443037974683546,b (log-log),|b/t|,-0.20527029373215963,0.06495895371270874,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.16,227.0,count,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M7,4,Model 7,9,Ln_UNITS_PER_DUNAM,density,F_neighbourhood,log,count,-0.109,,-3.08,,***,,,high,Log number of apartments per dunam (1 dunam = 1000 sq m) of the building's plot,Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,"All apartments, stepwise; adj. R2; transaction-year dummies",elasticity,-0.109,0.03538961038961039,b (log-log),|b/t|,-0.20028463413412165,0.06502747861497456,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.08,227.0,count,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M8,4,Model 8,9,Ln_UNITS_PER_DUNAM,density,F_neighbourhood,log,count,-0.154,,-3.46,,***,,,high,Log number of apartments per dunam (1 dunam = 1000 sq m) of the building's plot,Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.895,t,Apartments in non-designated buildings; adj. R2; transaction-year dummies,elasticity,-0.154,0.04450867052023121,b (log-log),|b/t|,-0.28443753997644194,0.08220738149608148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.46,136.0,count,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,True
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M9,4,Model 9,9,Ln_UNITS_PER_DUNAM,density,F_neighbourhood,log,count,-0.14,,-3.16,,***,,,high,Log number of apartments per dunam (1 dunam = 1000 sq m) of the building's plot,Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.894,t,"Apartments in non-designated buildings, stepwise; adj. R2; transaction-year dummies",elasticity,-0.14,0.04430379746835443,b (log-log),|b/t|,-0.2615363587998367,0.08276467050627744,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.16,136.0,count,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M6,4,Model 6,9,BUILD_PRESERVED,renovation,A_structural,binary,binary,0.129,,3.14,,***,,,high,Designated building preserved (restored) before the transaction,Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,All apartments; adj. R2; transaction-year dummies,pct_premium,13.673043436421084,4.673949873164948,100*(exp(b - se^2/2) - 1),|b/t|,0.2040253597538615,0.064976229220975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.14,227.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M7,4,Model 7,9,BUILD_PRESERVED,renovation,A_structural,binary,binary,0.105,,2.8,,***,,,high,Designated building preserved (restored) before the transaction,Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,"All apartments, stepwise; adj. R2; transaction-year dummies",pct_premium,10.992991645266281,4.165164788833894,100*(exp(b - se^2/2) - 1),|b/t|,0.18271407158090092,0.06525502556460747,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8,227.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M6,4,Model 6,9,BUILD_RENOVATED,renovation,A_structural,binary,binary,0.022,,0.8,,,,,high,Non-designated building renovated before the transaction,Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,All apartments; adj. R2; transaction-year dummies,pct_premium,2.1857321609674685,2.8111704072937047,100*(exp(b - se^2/2) - 1),|b/t|,0.053023171217831094,0.06627896402228886,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8,227.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M8,4,Model 8,9,BUILD_RENOVATED,renovation,A_structural,binary,binary,0.033,,1.15,,,,,high,Non-designated building renovated before the transaction,Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.895,t,Apartments in non-designated buildings; adj. R2; transaction-year dummies,pct_premium,3.312509316722223,2.965840677822877,100*(exp(b - se^2/2) - 1),|b/t|,0.09813569210756053,0.08533538444135698,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.15,136.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M6,4,Model 6,9,LOCATION_MAIN_ROAD,highway_distance,D_location,binary,binary,-0.182,,-4.01,,***,,,high,"Dummy: located on a main transportation artery (negative externality), not a distance",Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,All apartments; adj. R2; transaction-year dummies,pct_premium,-16.725680088388295,3.78342753006643,100*(exp(b - se^2/2) - 1),|b/t|,-0.25719923318763943,0.06413945964779037,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.01,227.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M7,4,Model 7,9,LOCATION_MAIN_ROAD,highway_distance,D_location,binary,binary,-0.19,,-4.23,,***,,,high,"Dummy: located on a main transportation artery (negative externality), not a distance",Ln nominal selling price of the apartment (NIS),log,OLS,237.0,0.891,t,"All apartments, stepwise; adj. R2; transaction-year dummies",pct_premium,-17.387466527669325,3.714473651282242,100*(exp(b - se^2/2) - 1),|b/t|,-0.27030387415698603,0.06390162509621419,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.23,227.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M8,4,Model 8,9,LOCATION_MAIN_ROAD,highway_distance,D_location,binary,binary,-0.213,,-2.25,,**,,,high,"Dummy: located on a main transportation artery (negative externality), not a distance",Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.895,t,Apartments in non-designated buildings; adj. R2; transaction-year dummies,pct_premium,-19.545701951680094,7.650544765649424,100*(exp(b - se^2/2) - 1),|b/t|,-0.18944220058835148,0.08419653359482288,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.25,136.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,True
828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2,828367334a6cb48f8254ab88d9172664e3afd7a2:T4-M9,4,Model 9,9,LOCATION_MAIN_ROAD,highway_distance,D_location,binary,binary,-0.212,,-2.24,,**,,,high,"Dummy: located on a main transportation artery (negative externality), not a distance",Ln nominal selling price of the apartment (NIS),log,OLS,146.0,0.894,t,"Apartments in non-designated buildings, stepwise; adj. R2; transaction-year dummies",pct_premium,-19.465025912827315,7.656273030540086,100*(exp(b - se^2/2) - 1),|b/t|,-0.1886302580176659,0.0842099366150294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.24,136.0,binary,,2022.0,Israel,Asia,High income,1998.0,2009.0,mixed,transaction,journal,True,False,unknown,,2003.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-urban,7,Urban area,13,BUS,transit_distance,D_location,level,km,-0.016,0.011,,,,,,high,Distance to nearest bus station,ln residential property value (RM),log,OLS,680.0,0.539,se,Urban-area properties (R2 printed as 53.90 %),semi_elasticity,-1.6,1.0999999999999999,100*b/1 (X per km->km),reported,-0.05610547926785547,0.03857251699665063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4545454545454546,670.0,km,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-rural,7,Rural area,13,BUS,transit_distance,D_location,level,km,0.003,0.006,,,,,,high,Distance to nearest bus station,ln residential property value (RM),log,OLS,680.0,0.47,se,Rural-area properties (R2 printed as 47.00 %),semi_elasticity,0.3,0.6,100*b/1 (X per km->km),reported,0.019313082381200473,0.03862616476240095,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5,670.0,km,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-urban,7,Urban area,13,CITY,cbd_distance,D_location,level,km,0.041,0.012,,,***,,,high,Distance to nearest city centre,ln residential property value (RM),log,OLS,680.0,0.539,se,Urban-area properties (R2 printed as 53.90 %),semi_elasticity,4.1000000000000005,1.2,100*b/1 (X per km->km),reported,0.13086224595033083,0.03830114515619439,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4166666666666665,670.0,km,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-rural,7,Rural area,13,CITY,cbd_distance,D_location,level,km,-0.01,0.008,,,,,,high,Distance to nearest city centre,ln residential property value (RM),log,OLS,680.0,0.47,se,Rural-area properties (R2 printed as 47.00 %),semi_elasticity,-1.0,0.8,100*b/1 (X per km->km),reported,-0.04823550108010261,0.03858840086408209,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.25,670.0,km,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-urban,7,Urban area,13,LOT,lot_size,A_structural,level,sqft,0.0001,5e-05,,,***,,,high,Lot size in square feet,ln residential property value (RM),log,OLS,680.0,0.539,se,Urban-area properties (R2 printed as 53.90 %),semi_elasticity,0.10763910416709722,0.05381955208354861,100*b/0.092903 (X per sqft->m2),reported,0.07703712157713453,0.03851856078856727,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,670.0,sqft,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-rural,7,Rural area,13,LOT,lot_size,A_structural,level,sqft,0.0001,4e-05,,,***,,,high,Lot size in square feet,ln residential property value (RM),log,OLS,680.0,0.47,se,Rural-area properties (R2 printed as 47.00 %),semi_elasticity,0.10763910416709722,0.04305564166683889,100*b/0.092903 (X per sqft->m2),reported,0.09613607115671603,0.03845442846268641,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5,670.0,sqft,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-urban,7,Urban area,13,AGE,age,A_structural,level,years,-0.012,0.003,,,***,,,high,Age of house in years,ln residential property value (RM),log,OLS,680.0,0.539,se,Urban-area properties (R2 printed as 53.90 %),semi_elasticity,-1.2,0.3,100*b/1 (per year),reported,-0.1527207096642425,0.038180177416060626,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,670.0,years,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-rural,7,Rural area,13,AGE,age,A_structural,level,years,-0.01,0.002,,,***,,,high,Age of house in years,ln residential property value (RM),log,OLS,680.0,0.47,se,Rural-area properties (R2 printed as 47.00 %),semi_elasticity,-1.0,0.2,100*b/1 (per year),reported,-0.18966081045272037,0.03793216209054408,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,670.0,years,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-urban,7,Urban area,13,BED,bedrooms,A_structural,level,count,0.077,0.034,,,***,,,high,printed *** although beta/se = 2.3 (inconsistent stars in source),ln residential property value (RM),log,OLS,680.0,0.539,se,Urban-area properties (R2 printed as 53.90 %),semi_elasticity,7.7,3.4000000000000004,100*b/1 (per unit count),reported,0.08716024873081361,0.038486343595424195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.264705882352941,670.0,count,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-rural,7,Rural area,13,BED,bedrooms,A_structural,level,count,0.059,0.045,,,**,,,high,printed ** although beta/se = 1.3 (inconsistent stars in source),ln residential property value (RM),log,OLS,680.0,0.47,se,Rural-area properties (R2 printed as 47.00 %),semi_elasticity,5.8999999999999995,4.5,100*b/1 (per unit count),reported,0.05058778655728977,0.038583905001322714,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3111111111111111,670.0,count,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-urban,7,Urban area,13,BATH,bathrooms,A_structural,level,count,0.233,0.035,,,***,,,high,,ln residential property value (RM),log,OLS,680.0,0.539,se,Urban-area properties (R2 printed as 53.90 %),semi_elasticity,23.3,3.5000000000000004,100*b/1 (per unit count),reported,0.24908192655558284,0.037415740040538194,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.657142857142857,670.0,count,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-rural,7,Rural area,13,BATH,bathrooms,A_structural,level,count,0.18,0.042,,,***,,,high,,ln residential property value (RM),log,OLS,680.0,0.47,se,Rural-area properties (R2 printed as 47.00 %),semi_elasticity,18.0,4.2,100*b/1 (per unit count),reported,0.16334772268318037,0.038114468626075426,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.285714285714286,670.0,count,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-urban,7,Urban area,13,DAIRPORT,airport_distance,D_location,binary,binary,0.059,0.074,,,,,,high,"Dummy = 1 if within 10 km of airport (proximity dummy, not distance)",ln residential property value (RM),log,OLS,680.0,0.539,se,Urban-area properties (R2 printed as 53.90 %),pct_premium,5.787481063178834,7.849736781477176,100*(exp(b - se^2/2) - 1),reported,0.030787679943138198,0.03861505619986825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7972972972972973,670.0,binary,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-rural,7,Rural area,13,DAIRPORT,airport_distance,D_location,binary,binary,-0.112,0.09,,,,,,high,"Dummy = 1 if within 10 km of airport (proximity dummy, not distance)",ln residential property value (RM),log,OLS,680.0,0.47,se,Rural-area properties (R2 printed as 47.00 %),pct_premium,-10.956929935061677,8.046398317503215,100*(exp(b - se^2/2) - 1),reported,-0.04802161655277529,0.038588799015623,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2444444444444445,670.0,binary,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-urban,7,Urban area,13,DSCHOOL,school_distance,D_location,binary,binary,-0.139,0.094,,,,,,high,"Dummy = 1 if within 2 km of a school (proximity dummy, not distance)",ln residential property value (RM),log,OLS,680.0,0.539,se,Urban-area properties (R2 printed as 53.90 %),pct_premium,-13.360815859448982,8.180143467507564,100*(exp(b - se^2/2) - 1),reported,-0.0570350746046699,0.038570482106755184,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4787234042553192,670.0,binary,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42,85ea3296a5d9175ea12142cf209523d5db6d0b42:T7-rural,7,Rural area,13,DSCHOOL,school_distance,D_location,binary,binary,0.256,0.137,,,*,,,high,"Dummy = 1 if within 2 km of a school (proximity dummy, not distance)",ln residential property value (RM),log,OLS,680.0,0.47,se,Rural-area properties (R2 printed as 47.00 %),pct_premium,27.96869785282794,17.697012372773948,100*(exp(b - se^2/2) - 1),reported,0.07200344394239547,0.03853309304729758,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8686131386861313,670.0,binary,,2019.0,Malaysia,Asia,Upper middle income,2013.0,2014.0,single_family,appraisal,journal,False,False,unknown,,2013.5,ols,journal,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m1,5,1,46,BATHRMS,bathrooms,A_structural,level,count,0.0439,,1.705,,,,,high,number of bathrooms,ln(1994 sale price),log,OLS,1437.0,0.595,none,Test model 1: structural + neighbourhood + traffic-group dummies; adj. R2 reported; t-scores in column,semi_elasticity,4.390000000000001,2.5747800586510263,100*b/1 (per unit count),|b/t|,0.045088987535967955,0.026445153980039854,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.705,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m1,5,1,46,FIREPLC,fireplace,B_interior,level,count,0.0775,,5.38,,,,,high,number of fireplaces,ln(1994 sale price),log,OLS,1437.0,0.595,none,Test model 1: structural + neighbourhood + traffic-group dummies; adj. R2 reported; t-scores in column,semi_elasticity,7.75,1.4405204460966543,100*b/1 (per unit count),|b/t|,0.14099700267789986,0.026207621315594776,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.38,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m1,5,1,46,GARAGE,garage,A_structural,level,count (cars),0.0379,,2.638,,,,,high,number of cars that fit in garage,ln(1994 sale price),log,OLS,1437.0,0.595,none,Test model 1: structural + neighbourhood + traffic-group dummies; adj. R2 reported; t-scores in column,semi_elasticity,3.7900000000000005,1.43669446550417,100*b/1 (per unit count),|b/t|,0.0696636808131014,0.02640776376539098,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.638,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m1,5,1,46,SQFTBLD,living_area,A_structural,level,sqft,0.0006,,8.467,,,,,high,building area; squared term also included,ln(1994 sale price),log,OLS,1437.0,0.595,none,Test model 1: structural + neighbourhood + traffic-group dummies; adj. R2 reported; t-scores in column,semi_elasticity,0.6458346250025833,0.0762766770996319,100*b/0.092903 (X per sqft->m2),|b/t|,0.2187125187850698,0.025831170282871126,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.467,1427.0,sqft,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m1,5,1,46,SQFTLOT,lot_size,A_structural,level,sqft,1e-05,,1.23,,,,,high,lot size; squared term also included,ln(1994 sale price),log,OLS,1437.0,0.595,none,Test model 1: structural + neighbourhood + traffic-group dummies; adj. R2 reported; t-scores in column,semi_elasticity,0.010763910416709722,0.008751146680251808,100*b/0.092903 (X per sqft->m2),|b/t|,0.03254340778463125,0.026458055109456303,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.23,1427.0,sqft,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m1,5,1,46,STORIES,storeys,A_structural,level,"count (1, 1.5, 2)",0.0512,,1.497,,,,,high,number of stories,ln(1994 sale price),log,OLS,1437.0,0.595,none,Test model 1: structural + neighbourhood + traffic-group dummies; adj. R2 reported; t-scores in column,semi_elasticity,5.12,3.420173680694723,100*b/1 (per unit count),|b/t|,0.03959761838715894,0.02645131488788172,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.497,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m1,5,1,46,STRUCAGE,age,A_structural,level,years,-0.0037,,-2.56,,,,,high,age of structure; squared term also included,ln(1994 sale price),log,OLS,1437.0,0.595,none,Test model 1: structural + neighbourhood + traffic-group dummies; adj. R2 reported; t-scores in column,semi_elasticity,-0.37,0.14453125,100*b/1 (per year),|b/t|,-0.06761343457776167,0.026411497881938154,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.56,1427.0,years,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m2,5,2,46,BATHRMS,bathrooms,A_structural,level,count,0.0438,,1.702,,,,,high,number of bathrooms,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 2: structural + neighbourhood + continuous distance to arterial; adj. R2 reported; t-scores in column,semi_elasticity,4.38,2.573443008225617,100*b/1 (per unit count),|b/t|,0.045009812939773686,0.026445248495754223,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.702,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m2,5,2,46,FIREPLC,fireplace,B_interior,level,count,0.0781,,5.495,,,,,high,number of fireplaces,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 2: structural + neighbourhood + continuous distance to arterial; adj. R2 reported; t-scores in column,semi_elasticity,7.8100000000000005,1.4212920837124658,100*b/1 (per unit count),|b/t|,0.1439490678196906,0.026196372669643427,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.495,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m2,5,2,46,GARAGE,garage,A_structural,level,count (cars),0.0387,,2.72,,,,,high,number of cars that fit in garage,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 2: structural + neighbourhood + continuous distance to arterial; adj. R2 reported; t-scores in column,semi_elasticity,3.8699999999999997,1.4227941176470587,100*b/1 (per unit count),|b/t|,0.07181811597578265,0.026403719108743624,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.72,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m2,5,2,46,SQFTBLD,living_area,A_structural,level,sqft,0.0006,,8.541,,,,,high,building area; squared term also included,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 2: structural + neighbourhood + continuous distance to arterial; adj. R2 reported; t-scores in column,semi_elasticity,0.6458346250025833,0.0756158090390567,100*b/0.092903 (X per sqft->m2),|b/t|,0.22053144424971338,0.02582033066967725,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.541,1427.0,sqft,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m2,5,2,46,SQFTLOT,lot_size,A_structural,level,sqft,1e-06,,1.047,,,,,high,lot size; squared term also included,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 2: structural + neighbourhood + continuous distance to arterial; adj. R2 reported; t-scores in column,semi_elasticity,0.0010763910416709721,0.001028071673038178,100*b/0.092903 (X per sqft->m2),|b/t|,0.027705624799442996,0.026461914803670484,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.047,1427.0,sqft,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m2,5,2,46,STORIES,storeys,A_structural,level,"count (1, 1.5, 2)",0.0515,,1.506,,,,,high,number of stories,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 2: structural + neighbourhood + continuous distance to arterial; adj. R2 reported; t-scores in column,semi_elasticity,5.1499999999999995,3.4196547144754312,100*b/1 (per unit count),|b/t|,0.03983530357940319,0.02645106479376042,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.506,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m2,5,2,46,STRUCAGE,age,A_structural,level,years,-0.0036,,-2.512,,,,,high,age of structure; squared term also included,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 2: structural + neighbourhood + continuous distance to arterial; adj. R2 reported; t-scores in column,semi_elasticity,-0.36,0.14331210191082802,100*b/1 (per year),|b/t|,-0.06635131703873316,0.026413740859368297,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.512,1427.0,years,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m2,5,2,46,LINKDIST,highway_distance,D_location,level,feet,8e-05,,3.083,,,,,high,distance to nearest arterial link,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 2: structural + neighbourhood + continuous distance to arterial; adj. R2 reported; t-scores in column,semi_elasticity,26.246719160104988,8.513369821636388,100*b/0.0003048 (X per ft->km),|b/t|,0.08134295973133068,0.026384352815871127,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.083,1427.0,ft,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,True
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m3,5,3,46,BATHRMS,bathrooms,A_structural,level,count,0.0422,,1.635,,,,,high,number of bathrooms,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 3: structural + neighbourhood + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,4.22,2.581039755351682,100*b/1 (per unit count),|b/t|,0.043241362037477346,0.026447316230872993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.635,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m3,5,3,46,FIREPLC,fireplace,B_interior,level,count,0.0784,,5.494,,,,,high,number of fireplaces,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 3: structural + neighbourhood + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,7.84,1.4270112850382235,100*b/1 (per unit count),|b/t|,0.14392341412571272,0.026196471446252773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.494,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m3,5,3,46,GARAGE,garage,A_structural,level,count (cars),0.0392,,2.758,,,,,high,number of cars that fit in garage,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 3: structural + neighbourhood + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,3.92,1.4213197969543148,100*b/1 (per unit count),|b/t|,0.07281617384784791,0.02640180342561563,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.758,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m3,5,3,46,SQFTBLD,living_area,A_structural,level,sqft,0.00061,,8.512,,,,,high,building area; squared term also included,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 3: structural + neighbourhood + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,0.656598535419293,0.07713798583403347,100*b/0.092903 (X per sqft->m2),|b/t|,0.2198188950797638,0.0258245882377542,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.512,1427.0,sqft,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m3,5,3,46,SQFTLOT,lot_size,A_structural,level,sqft,7e-06,,0.947,,,,,high,lot size; squared term also included,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 3: structural + neighbourhood + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,0.007534737291696805,0.007956427974336648,100*b/0.092903 (X per sqft->m2),|b/t|,0.025061182982124782,0.02646376238872733,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.947,1427.0,sqft,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m3,5,3,46,STORIES,storeys,A_structural,level,"count (1, 1.5, 2)",0.0528,,1.538,,,,,high,number of stories,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 3: structural + neighbourhood + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,5.28,3.4330299089726917,100*b/1 (per unit count),|b/t|,0.04068035144529692,0.02645016348848955,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.538,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m3,5,3,46,STRUCAGE,age,A_structural,level,years,-0.0036,,-2.485,,,,,high,age of structure; squared term also included,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 3: structural + neighbourhood + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,-0.36,0.1448692152917505,100*b/1 (per year),|b/t|,-0.06564123554770517,0.026414984123825015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.485,1427.0,years,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m3,5,3,46,WIN85,highway_distance,D_location,dummy,binary (within 85 feet of any arterial),-0.0883,,-2.36,,,,,high,= 1 if house within 85 ft of an arterial (any traffic level),ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 3: structural + neighbourhood + distance bands to any arterial; adj. R2 reported; t-scores in column,pct_premium,-8.51543812548824,3.425314853705816,100*(exp(b - se^2/2) - 1),|b/t|,-0.06235253825753938,0.026420567058279398,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.36,1427.0,binary,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m3,5,3,46,WIN350,highway_distance,D_location,dummy,binary (85-350 feet of any arterial),-0.0603,,-3.265,,,,,high,= 1 if house between 85 and 350 ft of an arterial,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 3: structural + neighbourhood + distance bands to any arterial; adj. R2 reported; t-scores in column,pct_premium,-5.867850449397249,1.738786138129868,100*(exp(b - se^2/2) - 1),|b/t|,-0.08611029099525008,0.02637374915627874,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.265,1427.0,binary,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m3,5,3,46,WIN550,highway_distance,D_location,dummy,binary (350-550 feet of any arterial),-0.0153,,-0.8,,,,,high,= 1 if house between 350 and 550 ft of an arterial,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 3: structural + neighbourhood + distance bands to any arterial; adj. R2 reported; t-scores in column,pct_premium,-1.5363639187307099,1.8834614612882288,100*(exp(b - se^2/2) - 1),|b/t|,-0.021172913983928718,0.026466142479910897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8,1427.0,binary,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m4,5,4,46,BATHRMS,bathrooms,A_structural,level,count,0.0422,,1.637,,,,,high,number of bathrooms,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 4: structural + neighbourhood + traffic-group dummies + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,4.22,2.5778863775198535,100*b/1 (per unit count),|b/t|,0.043294157585533614,0.026447255702830554,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.637,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m4,5,4,46,FIREPLC,fireplace,B_interior,level,count,0.0786,,5.47,,,,,high,number of fireplaces,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 4: structural + neighbourhood + traffic-group dummies + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,7.86,1.436928702010969,100*b/1 (per unit count),|b/t|,0.1433076385291062,0.026198837025430754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.47,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m4,5,4,46,GARAGE,garage,A_structural,level,count (cars),0.0393,,2.76,,,,,high,number of cars that fit in garage,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 4: structural + neighbourhood + traffic-group dummies + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,3.93,1.423913043478261,100*b/1 (per unit count),|b/t|,0.07286869717667181,0.026401701875605733,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.76,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m4,5,4,46,SQFTBLD,living_area,A_structural,level,sqft,0.0006,,8.491,,,,,high,building area; squared term also included,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 4: structural + neighbourhood + traffic-group dummies + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,0.6458346250025833,0.07606107937846936,100*b/0.092903 (X per sqft->m2),|b/t|,0.21930269140898595,0.025827663574253437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.491,1427.0,sqft,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m4,5,4,46,SQFTLOT,lot_size,A_structural,level,sqft,7e-06,,0.948,,,,,high,lot size; squared term also included,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 4: structural + neighbourhood + traffic-group dummies + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,0.007534737291696805,0.007948035117823635,100*b/0.092903 (X per sqft->m2),|b/t|,0.025087630097286987,0.0264637448283618,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.948,1427.0,sqft,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m4,5,4,46,STORIES,storeys,A_structural,level,"count (1, 1.5, 2)",0.0533,,1.55,,,,,high,number of stories,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 4: structural + neighbourhood + traffic-group dummies + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,5.33,3.4387096774193546,100*b/1 (per unit count),|b/t|,0.04099722198840291,0.026449820637679294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.55,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m4,5,4,46,STRUCAGE,age,A_structural,level,years,-0.0036,,-2.47,,,,,high,age of structure; squared term also included,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 4: structural + neighbourhood + traffic-group dummies + distance bands to any arterial; adj. R2 reported; t-scores in column,semi_elasticity,-0.36,0.145748987854251,100*b/1 (per year),|b/t|,-0.06524670266691247,0.026415669095915976,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.47,1427.0,years,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m4,5,4,46,WIN85,highway_distance,D_location,dummy,binary (within 85 feet of any arterial),-0.094,,-2.39,,,,,high,= 1 if house within 85 ft of an arterial (any traffic level),ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 4: structural + neighbourhood + traffic-group dummies + distance bands to any arterial; adj. R2 reported; t-scores in column,pct_premium,-9.042101997387576,3.5801916171812596,100*(exp(b - se^2/2) - 1),|b/t|,-0.06314201492853798,0.026419253108174882,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.39,1427.0,binary,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m4,5,4,46,WIN350,highway_distance,D_location,dummy,binary (85-350 feet of any arterial),-0.066,,-2.944,,,,,high,= 1 if house between 85 and 350 ft of an arterial,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 4: structural + neighbourhood + traffic-group dummies + distance bands to any arterial; adj. R2 reported; t-scores in column,pct_premium,-6.4104350300953294,2.0986629430450696,100*(exp(b - se^2/2) - 1),|b/t|,-0.07769819433726627,0.026392049706951855,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.944,1427.0,binary,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T5-m4,5,4,46,WIN550,highway_distance,D_location,dummy,binary (350-550 feet of any arterial),-0.021,,-0.91,,,,,high,= 1 if house between 350 and 550 ft of an arterial,ln(1994 sale price),log,OLS,1437.0,0.597,none,Test model 4: structural + neighbourhood + traffic-group dummies + distance bands to any arterial; adj. R2 reported; t-scores in column,pct_premium,-2.1041739497426826,2.2597360720833684,100*(exp(b - se^2/2) - 1),|b/t|,-0.024082603196385933,0.02646439911690762,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.91,1427.0,binary,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T6-c1,6,1,47,BATHRMS,bathrooms,A_structural,level,count,0.0407,,1.557,0.12,,,,high,number of bathrooms; coefficients printed in scientific notation (e.g. 4.07E-02); p printed as 0 when <0.0005,ln(1994 sale price),log,OLS,1437.0,0.6,none,"Final model, White heteroskedasticity-consistent covariance; t-score and p-value in columns; R2 .60, adj. R2 .5963 (Table 7, p.48)",semi_elasticity,4.07,2.6140012845215157,100*b/1 (per unit count),|b/t|,0.041182057432323206,0.026449619417034817,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.557,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T6-c1,6,1,47,FIREPLC,fireplace,B_interior,level,count,0.076,,5.283,0.0,,,,high,number of fireplaces; coefficients printed in scientific notation (e.g. 4.07E-02); p printed as 0 when <0.0005,ln(1994 sale price),log,OLS,1437.0,0.6,none,"Final model, White heteroskedasticity-consistent covariance; t-score and p-value in columns; R2 .60, adj. R2 .5963 (Table 7, p.48)",semi_elasticity,7.6,1.4385765663448795,100*b/1 (per unit count),|b/t|,0.13850406918141944,0.026216935298394743,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.283,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T6-c1,6,1,47,GARAGE,garage,A_structural,level,count (cars),0.039,,2.733,0.006,,,,high,number of cars that fit in garage; coefficients printed in scientific notation (e.g. 4.07E-02); p printed as 0 when <0.0005,ln(1994 sale price),log,OLS,1437.0,0.6,none,"Final model, White heteroskedasticity-consistent covariance; t-score and p-value in columns; R2 .60, adj. R2 .5963 (Table 7, p.48)",semi_elasticity,3.9,1.4270032930845225,100*b/1 (per unit count),|b/t|,0.07215958125703849,0.02640306668753695,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.733,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T6-c1,6,1,47,SQFTBLD,living_area,A_structural,level,sqft,0.0006,,8.346,0.0,,,,high,building area; squared term also included; coefficients printed in scientific notation (e.g. 4.07E-02); p printed as 0 when <0.0005,ln(1994 sale price),log,OLS,1437.0,0.6,none,"Final model, White heteroskedasticity-consistent covariance; t-score and p-value in columns; R2 .60, adj. R2 .5963 (Table 7, p.48)",semi_elasticity,0.6458346250025833,0.07738253354931503,100*b/0.092903 (X per sqft->m2),|b/t|,0.21573341885144742,0.025848720207458358,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.346,1427.0,sqft,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T6-c1,6,1,47,SQFTLOT,lot_size,A_structural,level,sqft,8e-06,,1.08,0.28,,,,high,lot size; squared term also included; coefficients printed in scientific notation (e.g. 4.07E-02); p printed as 0 when <0.0005,ln(1994 sale price),log,OLS,1437.0,0.6,none,"Final model, White heteroskedasticity-consistent covariance; t-score and p-value in columns; R2 .60, adj. R2 .5963 (Table 7, p.48)",semi_elasticity,0.008611128333367777,0.007973266975340534,100*b/0.092903 (X per sqft->m2),|b/t|,0.02857816568745809,0.02646126452542416,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.08,1427.0,sqft,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T6-c1,6,1,47,STORIES,storeys,A_structural,level,"count (1, 1.5, 2)",0.053,,1.547,0.122,,,,high,number of stories; coefficients printed in scientific notation (e.g. 4.07E-02); p printed as 0 when <0.0005,ln(1994 sale price),log,OLS,1437.0,0.6,none,"Final model, White heteroskedasticity-consistent covariance; t-score and p-value in columns; R2 .60, adj. R2 .5963 (Table 7, p.48)",semi_elasticity,5.3,3.4259857789269557,100*b/1 (per unit count),|b/t|,0.04091800550855998,0.02644990659893987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.547,1427.0,count,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T6-c1,6,1,47,STRUCAGE,age,A_structural,level,years,-0.0036,,-2.466,0.014,,,,high,age of structure; squared term also included; coefficients printed in scientific notation (e.g. 4.07E-02); p printed as 0 when <0.0005,ln(1994 sale price),log,OLS,1437.0,0.6,none,"Final model, White heteroskedasticity-consistent covariance; t-score and p-value in columns; R2 .60, adj. R2 .5963 (Table 7, p.48)",semi_elasticity,-0.36,0.145985401459854,100*b/1 (per year),|b/t|,-0.06514148872305812,0.02641585106368942,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.466,1427.0,years,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T6-c1,6,1,47,HIGH85,highway_distance,D_location,dummy,binary (within 85 feet of high-traffic arterial),-0.1022,,-2.331,0.02,,,,high,= 1 if house within 85 ft of a high-traffic arterial; reference: not near high-traffic arterial; coefficients printed in scientific notation (e.g. 4.07E-02); p printed as 0 when <0.0005,ln(1994 sale price),log,OLS,1437.0,0.6,none,"Final model, White heteroskedasticity-consistent covariance; t-score and p-value in columns; R2 .60, adj. R2 .5963 (Table 7, p.48)",pct_premium,-9.80183847392302,3.9584368984209553,100*(exp(b - se^2/2) - 1),|b/t|,-0.06158926618772857,0.026421821616357175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.331,1427.0,binary,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T6-c1,6,1,47,HIGH350,highway_distance,D_location,dummy,binary (85-350 feet of high-traffic arterial),-0.0463,,-2.237,0.025,,,,high,= 1 if house between 85 and 350 ft of a high-traffic arterial; coefficients printed in scientific notation (e.g. 4.07E-02); p printed as 0 when <0.0005,ln(1994 sale price),log,OLS,1437.0,0.6,none,"Final model, White heteroskedasticity-consistent covariance; t-score and p-value in columns; R2 .60, adj. R2 .5963 (Table 7, p.48)",pct_premium,-4.544898499453376,1.9760920566028706,100*(exp(b - se^2/2) - 1),|b/t|,-0.05911447581545815,0.02642578266225219,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.237,1427.0,binary,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09,85ec88163a881d2f9a23ced6110d5e4e05b48d09:T6-c1,6,1,47,HIGH550,highway_distance,D_location,dummy,binary (350-550 feet of high-traffic arterial),0.00558,,0.26,0.794,,,,high,= 1 if house between 350 and 550 ft of a high-traffic arterial; coefficients printed in scientific notation (e.g. 4.07E-02); p printed as 0 when <0.0005,ln(1994 sale price),log,OLS,1437.0,0.6,none,"Final model, White heteroskedasticity-consistent covariance; t-score and p-value in columns; R2 .60, adj. R2 .5963 (Table 7, p.48)",pct_premium,0.5364036386425131,2.1581628586003414,100*(exp(b - se^2/2) - 1),|b/t|,0.006882576938168896,0.02647144976218806,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.26,1427.0,binary,,1997.0,United States,North America,High income,1994.0,1994.0,single_family,transaction,thesis,False,False,robust,,1994.0,ols,other,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-A,5,Regression A,16,Ln (Floor),living_area,A_structural,log,m2,0.5825,0.0086,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.71,se,"Treatment + control regions; years 2003-2006 and 2010-2013 (2007-2009 excluded); zip-code, year, month dummies",elasticity,0.5825,0.0086,b (log-log),reported,0.516340359331432,0.00762322247253273,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),67.73255813953489,12620.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-A,5,Regression A,16,Ln (Age),age,A_structural,log,years,-0.0679,0.0023,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.71,se,"Treatment + control regions; years 2003-2006 and 2010-2013 (2007-2009 excluded); zip-code, year, month dummies",elasticity,-0.0679,0.0023,b (log-log),reported,-0.2541623907415493,0.008609329877843347,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-29.521739130434785,12620.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-A,5,Regression A,16,Ln (Lot),lot_size,A_structural,log,m2,0.0097,0.0013,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.71,se,"Treatment + control regions; years 2003-2006 and 2010-2013 (2007-2009 excluded); zip-code, year, month dummies",elasticity,0.0097,0.0013,b (log-log),reported,0.06627394786719135,0.00888207548735554,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.461538461538462,12620.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-A,5,Regression A,16,Twin-house,dwelling_type,A_structural,dummy,binary,-0.074,0.0069,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.71,se,"Treatment + control regions; years 2003-2006 and 2010-2013 (2007-2009 excluded); zip-code, year, month dummies",pct_premium,-7.13504129252579,0.6407834687504882,100*(exp(b - se^2/2) - 1),reported,-0.09503484044742373,0.008861356744421943,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.72463768115942,12620.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-A,5,Regression A,16,Row-house,dwelling_type,A_structural,dummy,binary,-0.1168,0.0074,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.71,se,"Treatment + control regions; years 2003-2006 and 2010-2013 (2007-2009 excluded); zip-code, year, month dummies",pct_premium,-11.026123338600158,0.6584247147162512,100*(exp(b - se^2/2) - 1),reported,-0.13913505551717684,0.008815063448862232,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.783783783783782,12620.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-A,5,Regression A,16,Apartment,dwelling_type,A_structural,dummy,binary,0.0017,0.0086,,,,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.71,se,"Treatment + control regions; years 2003-2006 and 2010-2013 (2007-2009 excluded); zip-code, year, month dummies",pct_premium,0.16644035846302696,0.8614632434044961,100*(exp(b - se^2/2) - 1),reported,0.00175962498667754,0.008901632285545203,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.19767441860465115,12620.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-B,5,Regression B,16,Ln (Floor),living_area,A_structural,log,m2,0.5828,0.0086,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7117,se,As Regression A with town-specific treatment dummies,elasticity,0.5828,0.0086,b (log-log),reported,0.5165353476024656,0.007622175685280035,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),67.76744186046511,12620.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-B,5,Regression B,16,Ln (Age),age,A_structural,log,years,-0.0676,0.0023,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7117,se,As Regression A with town-specific treatment dummies,elasticity,-0.0676,0.0023,b (log-log),reported,-0.2531115267173383,0.008611782713755593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-29.391304347826086,12620.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-B,5,Regression B,16,Ln (Lot),lot_size,A_structural,log,m2,0.0098,0.0013,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7117,se,As Regression A with town-specific treatment dummies,elasticity,0.0098,0.0013,b (log-log),reported,0.06695413714907955,0.008881671254469736,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.538461538461538,12620.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-B,5,Regression B,16,Twin-house,dwelling_type,A_structural,dummy,binary,-0.0737,0.0069,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7117,se,As Regression A with town-specific treatment dummies,pct_premium,-7.107177625572481,0.6409757326292531,100*(exp(b - se^2/2) - 1),reported,-0.09465302279545323,0.00886168056022561,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.681159420289855,12620.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-B,5,Regression B,16,Row-house,dwelling_type,A_structural,dummy,binary,-0.116,0.0074,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7117,se,As Regression A with town-specific treatment dummies,pct_premium,-10.954915758036554,0.6589516652401298,100*(exp(b - se^2/2) - 1),reported,-0.138200338520747,0.008816228491840758,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.675675675675675,12620.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-B,5,Regression B,16,Apartment,dwelling_type,A_structural,dummy,binary,0.0029,0.0086,,,,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7117,se,As Regression A with town-specific treatment dummies,pct_premium,0.2867122355868279,0.8624976197982924,100*(exp(b - se^2/2) - 1),reported,0.0030017043365377916,0.008901605963525865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3372093023255814,12620.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-C,5,Regression C,16,Ln (Floor),living_area,A_structural,log,m2,0.6338,0.0055,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,18918.0,0.8146,se,Core town (Kristiansand) + control region; 2007-2009 excluded,elasticity,0.6338,0.0055,b (log-log),reported,0.642312635100817,0.00557387108402413,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),115.23636363636365,18908.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-C,5,Regression C,16,Ln (Age),age,A_structural,log,years,-0.0728,0.0018,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,18918.0,0.8146,se,Core town (Kristiansand) + control region; 2007-2009 excluded,elasticity,-0.0728,0.0018,b (log-log),reported,-0.28217529053218315,0.006976861579092441,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-40.44444444444445,18908.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-C,5,Regression C,16,Ln (Lot),lot_size,A_structural,log,m2,0.0076,0.0013,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,18918.0,0.8146,se,Core town (Kristiansand) + control region; 2007-2009 excluded,elasticity,0.0076,0.0013,b (log-log),reported,0.04247714205263422,0.007265826930055854,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.846153846153847,18908.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-C,5,Regression C,16,Twin-house,dwelling_type,A_structural,dummy,binary,-0.0866,0.0053,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,18918.0,0.8146,se,Core town (Kristiansand) + control region; 2007-2009 excluded,pct_premium,-8.296903997492954,0.48603323510213664,100*(exp(b - se^2/2) - 1),reported,-0.1179979671966721,0.00722158459748686,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.339622641509433,18908.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-C,5,Regression C,16,Row-house,dwelling_type,A_structural,dummy,binary,-0.1104,0.0053,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,18918.0,0.8146,se,Core town (Kristiansand) + control region; 2007-2009 excluded,pct_premium,-10.453670357073342,0.4746022128487805,100*(exp(b - se^2/2) - 1),reported,-0.14977649850018548,0.007190357264954557,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-20.830188679245282,18908.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-C,5,Regression C,16,Apartment,dwelling_type,A_structural,dummy,binary,-0.0486,0.0062,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,18918.0,0.8146,se,Core town (Kristiansand) + control region; 2007-2009 excluded,pct_premium,-4.745622973217223,0.59058848856772,100*(exp(b - se^2/2) - 1),reported,-0.056913758039093466,0.0072606028774152166,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.838709677419355,18908.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-D,5,Regression D,16,Ln (Floor),living_area,A_structural,log,m2,0.585,0.0072,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6911,se,"Treatment + control regions, all years 2003-2013, four treatment-period dummies",elasticity,0.585,0.0072,b (log-log),reported,0.5269139585733711,0.006485094874749183,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),81.25,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-D,5,Regression D,16,Ln (Age),age,A_structural,log,years,-0.0628,0.002,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6911,se,"Treatment + control regions, all years 2003-2013, four treatment-period dummies",elasticity,-0.0628,0.002,b (log-log),reported,-0.23299590632085806,0.007420251793657902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.399999999999995,17176.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-D,5,Regression D,16,Ln (Lot),lot_size,A_structural,log,m2,0.0094,0.0011,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6911,se,"Treatment + control regions, all years 2003-2013, four treatment-period dummies",elasticity,0.0094,0.0011,b (log-log),reported,0.0650658181749187,0.007614085105575593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.545454545454545,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-D,5,Regression D,16,Twin-house,dwelling_type,A_structural,dummy,binary,-0.0694,0.0058,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6911,se,"Treatment + control regions, all years 2003-2013, four treatment-period dummies",pct_premium,-6.706226808227078,0.5411129859561633,100*(exp(b - se^2/2) - 1),reported,-0.09092177261175431,0.007598649584267651,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.965517241379311,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-D,5,Regression D,16,Row-house,dwelling_type,A_structural,dummy,binary,-0.1127,0.0064,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6911,se,"Treatment + control regions, all years 2003-2013, four treatment-period dummies",pct_premium,-10.65996515166483,0.5717879331263037,100*(exp(b - se^2/2) - 1),reported,-0.1331672975132452,0.00756229551095625,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.609375,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T5-D,5,Regression D,16,Apartment,dwelling_type,A_structural,dummy,binary,0.003,0.0073,,,,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6911,se,"Treatment + control regions, all years 2003-2013, four treatment-period dummies",pct_premium,0.29777798043959525,0.7321932882874652,100*(exp(b - se^2/2) - 1),reported,0.003135705326685974,0.007630216294935872,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.410958904109589,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2005,6,2005,18,Ln (Floor),living_area,A_structural,log,m2,0.5845,0.0072,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2005",elasticity,0.5845,0.0072,b (log-log),reported,0.5265885244291887,0.006486633662771872,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),81.18055555555556,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2005,6,2005,18,Ln (Age),age,A_structural,log,years,-0.0629,0.002,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2005",elasticity,-0.0629,0.002,b (log-log),reported,-0.23334673220192167,0.007419609926929148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.45,17176.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2005,6,2005,18,Ln (Lot),lot_size,A_structural,log,m2,0.0094,0.0011,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2005",elasticity,0.0094,0.0011,b (log-log),reported,0.0650658181749187,0.007614085105575593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.545454545454545,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2005,6,2005,18,Twin-house,dwelling_type,A_structural,dummy,binary,-0.0695,0.0058,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2005",pct_premium,-6.715555719092947,0.5410588773630425,100*(exp(b - se^2/2) - 1),reported,-0.0910516984496127,0.007598559007305806,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.982758620689657,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2005,6,2005,18,Row-house,dwelling_type,A_structural,dummy,binary,-0.1131,0.0064,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2005",pct_premium,-10.695694019354251,0.5715592636899893,100*(exp(b - se^2/2) - 1),reported,-0.13363151546728688,0.007561818735549391,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.671875,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2005,6,2005,18,Apartment,dwelling_type,A_structural,dummy,binary,0.0031,0.0073,,,,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2005",pct_premium,0.30780825974323633,0.7322665112773824,100*(exp(b - se^2/2) - 1),reported,0.0032402277578750553,0.007630213752415452,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4246575342465753,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2006,6,2006,18,Ln (Floor),living_area,A_structural,log,m2,0.5848,0.0072,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2006",elasticity,0.5848,0.0072,b (log-log),reported,0.5267838127110238,0.006485710416414794,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),81.22222222222223,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2006,6,2006,18,Ln (Age),age,A_structural,log,years,-0.0629,0.002,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2006",elasticity,-0.0629,0.002,b (log-log),reported,-0.23334673220192167,0.007419609926929148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.45,17176.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2006,6,2006,18,Ln (Lot),lot_size,A_structural,log,m2,0.0094,0.0011,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2006",elasticity,0.0094,0.0011,b (log-log),reported,0.0650658181749187,0.007614085105575593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.545454545454545,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2006,6,2006,18,Twin-house,dwelling_type,A_structural,dummy,binary,-0.0693,0.0058,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2006",pct_premium,-6.696896964423493,0.5411670999604141,100*(exp(b - se^2/2) - 1),reported,-0.09079184213087274,0.007598740034041297,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.948275862068966,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2006,6,2006,18,Row-house,dwelling_type,A_structural,dummy,binary,-0.1131,0.0064,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2006",pct_premium,-10.695694019354251,0.5715592636899893,100*(exp(b - se^2/2) - 1),reported,-0.13363151546728688,0.007561818735549391,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.671875,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2006,6,2006,18,Apartment,dwelling_type,A_structural,dummy,binary,0.0032,0.0073,,,,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2006",pct_premium,0.3178395421249869,0.7323397415899648,100*(exp(b - se^2/2) - 1),reported,0.003344750082865261,0.0076302111265363765,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4383561643835617,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2007,6,2007,18,Ln (Floor),living_area,A_structural,log,m2,0.585,0.0072,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6902,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2007",elasticity,0.585,0.0072,b (log-log),reported,0.5269139585733711,0.006485094874749183,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),81.25,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2007,6,2007,18,Ln (Age),age,A_structural,log,years,-0.0629,0.002,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6902,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2007",elasticity,-0.0629,0.002,b (log-log),reported,-0.23334673220192167,0.007419609926929148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.45,17176.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2007,6,2007,18,Ln (Lot),lot_size,A_structural,log,m2,0.0094,0.0011,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6902,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2007",elasticity,0.0094,0.0011,b (log-log),reported,0.0650658181749187,0.007614085105575593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.545454545454545,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2007,6,2007,18,Twin-house,dwelling_type,A_structural,dummy,binary,-0.0692,0.0058,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6902,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2007",pct_premium,-6.6875661875888675,0.5412212193763357,100*(exp(b - se^2/2) - 1),reported,-0.09066190701338228,0.007598830356612965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.931034482758621,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2007,6,2007,18,Row-house,dwelling_type,A_structural,dummy,binary,-0.1129,0.0064,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6902,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2007",pct_premium,-10.677831371952918,0.5716735869746747,100*(exp(b - se^2/2) - 1),reported,-0.13339941746583642,0.007562057323129787,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.640625,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2007,6,2007,18,Apartment,dwelling_type,A_structural,dummy,binary,0.0032,0.0073,,,,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6902,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2007",pct_premium,0.3178395421249869,0.7323397415899648,100*(exp(b - se^2/2) - 1),reported,0.003344750082865261,0.0076302111265363765,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4383561643835617,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2008,6,2008,18,Ln (Floor),living_area,A_structural,log,m2,0.5853,0.0072,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6905,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2008",elasticity,0.5853,0.0072,b (log-log),reported,0.5271091078908645,0.006484171496350973,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),81.29166666666667,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2008,6,2008,18,Ln (Age),age,A_structural,log,years,-0.0628,0.002,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6905,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2008",elasticity,-0.0628,0.002,b (log-log),reported,-0.23299590632085806,0.007420251793657902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.399999999999995,17176.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2008,6,2008,18,Ln (Lot),lot_size,A_structural,log,m2,0.0094,0.0011,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6905,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2008",elasticity,0.0094,0.0011,b (log-log),reported,0.0650658181749187,0.007614085105575593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.545454545454545,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2008,6,2008,18,Twin-house,dwelling_type,A_structural,dummy,binary,-0.069,0.0058,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6905,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2008",pct_premium,-6.668901834453289,0.5413294744453572,100*(exp(b - se^2/2) - 1),reported,-0.09040202289423764,0.007599010620095337,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.896551724137932,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2008,6,2008,18,Row-house,dwelling_type,A_structural,dummy,binary,-0.1128,0.0064,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6905,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2008",pct_premium,-10.668898708464381,0.5717307571918354,100*(exp(b - se^2/2) - 1),reported,-0.13328336023121914,0.007562176467019526,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.625,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2008,6,2008,18,Apartment,dwelling_type,A_structural,dummy,binary,0.0032,0.0073,,,,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6905,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2008",pct_premium,0.3178395421249869,0.7323397415899648,100*(exp(b - se^2/2) - 1),reported,0.003344750082865261,0.0076302111265363765,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4383561643835617,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2009,6,2009,18,Ln (Floor),living_area,A_structural,log,m2,0.5853,0.0072,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6909,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2009",elasticity,0.5853,0.0072,b (log-log),reported,0.5271091078908645,0.006484171496350973,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),81.29166666666667,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2009,6,2009,18,Ln (Age),age,A_structural,log,years,-0.0628,0.002,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6909,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2009",elasticity,-0.0628,0.002,b (log-log),reported,-0.23299590632085806,0.007420251793657902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.399999999999995,17176.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2009,6,2009,18,Ln (Lot),lot_size,A_structural,log,m2,0.0094,0.0011,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6909,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2009",elasticity,0.0094,0.0011,b (log-log),reported,0.0650658181749187,0.007614085105575593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.545454545454545,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2009,6,2009,18,Twin-house,dwelling_type,A_structural,dummy,binary,-0.0693,0.0058,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6909,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2009",pct_premium,-6.696896964423493,0.5411670999604141,100*(exp(b - se^2/2) - 1),reported,-0.09079184213087274,0.007598740034041297,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.948275862068966,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2009,6,2009,18,Row-house,dwelling_type,A_structural,dummy,binary,-0.1126,0.0064,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6909,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2009",pct_premium,-10.651030701464936,0.5718451147786513,100*(exp(b - se^2/2) - 1),reported,-0.13305122931634453,0.007562414454925444,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.59375,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2009,6,2009,18,Apartment,dwelling_type,A_structural,dummy,binary,0.0029,0.0073,,,,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6909,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2009",pct_premium,0.28774870411372167,0.7321200726194809,100*(exp(b - se^2/2) - 1),reported,0.003031182792723618,0.007630218754097384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3972602739726027,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2010,6,2010,18,Ln (Floor),living_area,A_structural,log,m2,0.5852,0.0072,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6909,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2010",elasticity,0.5852,0.0072,b (log-log),reported,0.5270440673810172,0.00648447929792092,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),81.27777777777779,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2010,6,2010,18,Ln (Age),age,A_structural,log,years,-0.0627,0.002,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6909,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2010",elasticity,-0.0627,0.002,b (log-log),reported,-0.2326449894471912,0.007420892805333051,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.35,17176.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2010,6,2010,18,Ln (Lot),lot_size,A_structural,log,m2,0.0094,0.0011,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6909,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2010",elasticity,0.0094,0.0011,b (log-log),reported,0.0650658181749187,0.007614085105575593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.545454545454545,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2010,6,2010,18,Twin-house,dwelling_type,A_structural,dummy,binary,-0.0693,0.0058,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6909,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2010",pct_premium,-6.696896964423493,0.5411670999604141,100*(exp(b - se^2/2) - 1),reported,-0.09079184213087274,0.007598740034041297,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.948275862068966,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2010,6,2010,18,Row-house,dwelling_type,A_structural,dummy,binary,-0.1128,0.0064,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6909,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2010",pct_premium,-10.668898708464381,0.5717307571918354,100*(exp(b - se^2/2) - 1),reported,-0.13328336023121914,0.007562176467019526,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.625,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T6-c2010,6,2010,18,Apartment,dwelling_type,A_structural,dummy,binary,0.0034,0.0073,,,,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6909,se,"Treatment + control regions, all years 2003-2013; treatment assumed to start in 2010",pct_premium,0.33790511652396216,0.732486224186054,100*(exp(b - se^2/2) - 1),reported,0.003553794400546739,0.007630205624703293,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4657534246575342,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob1,7,Rob-1,19,Ln (Floor),living_area,A_structural,log,m2,0.582,0.0086,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7095,se,Regression A with mutual-debt parameter zeta = 1.0,elasticity,0.582,0.0086,b (log-log),reported,0.5160152003458163,0.007624966877962235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),67.67441860465115,12620.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob1,7,Rob-1,19,Ln (Age),age,A_structural,log,years,-0.069,0.0023,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7095,se,Regression A with mutual-debt parameter zeta = 1.0,elasticity,-0.069,0.0023,b (log-log),reported,-0.25800784355766804,0.008600261451922268,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.000000000000004,12620.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob1,7,Rob-1,19,Ln (Lot),lot_size,A_structural,log,m2,0.0098,0.0013,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7095,se,Regression A with mutual-debt parameter zeta = 1.0,elasticity,0.0098,0.0013,b (log-log),reported,0.06695413714907955,0.008881671254469736,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.538461538461538,12620.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob1,7,Rob-1,19,Twin-house,dwelling_type,A_structural,dummy,binary,-0.0752,0.0069,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7095,se,Regression A with mutual-debt parameter zeta = 1.0,pct_premium,-7.246412406941571,0.6400149897675949,100*(exp(b - se^2/2) - 1),reported,-0.09656169005196033,0.008860048688278275,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.898550724637682,12620.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob1,7,Rob-1,19,Row-house,dwelling_type,A_structural,dummy,binary,-0.1168,0.0074,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7095,se,Regression A with mutual-debt parameter zeta = 1.0,pct_premium,-11.026123338600158,0.6584247147162512,100*(exp(b - se^2/2) - 1),reported,-0.13913505551717684,0.008815063448862232,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.783783783783782,12620.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob1,7,Rob-1,19,Apartment,dwelling_type,A_structural,dummy,binary,-0.0006,0.0086,,,,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7095,se,Regression A with mutual-debt parameter zeta = 1.0,pct_premium,-0.06367771713080561,0.8594841547690446,100*(exp(b - se^2/2) - 1),reported,-0.0006210449546429375,0.008901644349882103,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.06976744186046512,12620.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob2,7,Rob-2,19,Ln (Floor),living_area,A_structural,log,m2,0.5832,0.0086,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7101,se,Regression A with zeta = 0.7,elasticity,0.5832,0.0086,b (log-log),reported,0.5167952070187263,0.007620779801716472,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),67.81395348837209,12620.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob2,7,Rob-2,19,Ln (Age),age,A_structural,log,years,-0.0664,0.0023,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7101,se,Regression A with zeta = 0.7,elasticity,-0.0664,0.0023,b (log-log),reported,-0.24889913073219927,0.00862150603439847,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-28.869565217391305,12620.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob2,7,Rob-2,19,Ln (Lot),lot_size,A_structural,log,m2,0.0097,0.0013,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7101,se,Regression A with zeta = 0.7,elasticity,0.0097,0.0013,b (log-log),reported,0.06627394786719135,0.00888207548735554,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.461538461538462,12620.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob2,7,Rob-2,19,Twin-house,dwelling_type,A_structural,dummy,binary,-0.0725,0.0069,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7101,se,Regression A with zeta = 0.7,pct_premium,-6.995639329129899,0.6417453651955922,100*(exp(b - se^2/2) - 1),reported,-0.0931253360558319,0.00886296301772745,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.507246376811594,12620.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob2,7,Rob-2,19,Row-house,dwelling_type,A_structural,dummy,binary,-0.1167,0.0075,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7101,se,Regression A with zeta = 0.7,pct_premium,-11.017291798192119,0.6673890815675231,100*(exp(b - se^2/2) - 1),reported,-0.13719978226421534,0.008817466726491988,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.56,12620.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob2,7,Rob-2,19,Apartment,dwelling_type,A_structural,dummy,binary,0.0048,0.0086,,,,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,12630.0,0.7101,se,Regression A with zeta = 0.7,pct_premium,0.47743812104892314,0.86413792307056,100*(exp(b - se^2/2) - 1),reported,0.0049682992754049365,0.008901536201767177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5581395348837209,12620.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob3,7,Rob-3,19,Ln (Floor),living_area,A_structural,log,m2,0.5844,0.0072,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,Placebo: treatment assumed to start in 2004; all years,elasticity,0.5844,0.0072,b (log-log),reported,0.526523409802573,0.006486941393871536,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),81.16666666666667,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob3,7,Rob-3,19,Ln (Age),age,A_structural,log,years,-0.063,0.002,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,Placebo: treatment assumed to start in 2004; all years,elasticity,-0.063,0.002,b (log-log),reported,-0.23369746698490032,0.007418967205869853,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.5,17176.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob3,7,Rob-3,19,Ln (Lot),lot_size,A_structural,log,m2,0.0094,0.0011,,,***,,,high,"Lot = lot size exceeding 1000 m2 (0 for lots below 1000 m2, co-ops and apartments)","Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,Placebo: treatment assumed to start in 2004; all years,elasticity,0.0094,0.0011,b (log-log),reported,0.0650658181749187,0.007614085105575593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.545454545454545,17176.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob3,7,Rob-3,19,Twin-house,dwelling_type,A_structural,dummy,binary,-0.0695,0.0058,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,Placebo: treatment assumed to start in 2004; all years,pct_premium,-6.715555719092947,0.5410588773630425,100*(exp(b - se^2/2) - 1),reported,-0.0910516984496127,0.007598559007305806,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.982758620689657,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob3,7,Rob-3,19,Row-house,dwelling_type,A_structural,dummy,binary,-0.1131,0.0064,,,***,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,Placebo: treatment assumed to start in 2004; all years,pct_premium,-10.695694019354251,0.5715592636899893,100*(exp(b - se^2/2) - 1),reported,-0.13363151546728688,0.007561818735549391,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.671875,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob3,7,Rob-3,19,Apartment,dwelling_type,A_structural,dummy,binary,0.0031,0.0073,,,,,,high,Reference category: detached house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,17186.0,0.6901,se,Placebo: treatment assumed to start in 2004; all years,pct_premium,0.30780825974323633,0.7322665112773824,100*(exp(b - se^2/2) - 1),reported,0.0032402277578750553,0.007630213752415452,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4246575342465753,17176.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob4,7,Rob-4,19,Ln(Floor),living_area,A_structural,log,m2,0.5716,0.0119,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,7053.0,0.6632,se,Detached houses only,elasticity,0.5716,0.0119,b (log-log),reported,0.4967457472817007,0.01034162769883177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),48.033613445378144,7043.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob4,7,Rob-4,19,Ln(Age),age,A_structural,log,years,-0.0625,0.0041,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,7053.0,0.6632,se,Detached houses only,elasticity,-0.0625,0.0041,b (log-log),reported,-0.17871805210969513,0.011723904218396003,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.243902439024389,7043.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob4,7,Rob-4,19,Ln(Lot),lot_size,A_structural,log,m2,0.0103,0.0014,,,***,,,high,Lot = lot size exceeding 1000 m2,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,7053.0,0.6632,se,Detached houses only,elasticity,0.0103,0.0014,b (log-log),reported,0.08733088952397261,0.011870217993549674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.357142857142858,7043.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob5,7,Rob-5,19,Ln(Floor),living_area,A_structural,log,m2,0.4651,0.0167,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,2122.0,0.7848,se,Small houses only (row-houses and twin-houses),elasticity,0.4651,0.0167,b (log-log),reported,0.5182727867985625,0.018609235733253047,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.850299401197606,2112.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob5,7,Rob-5,19,Ln(Age),age,A_structural,log,years,-0.0661,0.0045,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,2122.0,0.7848,se,Small houses only (row-houses and twin-houses),elasticity,-0.0661,0.0045,b (log-log),reported,-0.30445248466266134,0.020726719833312795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.688888888888892,2112.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob5,7,Rob-5,19,Ln(Lot),lot_size,A_structural,log,m2,0.0016,0.0023,,,***,,,high,Lot = lot size exceeding 1000 m2; stars as printed despite SE > coefficient,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,2122.0,0.7848,se,Small houses only (row-houses and twin-houses),elasticity,0.0016,0.0023,b (log-log),reported,0.015135453546857072,0.021757214473607036,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6956521739130436,2112.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob5,7,Rob-5,19,Twin-house,dwelling_type,A_structural,dummy,binary,0.0499,0.0082,,,***,,,high,Small-house subsample: reference category row-house,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,2122.0,0.7848,se,Small houses only (row-houses and twin-houses),pct_premium,5.113063491656544,0.8619560991085049,100*(exp(b - se^2/2) - 1),reported,0.13126993936399756,0.021571412881458515,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.085365853658536,2112.0,binary,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob6,7,Rob-6,19,Ln(Floor),living_area,A_structural,log,m2,0.6615,0.0162,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,3455.0,0.7386,se,Apartments only,elasticity,0.6615,0.0162,b (log-log),reported,0.5710893650190773,0.0139858620004672,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.833333333333336,3445.0,m2,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c,877cbdabc2aba0920a744f15d91bf843fa770f5c:T7-Rob6,7,Rob-6,19,Ln(Age),age,A_structural,log,years,-0.0786,0.0035,,,***,,,high,,"Ln(Price + 0.86*mutual debt), NOK",log,OLS,3455.0,0.7386,se,Apartments only,elasticity,-0.0786,0.0035,b (log-log),reported,-0.3573494844396483,0.015912508849093752,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.45714285714286,3445.0,years,,2020.0,Norway,Europe,High income,2003.0,2013.0,mixed,transaction,journal,True,True,robust,,2008.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,STRQUAL,condition,A_structural,binary,binary,0.191025,,1.733654,,,,,high,"Structural quality of property: good=1, poor=0",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,20.316367633931055,13.337943880757662,100*(exp(b - se^2/2) - 1),|b/t|,0.16999422017023924,0.09805544830181757,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.733654,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,REPAIR,condition,A_structural,binary,binary,0.081544,,1.380998,,,,,high,"State of repair: good=1, poor=0",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,8.307120834647508,6.406385534193269,100*(exp(b - se^2/2) - 1),|b/t|,0.13613514640616256,0.09857736680731077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.380998,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,BED,bedrooms,A_structural,level,count,0.072237,,3.410468,,,,,high,Number of bedrooms (3-5),natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",semi_elasticity,7.223699999999999,2.118096402018726,100*b/1 (per unit count),|b/t|,0.3213545445467387,0.0942259374803513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.410468,101.0,count,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,BATH,bathrooms,A_structural,level,count,0.061126,,4.736524,,,,,high,Number of bathrooms (2-5),natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",semi_elasticity,6.1126,1.29052444366375,100*b/1 (per unit count),|b/t|,0.42632537266292564,0.09000806765951691,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.736524,101.0,count,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,STORE,storage,B_interior,binary,binary,0.090283,,3.028461,,,,,high,Store room available=1,natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,9.399773858460158,3.2628221747702977,100*(exp(b - se^2/2) - 1),|b/t|,0.2885274943188608,0.09527198610741919,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.028461,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,True
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,BCNY,terrace_balcony,C_exterior,binary,binary,0.152038,,3.842652,,,,,high,Balcony available=1,natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,16.329357369397645,4.606280246689829,100*(exp(b - se^2/2) - 1),|b/t|,0.3571417231550555,0.09294146936934582,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.842652,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,True
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,PLOT,lot_size,A_structural,level,m2,0.008826,,3.947261,,,,,high,Plot size in square metres (range 593-1407 m2),natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",semi_elasticity,0.8826,0.2235980848492157,100*b/1 (X per m2->m2),|b/t|,0.36557980663970313,0.09261607140741471,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.947261,101.0,m2,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,NTLIGHT,sunlight,E_environment,binary,binary,0.009435,,6.884632,,,,,high,"Natural lighting: good=1, poor=0",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,0.947870196668732,0.13834349456953088,100*(exp(b - se^2/2) - 1),|b/t|,0.5651535713057985,0.08208914743820708,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.884632,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,DISCBD,cbd_distance,D_location,dummy,binary,0.280001,,1.920375,,,,,high,"Distance to closest CBD: 1 if within 15 minutes walking distance, 0 otherwise (positive = proximity premium)",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,30.914126070699275,19.29196334372977,100*(exp(b - se^2/2) - 1),|b/t|,0.1876886124548838,0.09773539670891561,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.920375,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,SECRTY,crime,F_neighbourhood,binary,binary,0.000983,,1.677463,,,,,high,"Neighbourhood security: good=1, poor=0",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,0.09833114336652571,0.058658030852942855,100*(exp(b - se^2/2) - 1),|b/t|,0.16463616219591817,0.09814592762756508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.677463,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,ROAD,public_services,F_neighbourhood,binary,binary,0.120567,,1.814028,,,,,high,"Condition of road surface: good=1, poor=0",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,12.564734591706216,7.4980106218619795,100*(exp(b - se^2/2) - 1),|b/t|,0.1776319976991941,0.09792130975883179,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.814028,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,WATER,public_services,F_neighbourhood,binary,binary,0.097635,,2.376251,,,,,high,"Government water supply: good=1, poor=0",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,10.162999326494004,4.530181056628356,100*(exp(b - se^2/2) - 1),|b/t|,0.23010119228593862,0.0968337066605921,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.376251,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,WASTE,public_services,F_neighbourhood,binary,binary,-0.039012,,-3.429712,,,,,high,"Government waste disposal services: good=1, poor=0",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,-3.832304668976283,1.093950991514608,100*(exp(b - se^2/2) - 1),|b/t|,-0.32297915039804626,0.09417092467182268,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.429712,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,SRTLIGHT,public_services,F_neighbourhood,binary,binary,0.050754,,1.092836,,,,,high,"Street lighting: good=1, poor=0",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,5.093006534903011,4.8860450223989575,100*(exp(b - se^2/2) - 1),|b/t|,0.1081039782921921,0.09892058670485976,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.092836,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,DRAIN,public_services,F_neighbourhood,binary,binary,0.009127,,2.348283,,,,,high,"Nature of drainage: good=1, poor=0",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,0.9161155746629346,0.3922305547265911,100*(exp(b - se^2/2) - 1),|b/t|,0.227533948861164,0.09689375124768353,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.348283,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,GREEN,green_space,E_environment,binary,binary,0.170362,,2.736555,,,,,high,"Green environment in neighbourhood (trees, flowers): good=1, poor=0",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,18.343852857220135,7.381690384472183,100*(exp(b - se^2/2) - 1),|b/t|,0.2627313285765856,0.09600805705589166,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.736555,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,LSCAPE,landscaping,C_exterior,binary,binary,0.093552,,5.012254,,,,,high,"Landscape of neighbourhood: good=1, poor=0",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,9.787645143644541,2.0495056635046964,100*(exp(b - se^2/2) - 1),|b/t|,0.4463098361859125,0.08904373884202844,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.012254,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111,8885ddb1a206684210159fea8394d2ea9c611111:T3-c1,3,1,13,VIEWWAT,view,E_environment,binary,binary,0.0349,,4.773652,,,,,high,"View of navigable water body: good=1, poor=0 (mean 0.0078)",natural log of annual net rental value (Naira),log,OLS,111.0,0.790123,t,"Log-linear model, detached houses, Yaba LCDA; t-statistics printed in a separate column",pct_premium,3.548847810324407,0.757062175982513,100*(exp(b - se^2/2) - 1),|b/t|,0.42905396041648713,0.08987960589009988,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.773652,101.0,binary,,2018.0,Nigeria,Africa,Lower middle income,2016.0,2016.0,single_family,rent,journal,False,False,OLS,,2016.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,logSQFT,living_area,A_structural,log,sqft,0.6321,0.0274,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,elasticity,0.6321,0.0274,b (log-log),reported,0.04541005198496497,0.001968415479177409,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.06934306569343,257555.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,logSQFT,living_area,A_structural,log,sqft,0.6321,0.0275,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,elasticity,0.6321,0.0275,b (log-log),reported,0.04524526317680663,0.0019684302125647563,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.985454545454544,257555.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,logSQFT,living_area,A_structural,log,sqft,0.6309,0.0277,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,elasticity,0.6309,0.0277,b (log-log),reported,0.044834139489778956,0.0019684667361973005,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.776173285198556,257555.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,bedrooms,bedrooms,A_structural,level,count,-0.0188,0.0039,,,***,,,high,,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,-1.8800000000000001,0.38999999999999996,100*b/1 (per unit count),reported,-0.009498142014342476,0.0019703592476561517,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.820512820512821,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,bedrooms,bedrooms,A_structural,level,count,-0.0188,0.0039,,,***,,,high,,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-1.8800000000000001,0.38999999999999996,100*b/1 (per unit count),reported,-0.009498142014342476,0.0019703592476561517,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.820512820512821,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,bedrooms,bedrooms,A_structural,level,count,-0.0187,0.004,,,***,,,high,,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,-1.87,0.4,100*b/1 (per unit count),reported,-0.009211454189182913,0.001970364532445543,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.675,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,fullBaths,bathrooms,A_structural,level,count,0.0848,0.0057,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,8.48,0.5700000000000001,100*b/1 (per unit count),reported,0.029302149358981965,0.0019696020205919483,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.87719298245614,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,fullBaths,bathrooms,A_structural,level,count,0.085,0.0057,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,8.5,0.5700000000000001,100*b/1 (per unit count),reported,0.02937119865394858,0.001969598027382434,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.912280701754387,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,fullBaths,bathrooms,A_structural,level,count,0.0845,0.0058,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,8.450000000000001,0.58,100*b/1 (per unit count),reported,0.02869556910006875,0.00196963669562602,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.56896551724138,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,halfBaths,bathrooms,A_structural,level,count,0.058,0.0066,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,5.800000000000001,0.66,100*b/1 (per unit count),reported,0.017313463845037645,0.0019701527823663524,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.787878787878789,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,halfBaths,bathrooms,A_structural,level,count,0.0584,0.0065,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,5.84,0.65,100*b/1 (per unit count),reported,0.017700944883192113,0.001970139413368985,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.984615384615385,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,halfBaths,bathrooms,A_structural,level,count,0.0589,0.0066,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,5.89,0.66,100*b/1 (per unit count),reported,0.017582038627459304,0.001970143547389328,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.924242424242424,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,distanceCBD,cbd_distance,D_location,level,km,-0.0307,0.013,,,*,,,high,distance to CBD in km,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,-3.0700000000000003,1.3,100*b/1 (X per km->km),reported,-0.004653238670417924,0.0019704267985483064,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3615384615384616,257555.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,distanceCBD,cbd_distance,D_location,level,km,-0.0282,0.013,,,*,,,high,distance to CBD in km,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-2.82,1.3,100*b/1 (X per km->km),reported,-0.004274317669729429,0.001970430131435552,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.169230769230769,257555.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,distanceCBD,cbd_distance,D_location,level,km,-0.0362,0.0137,,,**,,,high,distance to CBD in km,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,-3.62,1.37,100*b/1 (X per km->km),reported,-0.005206515003349711,0.001970421423919642,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6423357664233578,257555.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,house,dwelling_type,A_structural,binary,binary,0.008,0.0448,,,,,,high,single-family house dummy (reference: condominium),log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,pct_premium,0.7021012546645666,4.515983743059145,100*(exp(b - se^2/2) - 1),reported,0.000351865715959997,0.001970448009375983,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.17857142857142858,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,house,dwelling_type,A_structural,binary,binary,-0.027,0.0461,,,,,,high,single-family house dummy (reference: condominium),log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-2.767250766691376,4.487195323427193,100*(exp(b - se^2/2) - 1),reported,-0.0011540577899785318,0.0019704468191855677,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5856832971800433,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,house,dwelling_type,A_structural,binary,binary,-0.0804,0.0571,,,,,,high,single-family house dummy (reference: condominium),log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-7.875586790291045,5.268886361755872,100*(exp(b - se^2/2) - 1),reported,-0.0027744907180684013,0.001970440547284897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4080560420315236,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,rowhouse,dwelling_type,A_structural,binary,binary,0.1527,0.03,,,***,,,high,row house dummy (reference: condominium),log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,pct_premium,16.44513128742595,3.494926301650306,100*(exp(b - se^2/2) - 1),reported,0.010029076576370376,0.001970349032685732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.09,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,rowhouse,dwelling_type,A_structural,binary,binary,0.1516,0.03,,,***,,,high,row house dummy (reference: condominium),log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,16.317112066489912,3.4910839963738254,100*(exp(b - se^2/2) - 1),reported,0.009956837633535632,0.0019703504551851513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.053333333333334,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,rowhouse,dwelling_type,A_structural,binary,binary,0.1522,0.0318,,,***,,,high,row house dummy (reference: condominium),log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,16.38045001434851,3.7027700318100156,100*(exp(b - se^2/2) - 1),reported,0.009430467597063745,0.0019703605097675897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.786163522012578,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,i.distBrew_0to0.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0001,0.0232,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-0.5km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-0.016910570001893444,2.3202320116003867,100*(exp(b - se^2/2) - 1),reported,8.493310910711198e-06,0.0019704481312849977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.004310344827586208,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,i.distBrew_0to0.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0005,0.0273,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-0.5km of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.08722643560823418,2.728635341193132,100*(exp(b - se^2/2) - 1),reported,-3.6088793591078964e-05,0.0019704481300729113,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.018315018315018316,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,i.distBrew_0to0.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0551,0.0237,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-0.5km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-5.387524755091944,2.242945494885167,100*(exp(b - se^2/2) - 1),reported,-0.0045810359829076995,0.0019704274554430577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3248945147679327,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,i.distBrew_0.5to1km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0266,0.015,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 0.5-1km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-2.6358876887674465,1.460625995850344,100*(exp(b - se^2/2) - 1),reported,-0.0034942400209082808,0.0019704361020159477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7733333333333332,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,i.distBrew_0.5to1km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0,0.0143,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0.5-1km of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.010223977315815258,1.43,100*(exp(b - se^2/2) - 1),reported,0.0,0.0019704481313560685,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,i.distBrew_0.5to1km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.001,0.0309,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0.5-1km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-0.14763141744961183,3.0869115444851287,100*(exp(b - se^2/2) - 1),reported,-6.376854781067073e-05,0.001970448127349726,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.032362459546925564,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,i.distBrew_1to1.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0044,0.0157,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1-1.5km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-0.4513030533982554,1.563107175334684,100*(exp(b - se^2/2) - 1),reported,-0.0005522274175790099,0.0019704478309069216,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.28025477707006374,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,i.distBrew_1to1.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0011,0.0165,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1-1.5km of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.12353613121958151,1.6481859978840756,100*(exp(b - se^2/2) - 1),reported,-0.00013136320762365024,0.0019704481143547536,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.06666666666666667,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,i.distBrew_1to1.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0218,0.0144,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1-1.5km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-2.166553631137147,1.4089476998366344,100*(exp(b - se^2/2) - 1),reported,-0.002983026259954699,0.001970439364373746,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5138888888888888,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,i.distBrew_1.5to2km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.002,0.0217,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1.5-2km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-0.22329482536189715,2.165664337108113,100*(exp(b - se^2/2) - 1),reported,-0.00018160811971077343,0.0019704480988618914,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.09216589861751152,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,i.distBrew_1.5to2km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0015,0.0199,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1.5-2km of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.16965642051176566,1.9870172376310447,100*(exp(b - se^2/2) - 1),reported,-0.00014852623941874235,0.001970448109621982,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.07537688442211055,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,i.distBrew_1.5to2km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0004,0.0161,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1.5-2km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,0.027043156002304336,1.6106441288171751,100*(exp(b - se^2/2) - 1),reported,4.895523301850598e-05,0.0019704481289948656,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.02484472049689441,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,i.distBrew_2to2.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0145,0.0312,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2-2.5km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,pct_premium,1.411192625544988,3.1655695810483633,100*(exp(b - se^2/2) - 1),reported,0.000915752753993174,0.001970447305143933,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4647435897435898,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,i.distBrew_2to2.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0127,0.0166,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2-2.5km of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,1.2641456131941675,1.6812164392232107,100*(exp(b - se^2/2) - 1),reported,0.0015075098092064208,0.0019704458923485504,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7650602409638554,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,i.distBrew_2to2.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0032,0.0189,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2-2.5km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-0.3372903936481486,1.8839616664863321,100*(exp(b - se^2/2) - 1),reported,-0.00033362082907052894,0.001970448021697811,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.16931216931216933,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,i.distBrew_2.5to3km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.061,0.0327,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 2.5-3km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-5.9679632224041494,3.0764919940675517,100*(exp(b - se^2/2) - 1),reported,-0.003675734679368364,0.0019704348199236967,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8654434250764527,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,i.distBrew_2.5to3km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0593,0.0255,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 2.5-3km of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-5.78823562542733,2.4031811988369842,100*(exp(b - se^2/2) - 1),reported,-0.004582209705075012,0.0019704274448467587,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3254901960784315,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,i.distBrew_2.5to3km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0033,0.0236,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2.5-3km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,0.30260893925664334,2.367800864346889,100*(exp(b - se^2/2) - 1),reported,0.0002755287536717637,0.001970448056561704,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.1398305084745763,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,i.distBrew_3to3.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0217,0.0325,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3-3.5km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,pct_premium,2.139758926248647,3.3212957613272702,100*(exp(b - se^2/2) - 1),reported,0.0013156519213543964,0.0019704464259916077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6676923076923077,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,i.distBrew_3to3.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0486,0.0296,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3-3.5km of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,4.934055079134647,3.107409025954231,100*(exp(b - se^2/2) - 1),reported,0.0032352458787726474,0.0019704378191701725,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6418918918918917,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,i.distBrew_3to3.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.017,0.0248,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3-3.5km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,1.6832577885768973,2.5225203993665968,100*(exp(b - se^2/2) - 1),reported,0.0013507091804941846,0.0019704463338973987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.685483870967742,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c1,2,All craft breweries,11,i.distBrew_3.5to4km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0296,0.0503,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3.5-4km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: All craft breweries,pct_premium,2.8740208394693045,5.181113445863497,100*(exp(b - se^2/2) - 1),reported,0.0011595472261931579,0.001970446806672832,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5884691848906561,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c2,2,Brewpubs/taprooms only,11,i.distBrew_3.5to4km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0443,0.0323,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3.5-4km of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,4.475076544066425,3.376305746094936,100*(exp(b - se^2/2) - 1),reported,0.0027024932958337757,0.001970440935788509,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.371517027863777,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T2-c3,2,Regional/microbreweries only,11,i.distBrew_3.5to4km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0111,0.0296,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3.5-4km of the home,log sale price (USD),log,OLS,257565.0,0.741,se,all home transactions; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,1.0718960810317313,2.993039027374411,100*(exp(b - se^2/2) - 1),reported,0.0007389178475340238,0.0019704475934240635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.375,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,logSQFT,living_area,A_structural,log,sqft,0.5024,0.0224,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,elasticity,0.5024,0.0224,b (log-log),reported,0.05266315391185602,0.00234803870944581,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.428571428571427,180877.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,logSQFT,living_area,A_structural,log,sqft,0.5031,0.0225,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,elasticity,0.5031,0.0225,b (log-log),reported,0.05250259004496712,0.0023480585887731276,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.36,180877.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,logSQFT,living_area,A_structural,log,sqft,0.5014,0.0225,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,elasticity,0.5014,0.0225,b (log-log),reported,0.052325667736150834,0.0023480804229425484,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.284444444444443,180877.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,bedrooms,bedrooms,A_structural,level,count,-0.0195,0.0032,,,***,,,high,,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,-1.95,0.32,100*b/1 (per unit count),reported,-0.014326773154812456,0.002351060210020505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.09375,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,bedrooms,bedrooms,A_structural,level,count,-0.0198,0.0033,,,***,,,high,,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-1.9800000000000002,0.33,100*b/1 (per unit count),reported,-0.014106405462621058,0.0023510675771035096,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.000000000000001,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,bedrooms,bedrooms,A_structural,level,count,-0.0195,0.0032,,,***,,,high,,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,-1.95,0.32,100*b/1 (per unit count),reported,-0.014326773154812456,0.002351060210020505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.09375,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,fullBaths,bathrooms,A_structural,level,count,0.0763,0.0051,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,7.630000000000001,0.51,100*b/1 (per unit count),reported,0.03515557029001013,0.002349848079673023,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.96078431372549,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,fullBaths,bathrooms,A_structural,level,count,0.0767,0.0051,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,7.670000000000001,0.51,100*b/1 (per unit count),reported,0.03533964252687534,0.002349832814694449,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.03921568627451,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,fullBaths,bathrooms,A_structural,level,count,0.0759,0.0051,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,7.59,0.51,100*b/1 (per unit count),reported,0.03497149447516826,0.002349863265129883,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.88235294117647,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,halfBaths,bathrooms,A_structural,level,count,0.0621,0.0073,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,6.21,0.73,100*b/1 (per unit count),reported,0.0199981677288279,0.0023508313111182556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.506849315068493,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,halfBaths,bathrooms,A_structural,level,count,0.0622,0.0073,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,6.22,0.73,100*b/1 (per unit count),reported,0.020030357987453295,0.00235082979595513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.520547945205479,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,halfBaths,bathrooms,A_structural,level,count,0.0625,0.0072,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,6.25,0.72,100*b/1 (per unit count),reported,0.02040635345210413,0.002350811917682396,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.680555555555555,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,distanceCBD,cbd_distance,D_location,level,km,-0.0235,0.0129,,,+,,,high,distance to CBD in km,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,-2.35,1.29,100*b/1 (X per km->km),reported,-0.0042833394666106145,0.0023512799625224224,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.821705426356589,180877.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,distanceCBD,cbd_distance,D_location,level,km,-0.0212,0.0131,,,,,,high,distance to CBD in km,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-2.12,1.31,100*b/1 (X per km->km),reported,-0.0038051321840201656,0.0023512845099369893,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.618320610687023,180877.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,distanceCBD,cbd_distance,D_location,level,km,-0.0177,0.0115,,,,,,high,distance to CBD in km,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,-1.77,1.15,100*b/1 (X per km->km),reported,-0.0036189360513975456,0.002351286135088801,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5391304347826087,180877.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,i.distBrew_0to0.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0334,0.0144,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-0.5km of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-3.29486475241223,1.392698335043465,100*(exp(b - se^2/2) - 1),reported,-0.005453632173209724,0.0023512665656952106,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3194444444444446,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,i.distBrew_0to0.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.035,0.0163,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-0.5km of the home,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-3.4522851073930827,1.5739368284998332,100*(exp(b - se^2/2) - 1),reported,-0.0050487426242032925,0.002351271564986104,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1472392638036815,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,i.distBrew_0to0.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0259,0.0154,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-0.5km of the home,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-2.5683013369038443,1.500626093103904,100*(exp(b - se^2/2) - 1),reported,-0.003954430748816904,0.0023512831479451865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6818181818181817,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,i.distBrew_0.5to1km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0264,0.0146,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 0.5-1km of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-2.6158364063511352,1.4219603329236088,100*(exp(b - se^2/2) - 1),reported,-0.004251630096611272,0.0023512802807016888,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8082191780821917,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,i.distBrew_0.5to1km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0117,0.0162,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0.5-1km of the home,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-1.1761506320135284,1.6011564497264097,100*(exp(b - se^2/2) - 1),reported,-0.0016981597692229992,0.0023512981420010753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7222222222222223,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,i.distBrew_0.5to1km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0476,0.0165,,,**,,,high,time-invariant dummy: at least one craft brewery (ever) within 0.5-1km of the home,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-4.661467155815102,1.5732999428077907,100*(exp(b - se^2/2) - 1),reported,-0.006782992618126354,0.0023512474411572447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.8848484848484848,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,i.distBrew_1to1.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0178,0.0168,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1-1.5km of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-1.778113629757594,1.6503605734716282,100*(exp(b - se^2/2) - 1),reported,-0.002491252226010809,0.0023512942357854826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0595238095238095,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,i.distBrew_1to1.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0086,0.0179,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1-1.5km of the home,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.8721946203986253,1.7746720048505693,100*(exp(b - se^2/2) - 1),reported,-0.0011296748756889343,0.002351300031957201,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.48044692737430167,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,i.distBrew_1to1.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0376,0.0135,,,**,,,high,time-invariant dummy: at least one craft brewery (ever) within 1-1.5km of the home,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-3.698965522123432,1.3001824391780628,100*(exp(b - se^2/2) - 1),reported,-0.0065486697690000885,0.0023512511138697122,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.785185185185185,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,i.distBrew_1.5to2km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0031,0.0208,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1.5-2km of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-0.33108270845949583,2.0735619840804524,100*(exp(b - se^2/2) - 1),reported,-0.00035043434146698804,0.0023513013879075326,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.14903846153846154,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,i.distBrew_1.5to2km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0032,0.0188,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1.5-2km of the home,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.3371025292634777,1.8739936153409018,100*(exp(b - se^2/2) - 1),reported,-0.00040022150535657926,0.002351301343969903,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.1702127659574468,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,i.distBrew_1.5to2km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0058,0.0167,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1.5-2km of the home,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,0.5676606213421032,1.6797141437850087,100*(exp(b - se^2/2) - 1),reported,0.0008166194215580671,0.002351300748279262,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.34730538922155685,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,i.distBrew_2to2.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0149,0.0274,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2-2.5km of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-1.5159303173733152,2.6994766486803266,100*(exp(b - se^2/2) - 1),reported,-0.0012786264303790182,0.002351299610227188,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5437956204379562,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,i.distBrew_2to2.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0071,0.0175,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2-2.5km of the home,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.7226884568903413,1.7376190045443225,100*(exp(b - se^2/2) - 1),reported,-0.0009539561876030485,0.0023513004624018804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4057142857142857,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,i.distBrew_2to2.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0129,0.0192,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2-2.5km of the home,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-1.299909240505981,1.8953910688691993,100*(exp(b - se^2/2) - 1),reported,-0.001579778745670955,0.0023512985982079328,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6718750000000001,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,i.distBrew_2.5to3km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0426,0.0274,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2.5-3km of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-4.206502586422722,2.6257272896693538,100*(exp(b - se^2/2) - 1),reported,-0.0036556487583619237,0.002351285821106026,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5547445255474452,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,i.distBrew_2.5to3km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0357,0.0225,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2.5-3km of the home,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-3.531448794331793,2.171091890214725,100*(exp(b - se^2/2) - 1),reported,-0.003730705801992846,0.0023512851693232215,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.586666666666667,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,i.distBrew_2.5to3km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0165,0.0277,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2.5-3km of the home,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,1.6246923937974111,2.816084148697374,100*(exp(b - se^2/2) - 1),reported,0.0014005934017999287,0.0023512992260520016,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5956678700361011,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,i.distBrew_3to3.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.037,0.0267,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3-3.5km of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-3.6667300979293826,2.5730152813819727,100*(exp(b - se^2/2) - 1),reported,-0.003258340631944531,0.002351289050619432,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3857677902621721,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,i.distBrew_3to3.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0148,0.0252,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3-3.5km of the home,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-1.5003823949679918,2.4829786338702298,100*(exp(b - se^2/2) - 1),reported,-0.0013809218054612485,0.0023512992903799634,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5873015873015873,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,i.distBrew_3to3.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0254,0.0271,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3-3.5km of the home,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,2.53487462851818,2.77971564052981,100*(exp(b - se^2/2) - 1),reported,0.0022037975605387426,0.002351295822464564,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9372693726937269,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c1,3,All craft breweries,12,i.distBrew_3.5to4km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0542,0.0229,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 3.5-4km of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-5.30057001689771,2.169185643373838,100*(exp(b - se^2/2) - 1),reported,-0.005565003042132975,0.002351265122967622,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3668122270742358,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c2,3,Brewpubs/taprooms only,12,i.distBrew_3.5to4km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0271,0.0097,,,**,,,high,time-invariant dummy: at least one craft brewery (ever) within 3.5-4km of the home,log sale price (USD),log,OLS,180887.0,0.757,se,single-family homes; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-2.678187585681757,0.9440659929588235,100*(exp(b - se^2/2) - 1),reported,-0.006568958423346533,0.0023512508009764345,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.7938144329896906,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T3-c3,3,Regional/microbreweries only,12,i.distBrew_3.5to4km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.032,0.0323,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3.5-4km of the home,log sale price (USD),log,OLS,180887.0,0.759,se,single-family homes; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,3.1979038167618823,3.3350315421355323,100*(exp(b - se^2/2) - 1),reported,0.0023294564980909653,0.0023512951527605683,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9907120743034056,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,logSQFT,living_area,A_structural,log,sqft,0.7124,0.0549,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,elasticity,0.7124,0.0549,b (log-log),reported,0.08449661077172943,0.006511600128253713,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.97632058287796,23416.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,logSQFT,living_area,A_structural,log,sqft,0.7148,0.0539,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,elasticity,0.7148,0.0539,b (log-log),reported,0.086340507329021,0.006510567074754102,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.261595547309833,23416.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,logSQFT,living_area,A_structural,log,sqft,0.7157,0.0545,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,elasticity,0.7157,0.0545,b (log-log),reported,0.08550367699088629,0.006511038697783015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.132110091743119,23416.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,bedrooms,bedrooms,A_structural,level,count,-0.0403,0.0101,,,***,,,high,,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,-4.03,1.01,100*b/1 (per unit count),reported,-0.02606632021761351,0.006532750228235643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.9900990099009905,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,bedrooms,bedrooms,A_structural,level,count,-0.0397,0.0102,,,***,,,high,,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-3.9699999999999998,1.02,100*b/1 (per unit count),reported,-0.025426907503547515,0.00653285784725906,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.8921568627450975,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,bedrooms,bedrooms,A_structural,level,count,-0.0405,0.0103,,,***,,,high,,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,-4.05,1.03,100*b/1 (per unit count),reported,-0.02568727971401918,0.0065328143470221615,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.9320388349514563,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,fullBaths,bathrooms,A_structural,level,count,0.1023,0.0096,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,10.23,0.96,100*b/1 (per unit count),reported,0.06947003820102224,0.00651918247047716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.656250000000002,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,fullBaths,bathrooms,A_structural,level,count,0.1021,0.0097,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,10.209999999999999,0.97,100*b/1 (per unit count),reported,0.06862346645372842,0.006519565373174982,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.525773195876289,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,fullBaths,bathrooms,A_structural,level,count,0.1009,0.0102,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,10.09,1.02,100*b/1 (per unit count),reported,0.06451030255381003,0.006521358632793482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.892156862745098,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,halfBaths,bathrooms,A_structural,level,count,0.065,0.0167,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,6.5,1.67,100*b/1 (per unit count),reported,0.025427290774304754,0.006532857783552144,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8922155688622757,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,halfBaths,bathrooms,A_structural,level,count,0.0655,0.0165,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,6.550000000000001,1.6500000000000001,100*b/1 (per unit count),reported,0.02593312865038028,0.0065327728661263304,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9696969696969697,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,halfBaths,bathrooms,A_structural,level,count,0.0661,0.0162,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,6.61,1.6199999999999999,100*b/1 (per unit count),reported,0.026654820163767988,0.006532648814720747,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.080246913580248,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,distanceCBD,cbd_distance,D_location,level,km,-0.0102,0.0151,,,,,,high,distance to CBD in km,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,-1.02,1.51,100*b/1 (X per km->km),reported,-0.004414308065038278,0.006534907037458628,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6754966887417219,23416.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,distanceCBD,cbd_distance,D_location,level,km,-0.0176,0.0157,,,,,,high,distance to CBD in km,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-1.76,1.5699999999999998,100*b/1 (X per km->km),reported,-0.007325630463745907,0.006534795356864245,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.121019108280255,23416.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,distanceCBD,cbd_distance,D_location,level,km,-0.0206,0.0134,,,,,,high,distance to CBD in km,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,-2.06,1.34,100*b/1 (X per km->km),reported,-0.010045791314592772,0.006534640952210831,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.537313432835821,23416.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,i.distBrew_0to0.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0139,0.0188,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-0.5km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-1.3978106238743626,1.8540487788221278,100*(exp(b - se^2/2) - 1),reported,-0.0048316506682290995,0.0065348944289717326,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7393617021276595,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,i.distBrew_0to0.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0094,0.0197,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-0.5km of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.9548168979691907,1.9515687625312483,100*(exp(b - se^2/2) - 1),reported,-0.003118194214112814,0.006534938938087492,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4771573604060914,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,i.distBrew_0to0.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0623,0.0301,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-0.5km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-6.082458332438312,2.8281989022888125,100*(exp(b - se^2/2) - 1),reported,-0.013524632502267203,0.006534373006713368,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0697674418604652,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,i.distBrew_0.5to1km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0346,0.0166,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 0.5-1km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-3.4141349490090622,1.603546281233454,100*(exp(b - se^2/2) - 1),reported,-0.013619820113982955,0.006534364563355984,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.08433734939759,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,i.distBrew_0.5to1km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0478,0.0213,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 0.5-1km of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-4.689179945557253,2.0305810420745867,100*(exp(b - se^2/2) - 1),reported,-0.014663756529799465,0.006534268077086373,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.244131455399061,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,i.distBrew_0.5to1km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0124,0.0175,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0.5-1km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-1.2474663183191015,1.728433985620973,100*(exp(b - se^2/2) - 1),reported,-0.0046304438890031,0.0065349006498027625,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7085714285714285,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,i.distBrew_1to1.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0366,0.0189,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 1-1.5km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-3.611048795356553,1.822076580695296,100*(exp(b - se^2/2) - 1),reported,-0.012654009414903024,0.006534447484745004,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9365079365079365,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,i.distBrew_1to1.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0355,0.0191,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 1-1.5km of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-3.505329292773185,1.843384422379301,100*(exp(b - se^2/2) - 1),reported,-0.01214525389065746,0.0065344887130016184,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8586387434554974,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,i.distBrew_1to1.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0444,0.0168,,,**,,,high,time-invariant dummy: at least one craft brewery (ever) within 1-1.5km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-4.356372937443565,1.6070397040927615,100*(exp(b - se^2/2) - 1),reported,-0.017268418732565665,0.006533996277187008,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6428571428571432,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,i.distBrew_1.5to2km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0044,0.0317,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1.5-2km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-0.48904476300001276,3.1560826406439157,100*(exp(b - se^2/2) - 1),reported,-0.000907061807193258,0.006534968020005971,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.13880126182965302,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,i.distBrew_1.5to2km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0021,0.0328,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1.5-2km of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.2634443746401538,3.273119227339977,100*(exp(b - se^2/2) - 1),reported,-0.0004183974782433311,0.00653497013637203,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.06402439024390243,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,i.distBrew_1.5to2km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0073,0.0131,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1.5-2km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-0.7358596967865116,1.3004718201694028,100*(exp(b - se^2/2) - 1),reported,-0.0036416007522152034,0.0065349273772629,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5572519083969465,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,i.distBrew_2to2.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0205,0.0366,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2-2.5km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,pct_premium,2.002814494619254,3.7358043397700884,100*(exp(b - se^2/2) - 1),reported,0.0036602732814482665,0.006534926931756417,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5601092896174864,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,i.distBrew_2to2.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0095,0.0218,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2-2.5km of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.9690362893340798,2.159388061725523,100*(exp(b - se^2/2) - 1),reported,-0.0028477967884046273,0.006534944209181145,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.43577981651376146,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,i.distBrew_2to2.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0346,0.0241,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2-2.5km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,3.490495853653819,2.4948453604486693,100*(exp(b - se^2/2) - 1),reported,0.009381744212244688,0.006534683107372746,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4356846473029046,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,i.distBrew_2.5to3km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0652,0.0557,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2.5-3km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,pct_premium,6.57180048927386,5.945264699862558,100*(exp(b - se^2/2) - 1),reported,0.007649328986610108,0.006534779517702195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1705565529622979,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,i.distBrew_2.5to3km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0088,0.0453,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2.5-3km of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,0.7804250642941435,4.57003991724528,100*(exp(b - se^2/2) - 1),reported,0.0012694855605750923,0.006534965442505872,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.19426048565121415,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,i.distBrew_2.5to3km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0209,0.0256,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2.5-3km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,2.078538877312708,2.6140670324180606,100*(exp(b - se^2/2) - 1),reported,0.0053351150003613295,0.006534877703791869,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8164062499999999,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,i.distBrew_3to3.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0952,0.0416,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 3-3.5km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,pct_premium,9.89275173821258,4.575495844989769,100*(exp(b - se^2/2) - 1),reported,0.014953357033753072,0.0065342400483626864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2884615384615388,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,i.distBrew_3to3.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.1438,0.0434,,,**,,,high,time-invariant dummy: at least one craft brewery (ever) within 3-3.5km of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,15.356623745007148,5.011194691829184,100*(exp(b - se^2/2) - 1),reported,0.02164766298598375,0.006533439315658517,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.313364055299539,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,i.distBrew_3to3.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0388,0.0334,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3-3.5km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,3.898286483164104,3.472138918160487,100*(exp(b - se^2/2) - 1),reported,0.007591304113916343,0.006534782407340356,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1616766467065869,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c1,4,All craft breweries,13,i.distBrew_3.5to4km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.1198,0.0385,,,**,,,high,time-invariant dummy: at least one craft brewery (ever) within 3.5-4km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-11.355936827521496,3.415326678394755,100*(exp(b - se^2/2) - 1),reported,-0.02033058901734227,0.0065336200097468895,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.1116883116883116,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c2,4,Brewpubs/taprooms only,13,i.distBrew_3.5to4km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0952,0.0419,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 3.5-4km of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-9.160666422438835,3.809510617103177,100*(exp(b - se^2/2) - 1),reported,-0.01484631610843371,0.006534250472094248,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.272076372315036,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T4-c3,4,Regional/microbreweries only,13,i.distBrew_3.5to4km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.035,0.0561,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3.5-4km of the home,log sale price (USD),log,OLS,23426.0,0.783,se,row houses; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,3.399133399314591,5.809826566365887,100*(exp(b - se^2/2) - 1),reported,0.004077042314235873,0.006534916395103784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6238859180035652,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,logSQFT,living_area,A_structural,log,sqft,0.8709,0.0432,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,elasticity,0.8709,0.0432,b (log-log),reported,0.08703743790837049,0.004317392717466536,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.15972222222222,53242.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,logSQFT,living_area,A_structural,log,sqft,0.8711,0.0432,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,elasticity,0.8711,0.0432,b (log-log),reported,0.08705727436698012,0.004317385205663576,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.16435185185185,53242.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,logSQFT,living_area,A_structural,log,sqft,0.8677,0.0435,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,elasticity,0.8677,0.0435,b (log-log),reported,0.086126422884849,0.004317735848208978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.947126436781613,53242.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,bedrooms,bedrooms,A_structural,level,count,-0.0145,0.0125,,,,,,high,,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,-1.4500000000000002,1.25,100*b/1 (per unit count),reported,-0.005027190246079786,0.004333784694896367,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.16,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,bedrooms,bedrooms,A_structural,level,count,-0.0128,0.0125,,,,,,high,,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-1.28,1.25,100*b/1 (per unit count),reported,-0.004437807905996752,0.004333796783199952,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.024,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,bedrooms,bedrooms,A_structural,level,count,-0.0147,0.013,,,,,,high,,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,-1.47,1.3,100*b/1 (per unit count),reported,-0.004900513467308614,0.004333787420068843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1307692307692307,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,fullBaths,bathrooms,A_structural,level,count,0.0959,0.0165,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,9.59,1.6500000000000001,100*b/1 (per unit count),reported,0.025180813209926406,0.004332465255096827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.812121212121212,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,fullBaths,bathrooms,A_structural,level,count,0.0944,0.0166,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,9.44,1.66,100*b/1 (per unit count),reported,0.02463796709818325,0.004332523875316123,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.686746987951807,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,fullBaths,bathrooms,A_structural,level,count,0.0929,0.0171,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,9.29,1.71,100*b/1 (per unit count),reported,0.023538136693967444,0.004332638724077968,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.432748538011696,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,halfBaths,bathrooms,A_structural,level,count,0.0793,0.0128,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,7.93,1.28,100*b/1 (per unit count),reported,0.026839817170075084,0.004332278181298375,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.195312499999999,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,halfBaths,bathrooms,A_structural,level,count,0.0794,0.0124,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,7.9399999999999995,1.24,100*b/1 (per unit count),reported,0.027739873577013,0.004332171692127976,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.403225806451613,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,halfBaths,bathrooms,A_structural,level,count,0.083,0.0128,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,8.3,1.28,100*b/1 (per unit count),reported,0.028091150136308612,0.004332129177647593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.484375,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,distanceCBD,cbd_distance,D_location,level,km,0.0064,0.0385,,,,,,high,distance to CBD in km,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,semi_elasticity,0.64,3.85,100*b/1 (X per km->km),reported,0.0007204302685679571,0.004333838334354118,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.16623376623376623,53242.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,distanceCBD,cbd_distance,D_location,level,km,0.0033,0.0391,,,,,,high,distance to CBD in km,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,semi_elasticity,0.33,3.91,100*b/1 (X per km->km),reported,0.00036577159227856216,0.0043338391691187216,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.08439897698209718,53242.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,distanceCBD,cbd_distance,D_location,level,km,0.0015,0.0385,,,,,,high,distance to CBD in km,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,semi_elasticity,0.15,3.85,100*b/1 (X per km->km),reported,0.00016885088560707345,0.004333839397248218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.03896103896103896,53242.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,i.distBrew_0to0.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0569,0.0922,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-0.5km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,pct_premium,5.406021661446192,9.759830539991734,100*(exp(b - se^2/2) - 1),reported,0.0026745616402813516,0.004333823958417234,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6171366594360086,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,i.distBrew_0to0.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.078,0.0939,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-0.5km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,7.636690672999813,10.15174176491208,100*(exp(b - se^2/2) - 1),reported,0.0035999711111444257,0.004333811376108482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8306709265175719,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,i.distBrew_0to0.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.137,0.042,,,**,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-0.5km of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-12.879851254374797,3.6622749497548592,100*(exp(b - se^2/2) - 1),reported,-0.014135159235412932,0.004333406480929512,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.261904761904762,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,i.distBrew_0.5to1km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0556,0.0531,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0.5-1km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,pct_premium,5.568536914082012,5.613597812368749,100*(exp(b - se^2/2) - 1),reported,0.004537834142697907,0.0043337948377204834,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.047080979284369,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,i.distBrew_0.5to1km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0527,0.0693,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0.5-1km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,5.158521579245856,7.305005610235939,100*(exp(b - se^2/2) - 1),reported,0.003295701286053672,0.0043338159226474285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7604617604617604,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,i.distBrew_0.5to1km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.1377,0.0981,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0.5-1km of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,14.212229620883177,11.25826216286837,100*(exp(b - se^2/2) - 1),reported,0.006083166683991905,0.004333759271602077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.403669724770642,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,i.distBrew_1to1.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0904,0.0882,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1-1.5km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-8.998083567937588,8.057649349654467,100*(exp(b - se^2/2) - 1),reported,-0.004441895942066979,0.0043337967045388,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0249433106575963,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,i.distBrew_1to1.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0453,0.0973,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1-1.5km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-4.880257907489016,9.299065360128234,100*(exp(b - se^2/2) - 1),reported,-0.002017703266863805,0.004333830637215192,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4655704008221994,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,i.distBrew_1to1.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0962,0.0709,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1-1.5km of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-9.39976734441359,6.439721800763951,100*(exp(b - se^2/2) - 1),reported,-0.005880227757951149,0.004333764532627198,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3568406205923835,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,i.distBrew_1.5to2km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0737,0.0501,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1.5-2km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-7.221476891413414,4.654041189090663,100*(exp(b - se^2/2) - 1),reported,-0.006375199147115523,0.0043337513876592635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.471057884231537,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,i.distBrew_1.5to2km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0665,0.0597,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1.5-2km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,-6.600299276162824,5.585907607662295,100*(exp(b - se^2/2) - 1),reported,-0.0048274198642909,0.004333788960874688,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1139028475711892,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,i.distBrew_1.5to2km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0532,0.0541,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 1.5-2km of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-5.3196216255542055,5.129709822963604,100*(exp(b - se^2/2) - 1),reported,-0.004261703613299918,0.004333800102998602,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9833641404805914,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,i.distBrew_2to2.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.1464,0.1003,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2-2.5km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,pct_premium,15.18507020959543,11.611321365913984,100*(exp(b - se^2/2) - 1),reported,0.006325637117163261,0.004333752751717726,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4596211365902294,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,i.distBrew_2to2.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0514,0.055,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2-2.5km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,5.115283503000723,5.79009148650666,100*(exp(b - se^2/2) - 1),reported,0.004050136748328949,0.004333803913581561,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9345454545454546,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,i.distBrew_2to2.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.2326,0.1111,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 2-2.5km of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,25.411280587127116,14.019449333886817,100*(exp(b - se^2/2) - 1),reported,0.009072993396337981,0.004333661076238821,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0936093609360937,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,True
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,i.distBrew_2.5to3km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0175,0.0579,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2.5-3km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,pct_premium,-1.8993511235685046,5.689556444500774,100*(exp(b - se^2/2) - 1),reported,-0.0013098812688838364,0.00433383574104995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.30224525043177897,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,i.distBrew_2.5to3km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0642,0.0751,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 2.5-3km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,6.330288720909505,8.007955345619598,100*(exp(b - se^2/2) - 1),reported,0.0037048013823650933,0.004333809716754182,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8548601864181091,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,i.distBrew_2.5to3km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.09,0.0521,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 2.5-3km of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,9.269027217822279,5.700648018104146,100*(exp(b - se^2/2) - 1),reported,0.007486269122054237,0.004333718013989175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.727447216890595,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,i.distBrew_3to3.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0582,0.0508,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3-3.5km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,pct_premium,5.85601969206746,5.384428956318124,100*(exp(b - se^2/2) - 1),reported,0.004965085580838132,0.004333786039631909,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1456692913385829,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,i.distBrew_3to3.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0321,0.0439,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3-3.5km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,3.1626202946931414,4.533205146138813,100*(exp(b - se^2/2) - 1),reported,0.003168919091731931,0.004333817698661427,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7312072892938496,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,i.distBrew_3to3.5km,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.1687,0.1034,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3-3.5km of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,-15.974157025300617,8.73484212061919,100*(exp(b - se^2/2) - 1),reported,-0.007070603877564066,0.004333731125904709,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6315280464216633,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c1,5,All craft breweries,14,i.distBrew_3.5to4km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0732,0.0523,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3.5-4km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: All craft breweries,pct_premium,7.447519856932572,5.627196034734427,100*(exp(b - se^2/2) - 1),reported,0.006065606357954182,0.004333759733893494,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3996175908221797,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c2,5,Brewpubs/taprooms only,14,i.distBrew_3.5to4km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0709,0.0522,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3.5-4km of the home,log sale price (USD),log,OLS,53252.0,0.784,se,condominiums; Euclidean distance bins; brewery type: Brewpubs/taprooms only,pct_premium,7.201234667179013,5.6035336176524595,100*(exp(b - se^2/2) - 1),reported,0.005886281502288595,0.004333764378271717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3582375478927202,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T5-c3,5,Regional/microbreweries only,14,i.distBrew_3.5to4km,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.1359,0.1111,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 3.5-4km of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; Euclidean distance bins; brewery type: Regional/microbreweries only,pct_premium,13.851911384303882,12.727253048895639,100*(exp(b - se^2/2) - 1),reported,0.005301174677678395,0.004333778562840837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2232223222322232,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,logSQFT,living_area,A_structural,log,sqft,0.6314,0.0278,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,elasticity,0.6314,0.0278,b (log-log),reported,0.04470852163326648,0.0019684778292759077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.712230215827336,257555.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,logSQFT,living_area,A_structural,log,sqft,0.6319,0.028,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,elasticity,0.6319,0.028,b (log-log),reported,0.0444248891097972,0.001968502761630514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.567857142857143,257555.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,logSQFT,living_area,A_structural,log,sqft,0.6296,0.0277,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,elasticity,0.6296,0.0277,b (log-log),reported,0.04474194170084676,0.001968474881056949,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.72924187725632,257555.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,bedrooms,bedrooms,A_structural,level,count,-0.019,0.0039,,,***,,,high,,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,semi_elasticity,-1.9,0.38999999999999996,100*b/1 (per unit count),reported,-0.009599176816699669,0.001970357346585721,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.871794871794872,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,bedrooms,bedrooms,A_structural,level,count,-0.0186,0.0039,,,***,,,high,,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-1.8599999999999999,0.38999999999999996,100*b/1 (per unit count),reported,-0.009397106921086211,0.001970361128614851,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.769230769230769,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,bedrooms,bedrooms,A_structural,level,count,-0.0185,0.004,,,***,,,high,,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,-1.8499999999999999,0.4,100*b/1 (per unit count),reported,-0.009112944188301553,0.0019703663109841194,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.625,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,fullBaths,bathrooms,A_structural,level,count,0.085,0.0058,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,semi_elasticity,8.5,0.58,100*b/1 (per unit count),reported,0.028865224308240765,0.001969627070444664,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.655172413793105,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,fullBaths,bathrooms,A_structural,level,count,0.0851,0.0058,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,8.51,0.58,100*b/1 (per unit count),reported,0.028899155051000908,0.001969625138611108,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.672413793103448,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,fullBaths,bathrooms,A_structural,level,count,0.0851,0.0058,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,8.51,0.58,100*b/1 (per unit count),reported,0.028899155051000908,0.001969625138611108,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.672413793103448,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,halfBaths,bathrooms,A_structural,level,count,0.0584,0.0065,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,semi_elasticity,5.84,0.65,100*b/1 (per unit count),reported,0.017700944883192113,0.001970139413368985,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.984615384615385,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,halfBaths,bathrooms,A_structural,level,count,0.0586,0.0065,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,5.86,0.65,100*b/1 (per unit count),reported,0.01776154546623387,0.0019701372957426646,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.015384615384615,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,halfBaths,bathrooms,A_structural,level,count,0.0588,0.0066,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,5.88,0.66,100*b/1 (per unit count),reported,0.01755219717184811,0.0019701445805135635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.909090909090908,257555.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,distanceCBD,cbd_distance,D_location,level,km,-0.0335,0.0129,,,*,,,high,distance to CBD in km,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,semi_elasticity,-3.35,1.29,100*b/1 (X per km->km),reported,-0.005116988233017683,0.0019704223345053166,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5968992248062017,257555.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,distanceCBD,cbd_distance,D_location,level,km,-0.0345,0.0127,,,**,,,high,distance to CBD in km,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-3.45,1.27,100*b/1 (X per km->km),reported,-0.005352715484376594,0.001970419902944427,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.7165354330708666,257555.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,distanceCBD,cbd_distance,D_location,level,km,-0.0425,0.0129,,,**,,,high,distance to CBD in km,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,-4.25,1.29,100*b/1 (X per km->km),reported,-0.0064916496909717845,0.0019704066120832006,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.294573643410853,257555.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,house,dwelling_type,A_structural,binary,binary,-0.023,0.0328,,,,,,high,single-family house dummy (reference: condominium),log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,pct_premium,-2.326306389801991,3.205420946776349,100*(exp(b - se^2/2) - 1),reported,-0.0013817153585312166,0.0019704462504271263,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7012195121951219,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,house,dwelling_type,A_structural,binary,binary,-0.0345,0.0362,,,,,,high,single-family house dummy (reference: condominium),log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-3.4544453383461238,3.4972397896650995,100*(exp(b - se^2/2) - 1),reported,-0.0018779099630821514,0.001970444656915185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9530386740331491,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,house,dwelling_type,A_structural,binary,binary,-0.026,0.0606,,,,,,high,single-family house dummy (reference: condominium),log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-2.7452323487801578,5.904470643029021,100*(exp(b - se^2/2) - 1),reported,-0.0008454064869193596,0.0019704474272043537,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.429042904290429,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,rowhouse,dwelling_type,A_structural,binary,binary,0.1565,0.0311,,,***,,,high,row house dummy (reference: condominium),log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,pct_premium,16.88453661525575,3.636867470812224,100*(exp(b - se^2/2) - 1),reported,0.009915111707117018,0.0019703512721491326,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.032154340836013,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,rowhouse,dwelling_type,A_structural,binary,binary,0.1556,0.0311,,,***,,,high,row house dummy (reference: condominium),log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,16.779387856341078,3.6335957625780386,100*(exp(b - se^2/2) - 1),reported,0.009858097452711068,0.001970352382900477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.003215434083601,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,rowhouse,dwelling_type,A_structural,binary,binary,0.1514,0.0315,,,***,,,high,row house dummy (reference: condominium),log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,16.288487040094356,3.6649051418611553,100*(exp(b - se^2/2) - 1),reported,0.009470237112769266,0.001970359769169299,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.806349206349206,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,i.walkBrew_0to5min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0053,0.0179,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-5min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,pct_premium,-0.5445325175295168,1.7805380961938158,100*(exp(b - se^2/2) - 1),reported,-0.0005834286770269217,0.0019704477959965844,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.29608938547486036,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,i.walkBrew_0to5min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0161,0.0212,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-5min of the home,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-1.6192193888991735,2.086141293956755,100*(exp(b - se^2/2) - 1),reported,-0.0014964235563706579,0.0019704459251588782,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7594339622641509,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,i.walkBrew_0to5min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0251,0.0299,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-5min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,2.495939277425485,3.0659987949180514,100*(exp(b - se^2/2) - 1),reported,0.0016541197470011564,0.0019704454356707,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8394648829431438,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,i.walkBrew_5to10min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0115,0.0232,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 5-10min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,pct_premium,-1.1700134804111917,2.293472823615158,100*(exp(b - se^2/2) - 1),reported,-0.0009767302888653308,0.0019704471914500587,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4956896551724138,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,i.walkBrew_5to10min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0077,0.0261,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 5-10min of the home,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.8008365801038142,2.589980175239847,100*(exp(b - se^2/2) - 1),reported,-0.0005813198485749964,0.001970447798416546,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2950191570881226,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,i.walkBrew_5to10min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0441,0.0243,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 5-10min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-4.342419905671302,2.3251655884744404,100*(exp(b - se^2/2) - 1),reported,-0.003575975596314488,0.0019704355326630855,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8148148148148149,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,i.walkBrew_10to15min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0115,0.0157,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 10-15min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,pct_premium,1.1441716393385093,1.5881592153590696,100*(exp(b - se^2/2) - 1),reported,0.0014433203763098395,0.0019704460789621288,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7324840764331211,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,i.walkBrew_10to15min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0332,0.0165,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 10-15min of the home,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,3.361655939049557,1.7056994955355456,100*(exp(b - se^2/2) - 1),reported,0.003964749320701311,0.001970432644324447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.012121212121212,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,i.walkBrew_10to15min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0233,0.0204,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 10-15min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-2.3233917632986545,1.9930174719611415,100*(exp(b - se^2/2) - 1),reported,-0.0022505551563606774,0.001970443141191323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.142156862745098,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,i.walkBrew_15to20min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.025,0.0145,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 15-20min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,pct_premium,-2.479261203715366,1.4141993724410824,100*(exp(b - se^2/2) - 1),reported,-0.0033973047589357457,0.001970436760182732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7241379310344829,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,i.walkBrew_15to20min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0259,0.0165,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 15-20min of the home,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-2.5700107610609146,1.6078136711827542,100*(exp(b - se^2/2) - 1),reported,-0.0030929916659254396,0.001970438706091496,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5696969696969696,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,i.walkBrew_15to20min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0059,0.026,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 15-20min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,0.5577496639447954,2.615385342128993,100*(exp(b - se^2/2) - 1),reported,0.0004471401081853226,0.0019704479343759978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.22692307692307692,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,i.walkBrew_20to25min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0105,0.0099,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 20-25min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,pct_premium,-1.0493559383387474,0.9796593832422203,100*(exp(b - se^2/2) - 1),reported,-0.002089864666433352,0.001970443828351446,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0606060606060606,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,i.walkBrew_20to25min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0075,0.0106,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 20-25min of the home,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.752770384070589,1.0520797381082867,100*(exp(b - se^2/2) - 1),reported,-0.0013941836436281595,0.001970446216327799,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7075471698113207,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,i.walkBrew_20to25min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0499,0.0144,,,***,,,high,time-invariant dummy: at least one craft brewery (ever) within 20-25min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-4.877407601712724,1.3699073551672365,100*(exp(b - se^2/2) - 1),reported,-0.006827990950831373,0.0019704021982359073,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.4652777777777777,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,i.walkBrew_25to30min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0142,0.0197,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 25-30min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,pct_premium,-1.4290945997618043,1.9422236786150515,100*(exp(b - se^2/2) - 1),reported,-0.0014203215859218657,0.001970446143849349,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7208121827411168,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,i.walkBrew_25to30min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0156,0.0191,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 25-30min of the home,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-1.5658515460792,1.8804352049728232,100*(exp(b - se^2/2) - 1),reported,-0.0016093691644541146,0.0019704455795559995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8167539267015707,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,i.walkBrew_25to30min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0037,0.0154,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 25-30min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-0.38112984946772066,1.5343125283110803,100*(exp(b - se^2/2) - 1),reported,-0.00047341930318214187,0.0019704479105418877,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.24025974025974026,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,i.walkBrew_30to35min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0109,0.0174,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 30-35min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,pct_premium,1.080659394306105,1.7590697412840417,100*(exp(b - se^2/2) - 1),reported,0.0012343602453699332,0.001970446630223563,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6264367816091955,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,i.walkBrew_30to35min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.007,0.0159,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 30-35min of the home,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,0.6897272372580199,1.6011690460542893,100*(exp(b - se^2/2) - 1),reported,0.0008674925616053337,0.0019704473899321154,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.440251572327044,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,i.walkBrew_30to35min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0017,0.012,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 30-35min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,0.16293259114303904,1.202041734983018,100*(exp(b - se^2/2) - 1),reported,0.0002791468077328057,0.0019704480545845106,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.14166666666666666,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c1,6,All craft breweries,16,i.walkBrew_35to40min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0139,0.0265,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 35-40min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: All craft breweries,pct_premium,1.3641076947186193,2.6870921935317424,100*(exp(b - se^2/2) - 1),reported,0.0010335552602550452,0.001970447078903503,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5245283018867924,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c2,6,Brewpubs/taprooms only,16,i.walkBrew_35to40min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0073,0.0206,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 35-40min of the home,log sale price (USD),log,OLS,257565.0,0.739,se,all home transactions; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,0.711299804684562,2.075093022506611,100*(exp(b - se^2/2) - 1),reported,0.0006982654297182583,0.00197044765098577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.35436893203883496,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T6-c3,6,Regional/microbreweries only,16,i.walkBrew_35to40min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0064,0.0165,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 35-40min of the home,log sale price (USD),log,OLS,257565.0,0.74,se,all home transactions; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,0.6283534090935294,1.6605938642050913,100*(exp(b - se^2/2) - 1),reported,0.0007642948095382263,0.0019704475558407395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3878787878787879,257555.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,logSQFT,living_area,A_structural,log,sqft,0.5034,0.0224,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,elasticity,0.5034,0.0224,b (log-log),reported,0.052767685485024696,0.0023480257347329226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.473214285714285,180877.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,logSQFT,living_area,A_structural,log,sqft,0.5046,0.0226,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,elasticity,0.5046,0.0226,b (log-log),reported,0.05242633262225449,0.0023480680088445328,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.327433628318587,180877.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,logSQFT,living_area,A_structural,log,sqft,0.5024,0.0226,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,elasticity,0.5024,0.0226,b (log-log),reported,0.05219838377636025,0.002348096085481174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.23008849557522,180877.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,bedrooms,bedrooms,A_structural,level,count,-0.0195,0.0033,,,***,,,high,,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,semi_elasticity,-1.95,0.33,100*b/1 (per unit count),reported,-0.013892713615933297,0.0023510746119271733,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.909090909090909,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,bedrooms,bedrooms,A_structural,level,count,-0.0196,0.0033,,,***,,,high,,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-1.96,0.33,100*b/1 (per unit count),reported,-0.01396394444444998,0.0023510722789124965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.9393939393939394,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,bedrooms,bedrooms,A_structural,level,count,-0.0194,0.0032,,,***,,,high,,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,-1.94,0.32,100*b/1 (per unit count),reported,-0.01425331748778819,0.0023510626783980523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0625,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,fullBaths,bathrooms,A_structural,level,count,0.0762,0.0051,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,semi_elasticity,7.62,0.51,100*b/1 (per unit count),reported,0.03510955167100679,0.0023498518834925803,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.941176470588236,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,fullBaths,bathrooms,A_structural,level,count,0.0764,0.0051,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,7.64,0.51,100*b/1 (per unit count),reported,0.03520158868538992,0.002349844270883359,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.980392156862743,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,fullBaths,bathrooms,A_structural,level,count,0.0763,0.0051,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,7.630000000000001,0.51,100*b/1 (per unit count),reported,0.03515557029001013,0.002349848079673023,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.96078431372549,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,halfBaths,bathrooms,A_structural,level,count,0.062,0.0072,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,semi_elasticity,6.2,0.72,100*b/1 (per unit count),reported,0.02024316979201654,0.002350819717782566,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.61111111111111,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,halfBaths,bathrooms,A_structural,level,count,0.0621,0.0072,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,6.21,0.72,100*b/1 (per unit count),reported,0.020275806653877865,0.002350818162768448,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.625,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,halfBaths,bathrooms,A_structural,level,count,0.0621,0.0073,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,6.21,0.73,100*b/1 (per unit count),reported,0.0199981677288279,0.0023508313111182556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.506849315068493,180877.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,distanceCBD,cbd_distance,D_location,level,km,-0.0212,0.0121,,,+,,,high,distance to CBD in km,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,semi_elasticity,-2.12,1.21,100*b/1 (X per km->km),reported,-0.004119600784966067,0.0023512815800985566,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7520661157024795,180877.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,distanceCBD,cbd_distance,D_location,level,km,-0.0215,0.012,,,+,,,high,distance to CBD in km,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-2.15,1.2,100*b/1 (X per km->km),reported,-0.004212711196817896,0.002351280667991384,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7916666666666665,180877.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,distanceCBD,cbd_distance,D_location,level,km,-0.0292,0.012,,,*,,,high,distance to CBD in km,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,-2.92,1.2,100*b/1 (X per km->km),reported,-0.005721406749240604,0.002351263047633125,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.433333333333333,180877.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,i.walkBrew_0to5min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0303,0.0148,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-5min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,pct_premium,-2.995180194242253,1.4358285764601064,100*(exp(b - se^2/2) - 1),reported,-0.0048137574983803085,0.002351274289637906,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0472972972972974,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,i.walkBrew_0to5min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0327,0.018,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-5min of the home,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-3.232791087641873,1.7420919564608965,100*(exp(b - se^2/2) - 1),reported,-0.004271492148381425,0.0023512800816778484,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8166666666666669,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,i.walkBrew_0to5min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0315,0.0131,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-5min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-3.109218424828386,1.269378152954399,100*(exp(b - se^2/2) - 1),reported,-0.005653802632037203,0.0023512639517361067,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.404580152671756,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,i.walkBrew_5to10min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0235,0.011,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 5-10min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,pct_premium,-2.3285118369041236,1.0744513721357283,100*(exp(b - se^2/2) - 1),reported,-0.005023171717522365,0.002351271867776426,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1363636363636367,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,i.walkBrew_5to10min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0262,0.0122,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 5-10min of the home,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-2.5932250743093688,1.188451095333001,100*(exp(b - se^2/2) - 1),reported,-0.005049452031309468,0.002351271556563951,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1475409836065573,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,i.walkBrew_5to10min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0103,0.0136,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 5-10min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-1.0338664765646266,1.34606389415169,100*(exp(b - se^2/2) - 1),reported,-0.001780762307559624,0.0023512978041563964,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7573529411764707,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,i.walkBrew_10to15min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0243,0.0142,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 10-15min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,pct_premium,-2.4105526667346,1.3859098725222934,100*(exp(b - se^2/2) - 1),reported,-0.0040236735713415515,0.002351282498479426,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7112676056338025,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,i.walkBrew_10to15min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0122,0.0181,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 10-15min of the home,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-1.2287687187835683,1.78805215408585,100*(exp(b - se^2/2) - 1),reported,-0.0015848531860666857,0.0023512985793284437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6740331491712707,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,i.walkBrew_10to15min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0506,0.0148,,,***,,,high,time-invariant dummy: at least one craft brewery (ever) within 10-15min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-4.944525242386821,1.406975109888945,100*(exp(b - se^2/2) - 1),reported,-0.00803864955190372,0.002351225560635871,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.418918918918919,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,i.walkBrew_15to20min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0182,0.0099,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 15-20min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,pct_premium,-1.8083500203382896,0.9721449735958029,100*(exp(b - se^2/2) - 1),reported,-0.004322554353217427,0.0023512795657611276,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8383838383838382,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,i.walkBrew_15to20min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0103,0.0108,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 15-20min of the home,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-1.0304857357007369,1.0689330924145775,100*(exp(b - se^2/2) - 1),reported,-0.002242439341749213,0.002351295620474903,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9537037037037037,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,i.walkBrew_15to20min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0308,0.0111,,,**,,,high,time-invariant dummy: at least one craft brewery (ever) within 15-20min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-3.0390247067341725,1.0763331312154045,100*(exp(b - se^2/2) - 1),reported,-0.006524193323767897,0.0023512514900592097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.774774774774775,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,i.walkBrew_20to25min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0095,0.0095,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 20-25min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,pct_premium,-0.9499714890941036,0.9410177333207554,100*(exp(b - se^2/2) - 1),reported,-0.0023512950325843313,0.0023512950325843317,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,i.walkBrew_20to25min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0099,0.0109,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 20-25min of the home,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.9909974362041551,1.0792622396144234,100*(exp(b - se^2/2) - 1),reported,-0.0021355809254808675,0.002351296170478935,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9082568807339451,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,i.walkBrew_20to25min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0336,0.0137,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 20-25min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-3.3132529360067053,1.3247327484882885,100*(exp(b - se^2/2) - 1),reported,-0.0057665998461030295,0.0023512624372503425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.452554744525547,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,i.walkBrew_25to30min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0249,0.0138,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 25-30min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,pct_premium,-2.468542597914569,1.3460622780968217,100*(exp(b - se^2/2) - 1),reported,-0.004242527627019654,0.002351280371601254,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8043478260869565,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,i.walkBrew_25to30min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0173,0.0164,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 25-30min of the home,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-1.7283378851200681,1.6118720086571605,100*(exp(b - se^2/2) - 1),reported,-0.0024803287429041956,0.0023512942996317234,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0548780487804876,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,i.walkBrew_25to30min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0093,0.0109,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 25-30min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-0.9315742094805568,1.0799099912642542,100*(exp(b - se^2/2) - 1),reported,-0.002006152316192038,0.0023512968006981954,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8532110091743118,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,i.walkBrew_30to35min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0025,0.0166,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 30-35min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,pct_premium,0.23650122398595208,1.66415519182562,100*(exp(b - se^2/2) - 1),reported,0.00035411165434662864,0.0023513013848616136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.15060240963855423,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,i.walkBrew_30to35min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0064,0.015,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 30-35min of the home,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-0.6491339632425097,1.4904306545687234,100*(exp(b - se^2/2) - 1),reported,-0.0010032214822589783,0.0023513003490444806,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4266666666666667,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,i.walkBrew_30to35min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0072,0.0131,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 30-35min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-0.7259327864189369,1.3006018738539955,100*(exp(b - se^2/2) - 1),reported,-0.0012923173202817714,0.002351299568846001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5496183206106869,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c1,7,All craft breweries,17,i.walkBrew_35to40min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0148,0.0251,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 35-40min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: All craft breweries,pct_premium,-1.5001346681181915,2.4731255440532847,100*(exp(b - se^2/2) - 1),reported,-0.001386423475406911,0.0023512992724806395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5896414342629482,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c2,7,Brewpubs/taprooms only,17,i.walkBrew_35to40min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0165,0.0176,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 35-40min of the home,log sale price (USD),log,OLS,180887.0,0.756,se,single-family homes; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-1.6516954259865213,1.7311982677275837,100*(exp(b - se^2/2) - 1),reported,-0.0022043398309258863,0.0023512958196542787,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9375,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T7-c3,7,Regional/microbreweries only,17,i.walkBrew_35to40min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0043,0.0161,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 35-40min of the home,log sale price (USD),log,OLS,180887.0,0.758,se,single-family homes; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-0.4419808769586808,1.6030918631385362,100*(exp(b - se^2/2) - 1),reported,-0.0006279872419358049,0.0023513010686433623,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2670807453416149,180877.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,logSQFT,living_area,A_structural,log,sqft,0.7188,0.0531,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,elasticity,0.7188,0.0531,b (log-log),reported,0.08811797584205765,0.0065095499682989175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.536723163841808,23416.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,logSQFT,living_area,A_structural,log,sqft,0.7192,0.0516,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,elasticity,0.7192,0.0516,b (log-log),reported,0.09070882140469437,0.006508030011793979,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.937984496124031,23416.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,logSQFT,living_area,A_structural,log,sqft,0.72,0.0531,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,elasticity,0.72,0.0531,b (log-log),reported,0.08826393921158884,0.006509465516854677,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.559322033898304,23416.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,bedrooms,bedrooms,A_structural,level,count,-0.0411,0.0102,,,***,,,high,,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,semi_elasticity,-4.109999999999999,1.02,100*b/1 (per unit count),reported,-0.02632296354257223,0.006532706280638363,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.029411764705882,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,bedrooms,bedrooms,A_structural,level,count,-0.0402,0.0099,,,***,,,high,,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-4.02,0.9900000000000001,100*b/1 (per unit count),reported,-0.026526603871512077,0.006532671102685811,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0606060606060606,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,bedrooms,bedrooms,A_structural,level,count,-0.0405,0.01,,,***,,,high,,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,-4.05,1.0,100*b/1 (per unit count),reported,-0.026457366528934396,0.006532683093564049,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.05,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,fullBaths,bathrooms,A_structural,level,count,0.1024,0.0107,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,semi_elasticity,10.24,1.0699999999999998,100*b/1 (per unit count),reported,0.06241833155760033,0.006522228004553939,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.570093457943926,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,fullBaths,bathrooms,A_structural,level,count,0.1029,0.0108,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,10.290000000000001,1.08,100*b/1 (per unit count),reported,0.062143407229775106,0.006522340117410798,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.527777777777779,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,fullBaths,bathrooms,A_structural,level,count,0.1006,0.0103,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,10.059999999999999,1.03,100*b/1 (per unit count),reported,0.06369737942790371,0.006521699881783381,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.766990291262136,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,halfBaths,bathrooms,A_structural,level,count,0.0665,0.0164,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,semi_elasticity,6.65,1.6400000000000001,100*b/1 (per unit count),reported,0.02648921092896801,0.006532677582482336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.054878048780488,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,halfBaths,bathrooms,A_structural,level,count,0.0666,0.0165,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,6.660000000000001,1.6500000000000001,100*b/1 (per unit count),reported,0.026368346529127416,0.006532698464423459,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.036363636363636,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,halfBaths,bathrooms,A_structural,level,count,0.0665,0.0164,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,6.65,1.6400000000000001,100*b/1 (per unit count),reported,0.02648921092896801,0.006532677582482336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.054878048780488,23416.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,distanceCBD,cbd_distance,D_location,level,km,-0.0278,0.012,,,*,,,high,distance to CBD in km,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,semi_elasticity,-2.78,1.2,100*b/1 (X per km->km),reported,-0.015137614137416985,0.006534221929820281,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3166666666666664,23416.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,distanceCBD,cbd_distance,D_location,level,km,-0.0379,0.0118,,,**,,,high,distance to CBD in km,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-3.7900000000000005,1.18,100*b/1 (X per km->km),reported,-0.02098481782672863,0.00653353167164638,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2118644067796613,23416.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,distanceCBD,cbd_distance,D_location,level,km,-0.0346,0.0131,,,**,,,high,distance to CBD in km,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,-3.46,1.31,100*b/1 (X per km->km),reported,-0.017257733809459788,0.006533997482772348,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6412213740458013,23416.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,i.walkBrew_0to5min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0135,0.0194,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-5min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,pct_premium,1.3400816740257282,1.9663675807134,100*(exp(b - se^2/2) - 1),reported,0.00454748414220535,0.0065349031376876875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6958762886597938,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,i.walkBrew_0to5min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0032,0.0197,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-5min of the home,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,0.3010477412985768,1.9763140971674393,100*(exp(b - se^2/2) - 1),reported,0.0010615174865380066,0.006534967026499601,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.16243654822335027,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,i.walkBrew_0to5min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0554,0.023,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-5min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,5.668378562839571,2.4310156255485347,100*(exp(b - se^2/2) - 1),reported,0.015738805840229617,0.006534161269409408,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.408695652173913,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,i.walkBrew_5to10min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0147,0.0203,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 5-10min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,pct_premium,1.459950167887314,2.0600614100348644,100*(exp(b - se^2/2) - 1),reported,0.004732167182566459,0.006534897537829872,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7241379310344828,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,i.walkBrew_5to10min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0138,0.0232,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 5-10min of the home,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,1.3622836640124092,2.3522379301033864,100*(exp(b - se^2/2) - 1),reported,0.003887151484731768,0.006534921336650508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5948275862068966,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,i.walkBrew_5to10min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0332,0.0227,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 5-10min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-3.290412829039746,2.195873311684372,100*(exp(b - se^2/2) - 1),reported,-0.009557317992462434,0.006534672241834256,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.462555066079295,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,i.walkBrew_10to15min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0388,0.0244,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 10-15min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,pct_premium,-3.834323007483642,2.347141111599762,100*(exp(b - se^2/2) - 1),reported,-0.010391113696024589,0.006534617891314433,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5901639344262295,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,i.walkBrew_10to15min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0287,0.0268,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 10-15min of the home,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-2.864096397717286,2.6041772607724742,100*(exp(b - se^2/2) - 1),reported,-0.00699809950388096,0.0065348106865508624,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0708955223880596,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,i.walkBrew_10to15min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0182,0.0184,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 10-15min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-1.8201593108441494,1.8068149004204819,100*(exp(b - se^2/2) - 1),reported,-0.006463803382536623,0.006534834188938124,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9891304347826088,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,i.walkBrew_15to20min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0143,0.0422,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 15-20min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,pct_premium,1.3499891646804318,4.28077953796601,100*(exp(b - se^2/2) - 1),reported,0.0022144514691783044,0.006534954685267444,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.33886255924170616,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,i.walkBrew_15to20min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0048,0.047,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 15-20min of the home,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,0.3702336779303428,4.722614230734456,100*(exp(b - se^2/2) - 1),reported,0.0006674011151947986,0.00653496925294907,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.10212765957446808,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,i.walkBrew_15to20min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0133,0.016,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 15-20min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-1.3338246593388003,1.5788608867106018,100*(exp(b - se^2/2) - 1),reported,-0.005432114254508091,0.006534874291137553,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8312499999999999,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,i.walkBrew_20to25min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0505,0.0196,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 20-25min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,pct_premium,-4.9428674604512395,1.8634777001977607,100*(exp(b - se^2/2) - 1),reported,-0.016835165837987127,0.006534044562862329,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5765306122448983,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,i.walkBrew_20to25min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0436,0.0246,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 20-25min of the home,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-4.295281153120822,2.3550485664315,100*(exp(b - se^2/2) - 1),reported,-0.011581529004430205,0.0065345324199308046,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7723577235772356,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,i.walkBrew_20to25min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0451,0.0171,,,**,,,high,time-invariant dummy: at least one craft brewery (ever) within 20-25min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-4.423786055448975,1.6345922265387134,100*(exp(b - se^2/2) - 1),reported,-0.017232948097624625,0.006534000276482951,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6374269005847952,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,i.walkBrew_25to30min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0051,0.024,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 25-30min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,pct_premium,-0.5373510762350819,2.387791159007183,100*(exp(b - se^2/2) - 1),reported,-0.0013886799365385421,0.006534964407240197,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.21250000000000002,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,i.walkBrew_25to30min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0303,0.0227,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 25-30min of the home,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-3.0095479690363858,2.202250586867866,100*(exp(b - se^2/2) - 1),reported,-0.008722558578623876,0.006534722103457491,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3348017621145374,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,i.walkBrew_25to30min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0068,0.0158,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 25-30min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,0.6697508668995544,1.5907806125413793,100*(exp(b - se^2/2) - 1),reported,0.002812507915226647,0.006534944861850153,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.43037974683544294,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,i.walkBrew_30to35min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0103,0.0426,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 30-35min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,pct_premium,-1.1144811278721023,4.216347197857499,100*(exp(b - se^2/2) - 1),reported,-0.0015800496308510344,0.006534962550898452,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.24178403755868547,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,i.walkBrew_30to35min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0084,0.0333,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 30-35min of the home,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,0.7876412010633604,3.3580898120426794,100*(exp(b - se^2/2) - 1),reported,0.0016484588398087022,0.006534961829241641,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.25225225225225223,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,i.walkBrew_30to35min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0087,0.0193,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 30-35min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,0.8550100083257739,1.9468642531299731,100*(exp(b - se^2/2) - 1),reported,0.0029458030299810245,0.0065349423538659515,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4507772020725388,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c1,8,All craft breweries,18,i.walkBrew_35to40min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.092,0.0309,,,**,,,high,time-invariant dummy: at least one craft brewery (ever) within 35-40min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: All craft breweries,pct_premium,9.584153695233866,3.3877673002297244,100*(exp(b - se^2/2) - 1),reported,0.019453188870806153,0.006533734088129459,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.977346278317152,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c2,8,Brewpubs/taprooms only,18,i.walkBrew_35to40min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0118,0.0212,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 35-40min of the home,log sale price (USD),log,OLS,23426.0,0.78,se,row houses; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-1.1952711968919227,2.09513101557058,100*(exp(b - se^2/2) - 1),reported,-0.003637365294358121,0.0065349274779993366,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5566037735849056,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T8-c3,8,Regional/microbreweries only,18,i.walkBrew_35to40min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0158,0.0211,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 35-40min of the home,log sale price (USD),log,OLS,23426.0,0.781,se,row houses; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,1.5699355067962273,2.143602762779391,100*(exp(b - se^2/2) - 1),reported,0.004893426585857141,0.006534892465923143,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7488151658767773,23416.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,18,logSQFT,living_area,A_structural,log,sqft,0.8589,0.0456,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,elasticity,0.8589,0.0456,b (log-log),reported,0.08135952841320968,0.004319471993995065,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.835526315789473,53242.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,18,logSQFT,living_area,A_structural,log,sqft,0.8614,0.0456,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,elasticity,0.8614,0.0456,b (log-log),reported,0.08159476721109075,0.004319388651991803,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.890350877192983,53242.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,18,logSQFT,living_area,A_structural,log,sqft,0.8463,0.0487,,,***,,,high,logged above-ground living area in square feet,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,elasticity,0.8463,0.0487,b (log-log),reported,0.07510001423119163,0.004321600724399187,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.37782340862423,53242.0,sqft,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,18,bedrooms,bedrooms,A_structural,level,count,-0.0112,0.0125,,,,,,high,,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,semi_elasticity,-1.1199999999999999,1.25,100*b/1 (per unit count),reported,-0.003883090879569792,0.004333806785234143,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8959999999999999,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,18,bedrooms,bedrooms,A_structural,level,count,-0.0098,0.0128,,,,,,high,,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-0.98,1.28,100*b/1 (per unit count),reported,-0.0033180775702501145,0.0043338156019593335,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7656249999999999,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,18,bedrooms,bedrooms,A_structural,level,count,-0.0102,0.0133,,,,,,high,,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,-1.02,1.3299999999999998,100*b/1 (per unit count),reported,-0.0033236780690096067,0.004333815521355664,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7669172932330828,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,18,fullBaths,bathrooms,A_structural,level,count,0.0951,0.0166,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,semi_elasticity,9.51,1.66,100*b/1 (per unit count),reported,0.02482055174993679,0.004332504301250796,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.728915662650603,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,18,fullBaths,bathrooms,A_structural,level,count,0.0943,0.0169,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,9.43,1.69,100*b/1 (per unit count),reported,0.024175243684050697,0.0043325728341511854,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.579881656804734,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,18,fullBaths,bathrooms,A_structural,level,count,0.0988,0.0173,,,***,,,high,number of full bathrooms,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,9.879999999999999,1.73,100*b/1 (per unit count),reported,0.024742904574591426,0.004332512643121777,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.710982658959538,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,18,halfBaths,bathrooms,A_structural,level,count,0.0839,0.0123,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,semi_elasticity,8.39,1.23,100*b/1 (per unit count),reported,0.02954880947461911,0.004331947038591359,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.821138211382114,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,18,halfBaths,bathrooms,A_structural,level,count,0.0837,0.0123,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,8.37,1.23,100*b/1 (per unit count),reported,0.029478432593668943,0.00433195604423092,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.804878048780488,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,18,halfBaths,bathrooms,A_structural,level,count,0.0868,0.013,,,***,,,high,number of half bathrooms,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,8.68,1.3,100*b/1 (per unit count),reported,0.028924605461311145,0.004332026163560425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.676923076923077,53242.0,count,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,18,distanceCBD,cbd_distance,D_location,level,km,-0.0156,0.0341,,,,,,high,distance to CBD in km,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,semi_elasticity,-1.5599999999999998,3.4099999999999997,100*b/1 (X per km->km),reported,-0.001982632336748033,0.004333830941224867,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4574780058651026,53242.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,18,distanceCBD,cbd_distance,D_location,level,km,-0.0107,0.0332,,,,,,high,distance to CBD in km,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,semi_elasticity,-1.0699999999999998,3.32,100*b/1 (X per km->km),reported,-0.0013967481017413484,0.004333835231571288,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.322289156626506,53242.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,18,distanceCBD,cbd_distance,D_location,level,km,-0.0142,0.0394,,,,,,high,distance to CBD in km,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,semi_elasticity,-1.4200000000000002,3.94,100*b/1 (X per km->km),reported,-0.001561940234753006,0.004333834172483693,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3604060913705584,53242.0,km,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,18,i.walkBrew_0to5min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0012,0.0414,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-5min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,pct_premium,-0.20548658664650832,4.1350349796080375,100*(exp(b - se^2/2) - 1),reported,-0.00012561853405317153,0.004333839424834418,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.02898550724637681,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,18,i.walkBrew_0to5min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0027,0.0483,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-5min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,0.1534731496799724,4.843058621205517,100*(exp(b - se^2/2) - 1),reported,0.00024226431047595285,0.0043338393318476005,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.055900621118012424,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,18,i.walkBrew_0to5min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0093,0.1116,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 0-5min of the home,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,0.30774456430522346,11.264272113788943,100*(exp(b - se^2/2) - 1),reported,0.0003611532646994546,0.004333839176393456,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.08333333333333333,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,18,i.walkBrew_5to10min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0026,0.0936,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 5-10min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,pct_premium,-0.6956173040451374,9.335695609399252,100*(exp(b - se^2/2) - 1),reported,-0.00012038442854512655,0.004333839427624556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.027777777777777776,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,18,i.walkBrew_5to10min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0151,0.0853,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 5-10min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,1.1527894898774038,8.659780375912216,100*(exp(b - se^2/2) - 1),reported,0.0007671858918275728,0.004333838183635229,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.17702227432590856,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,18,i.walkBrew_5to10min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0398,0.0495,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 5-10min of the home,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-4.019498545613997,4.7568590004732565,100*(exp(b - se^2/2) - 1),reported,-0.003484560874435173,0.0043338131478527905,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.804040404040404,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,18,i.walkBrew_10to15min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.1655,0.1387,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 10-15min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,pct_premium,16.868730219376495,16.366363692918906,100*(exp(b - se^2/2) - 1),reported,0.005171166837925318,0.004333781513113241,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1932227829848596,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,18,i.walkBrew_10to15min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.1963,0.1965,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 10-15min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,19.362378215908336,23.911926191747757,100*(exp(b - se^2/2) - 1),reported,0.004329387851774511,0.004333798842963277,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9989821882951654,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,True
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,18,i.walkBrew_10to15min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.032,0.049,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 10-15min of the home,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-3.2655412445819265,4.745682252188069,100*(exp(b - se^2/2) - 1),reported,-0.002830251168176071,0.004333822101269609,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6530612244897959,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,19,i.walkBrew_15to20min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.1027,0.0787,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 15-20min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,pct_premium,-10.03926107479327,7.101869522604144,100*(exp(b - se^2/2) - 1),reported,-0.005655377315608935,0.004333770153246575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3049555273189326,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,19,i.walkBrew_15to20min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0614,0.1,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 15-20min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-6.42435131736131,9.404469857359242,100*(exp(b - se^2/2) - 1),reported,-0.0026609680069678517,0.004333824115582821,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.614,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,19,i.walkBrew_15to20min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.164,0.1509,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 15-20min of the home,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,16.48759434050573,17.77925401474918,100*(exp(b - se^2/2) - 1),reported,0.004710018472526245,0.004333791387220795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0868124585818424,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,19,i.walkBrew_20to25min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.1252,0.0665,,,+,,,high,time-invariant dummy: at least one craft brewery (ever) within 20-25min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,pct_premium,13.087183992828844,7.536944451055766,100*(exp(b - se^2/2) - 1),reported,0.008159077285586827,0.004333695203606423,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8827067669172932,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,19,i.walkBrew_20to25min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.1842,0.0703,,,*,,,high,time-invariant dummy: at least one craft brewery (ever) within 20-25min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,19.928908851177063,8.451861439628965,100*(exp(b - se^2/2) - 1),reported,0.01135479038714611,0.004333560066321235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.620199146514936,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,True
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,19,i.walkBrew_20to25min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.1525,0.095,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 20-25min of the home,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-14.530662491627666,8.156309492585748,100*(exp(b - se^2/2) - 1),reported,-0.0069567844664705685,0.004333734585670191,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6052631578947367,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,19,i.walkBrew_25to30min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.1383,0.0504,,,**,,,high,time-invariant dummy: at least one craft brewery (ever) within 25-30min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,pct_premium,-13.026792975485101,4.389020502722333,100*(exp(b - se^2/2) - 1),reported,-0.011891421001199567,0.004333533032975114,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.744047619047619,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,19,i.walkBrew_25to30min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.1636,0.0466,,,***,,,high,time-invariant dummy: at least one craft brewery (ever) within 25-30min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-15.183982888994429,3.956720193543767,100*(exp(b - se^2/2) - 1),reported,-0.0152131777494952,0.004333337916421005,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5107296137339055,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,19,i.walkBrew_25to30min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0648,0.0491,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 25-30min of the home,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,-6.387419548202855,4.601921537458248,100*(exp(b - se^2/2) - 1),reported,-0.00571951534594873,0.00433376857231609,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.319755600814664,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,19,i.walkBrew_30to35min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0122,0.0383,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 30-35min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,pct_premium,1.153254793779257,3.8770121912602558,100*(exp(b - se^2/2) - 1),reported,0.0013804906271226826,0.004333835329409732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.31853785900783294,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,19,i.walkBrew_30to35min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0269,0.0402,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 30-35min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,2.643535565560251,4.1296055859019205,100*(exp(b - se^2/2) - 1),reported,0.0028999948066792745,0.004333821235260477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6691542288557214,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,19,i.walkBrew_30to35min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0569,0.0499,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 30-35min of the home,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,5.723287018260237,5.282164251036741,100*(exp(b - se^2/2) - 1),reported,0.004941732548714609,0.00433378654096413,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1402805611222444,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c1,9,All craft breweries,19,i.walkBrew_35to40min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0225,0.0717,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 35-40min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: All craft breweries,pct_premium,-2.475879125849023,7.010476370676222,100*(exp(b - se^2/2) - 1),reported,-0.0013599902043356477,0.004333835451149598,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3138075313807531,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c2,9,Brewpubs/taprooms only,19,i.walkBrew_35to40min,neighbourhood_amenities,F_neighbourhood,dummy,binary,-0.0321,0.0658,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 35-40min of the home,log sale price (USD),log,OLS,53252.0,0.783,se,condominiums; walk-time bins; brewery type: Brewpubs/taprooms only,pct_premium,-3.3684428938690947,6.372136064612915,100*(exp(b - se^2/2) - 1),reported,-0.002114223947015598,0.004333829773010167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.48784194528875374,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c,8965e19cc07a82548ccce5e2fba1b9f697ca577c:T9-c3,9,Regional/microbreweries only,19,i.walkBrew_35to40min,neighbourhood_amenities,F_neighbourhood,dummy,binary,0.0566,0.0881,,,,,,high,time-invariant dummy: at least one craft brewery (ever) within 35-40min of the home,log sale price (USD),log,OLS,53252.0,0.782,se,condominiums; walk-time bins; brewery type: Regional/microbreweries only,pct_premium,5.413359757061942,9.32302773254966,100*(exp(b - se^2/2) - 1),reported,0.002784271993117111,0.0043338226606646196,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6424517593643587,53242.0,binary,,2024.0,United States,North America,High income,1990.0,2016.0,mixed,transaction,journal,True,True,clustered,,2003.0,ols,journal,True,True,False
8a99113b012c7dc5288863734eba9456a85fd906,8a99113b012c7dc5288863734eba9456a85fd906,8a99113b012c7dc5288863734eba9456a85fd906:T2-c1,2,1,7,Number of bedrooms (NBR),bedrooms,A_structural,level,count,0.09,,2.72,,***,,,medium,count of bedrooms,Residential property monthly rentals (RPMR); specification says LN(MRP),log,OLS,90.0,0.96,t,Full sample; N not printed in table (90 per data section); t-statistics in separate column with stars; adj R2 0.92,semi_elasticity,9.0,3.308823529411764,100*b/1 (per unit count),|b/t|,0.2909491970543131,0.1069666165640857,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.72,80.0,count,,2025.0,Somalia,,,,,rental,rent,journal,False,False,unknown,ANN,2022.0,ols,journal,True,True,False
8a99113b012c7dc5288863734eba9456a85fd906,8a99113b012c7dc5288863734eba9456a85fd906,8a99113b012c7dc5288863734eba9456a85fd906:T2-c1,2,1,7,Dedicated parking space (DPS),parking,A_structural,binary,binary,-0.01,,-0.36,,,,,medium,presumed dummy for dedicated parking space (scale not described),Residential property monthly rentals (RPMR); specification says LN(MRP),log,OLS,90.0,0.96,t,Full sample; N not printed in table (90 per data section); t-statistics in separate column with stars; adj R2 0.92,pct_premium,-1.0332056249470867,2.7501384270810227,100*(exp(b - se^2/2) - 1),|b/t|,-0.04021666128175814,0.11171294800488372,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.36,80.0,binary,,2025.0,Somalia,,,,,rental,rent,journal,False,False,unknown,ANN,2022.0,ols,journal,True,True,False
8a99113b012c7dc5288863734eba9456a85fd906,8a99113b012c7dc5288863734eba9456a85fd906,8a99113b012c7dc5288863734eba9456a85fd906:T2-c1,2,1,7,Residential property size (RPS),living_area,A_structural,log,unknown,0.01,,0.26,,,,,medium,"specification enters LN(RPS); area unit not stated; text quotes b=0.07, t=2.26 instead (inconsistent)",Residential property monthly rentals (RPMR); specification says LN(MRP),log,OLS,90.0,0.96,t,Full sample; N not printed in table (90 per data section); t-statistics in separate column with stars; adj R2 0.92,elasticity,0.01,0.038461538461538464,b (log-log),|b/t|,0.029056609882120176,0.11175619185430835,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.26,80.0,unknown,,2025.0,Somalia,,,,,rental,rent,journal,False,False,unknown,ANN,2022.0,ols,journal,True,True,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TA-c1,A,1,20,DNWF50,living_area,A_structural,dummy,m2,-1.272,0.152,,,***,,,high,"Segment dummy: dwelling area up to 50 m2 (piecewise log-linear spline in dwelling area). Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.965,se,"Condominiums, year 2004 cross-section (centred moving sample over six quarters); robust estimation; D.F. residuals 10,345; regional quarterly coefficients not shown",pct_premium,-72.29485361556978,4.2601119013219355,100*(exp(b - se^2/2) - 1),reported,,,,-8.368421052631579,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TA-c1,A,1,20,LNWF50,living_area,A_structural,log,m2,1.114,0.035,,,***,,,high,"Slope of ln dwelling area (m2, SIA 416) for segment up to 50 m2 (piecewise spline). Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.965,se,"Condominiums, year 2004 cross-section (centred moving sample over six quarters); robust estimation; D.F. residuals 10,345; regional quarterly coefficients not shown",elasticity,1.114,0.035,b (log-log),reported,,,,31.82857142857143,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TA-c1,A,1,20,DNWF5075,living_area,A_structural,dummy,m2,-0.352,0.164,,,**,,,high,"Segment dummy: dwelling area 50-75 m2. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.965,se,"Condominiums, year 2004 cross-section (centred moving sample over six quarters); robust estimation; D.F. residuals 10,345; regional quarterly coefficients not shown",pct_premium,-30.61142795679942,11.533794000411993,100*(exp(b - se^2/2) - 1),reported,,,,-2.146341463414634,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TA-c1,A,1,20,LNWF5075,living_area,A_structural,log,m2,0.881,0.034,,,***,,,high,"Slope of ln dwelling area for segment 50-75 m2. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.965,se,"Condominiums, year 2004 cross-section (centred moving sample over six quarters); robust estimation; D.F. residuals 10,345; regional quarterly coefficients not shown",elasticity,0.881,0.034,b (log-log),reported,,,,25.91176470588235,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TA-c1,A,1,20,DNWF7500,living_area,A_structural,dummy,m2,-0.056,0.179,,,,,,high,"Segment dummy: dwelling area 75-100 m2. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.965,se,"Condominiums, year 2004 cross-section (centred moving sample over six quarters); robust estimation; D.F. residuals 10,345; regional quarterly coefficients not shown",pct_premium,-6.948817987663192,16.925150532438092,100*(exp(b - se^2/2) - 1),reported,,,,-0.3128491620111732,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TA-c1,A,1,20,LNWF7500,living_area,A_structural,log,m2,0.82,0.036,,,***,,,high,"Slope of ln dwelling area for segment 75-100 m2. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.965,se,"Condominiums, year 2004 cross-section (centred moving sample over six quarters); robust estimation; D.F. residuals 10,345; regional quarterly coefficients not shown",elasticity,0.82,0.036,b (log-log),reported,,,,22.77777777777778,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TA-c1,A,1,20,LNWF0150,living_area,A_structural,log,m2,0.81,0.017,,,***,,,high,"Slope of ln dwelling area for segment 100-150 m2 (reference segment). Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.965,se,"Condominiums, year 2004 cross-section (centred moving sample over six quarters); robust estimation; D.F. residuals 10,345; regional quarterly coefficients not shown",elasticity,0.81,0.017,b (log-log),reported,,,,47.64705882352941,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TA-c1,A,1,20,DNWF150P,living_area,A_structural,dummy,m2,-0.442,0.146,,,***,,,high,"Segment dummy: dwelling area above 150 m2. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.965,se,"Condominiums, year 2004 cross-section (centred moving sample over six quarters); robust estimation; D.F. residuals 10,345; regional quarterly coefficients not shown",pct_premium,-36.4064413589579,9.384144677650754,100*(exp(b - se^2/2) - 1),reported,,,,-3.0273972602739727,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TA-c1,A,1,20,LNWF150P,living_area,A_structural,log,m2,0.899,0.024,,,***,,,high,"Slope of ln dwelling area for segment above 150 m2. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.965,se,"Condominiums, year 2004 cross-section (centred moving sample over six quarters); robust estimation; D.F. residuals 10,345; regional quarterly coefficients not shown",elasticity,0.899,0.024,b (log-log),reported,,,,37.458333333333336,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TA-c1,A,1,20,stand: 4,condition,A_structural,dummy,ordinal,0.132,0.003,,,***,,,high,"Standard (quality) factor level 4 vs reference (5-level factor). Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.965,se,"Condominiums, year 2004 cross-section (centred moving sample over six quarters); robust estimation; D.F. residuals 10,345; regional quarterly coefficients not shown",pct_premium,14.110318429135216,0.3423324957801705,100*(exp(b - se^2/2) - 1),reported,,,,44.0,,ordinal,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TA-c1,A,1,20,stand: 5,condition,A_structural,dummy,ordinal,0.276,0.006,,,***,,,high,"Standard (quality) factor level 5 vs reference. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.965,se,"Condominiums, year 2004 cross-section (centred moving sample over six quarters); robust estimation; D.F. residuals 10,345; regional quarterly coefficients not shown",pct_premium,31.7824142979241,0.790708718416382,100*(exp(b - se^2/2) - 1),reported,,,,46.0,,ordinal,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,DVOL600,living_area,A_structural,dummy,m3,-1.566,0.144,,,***,,,high,"Segment dummy: cubic content up to 600 m3 (piecewise spline in ln building volume, SIA 416). Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",pct_premium,-79.32754400397609,3.007858027237588,100*(exp(b - se^2/2) - 1),reported,,,,-10.875000000000002,,m3,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,True
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,LVOL600,living_area,A_structural,log,m3,0.747,0.023,,,***,,,high,"Slope of ln cubic content (m3) for segment up to 600 m3; building volume used instead of floor area. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",elasticity,0.747,0.023,b (log-log),reported,,,,32.47826086956522,,m3,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,LVOL1300,living_area,A_structural,log,m3,0.507,0.004,,,***,,,high,"Slope of ln cubic content for segment 600-1300 m3 (reference segment). Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",elasticity,0.507,0.004,b (log-log),reported,,,,126.75,,m3,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,DVOL2300,living_area,A_structural,dummy,m3,-0.76,0.373,,,*,,,high,"Segment dummy: cubic content above 2300 m3. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",pct_premium,-56.376077285765966,17.443957727469613,100*(exp(b - se^2/2) - 1),reported,,,,-2.037533512064343,,m3,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,LVOL2300,living_area,A_structural,log,m3,0.627,0.051,,,***,,,high,"Slope of ln cubic content for segment above 2300 m3. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",elasticity,0.627,0.051,b (log-log),reported,,,,12.294117647058824,,m3,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,LLA2000,lot_size,A_structural,log,m2,0.002,0.002,,,,,,high,"Slope of ln site area (m2) up to 2000 m2. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",elasticity,0.002,0.002,b (log-log),reported,,,,1.0,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,LLAE250,lot_size,A_structural,log,m2,0.021,0.001,,,***,,,high,"Slope of ln additional site area (landexc, m2) up to 250 m2. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",elasticity,0.021,0.001,b (log-log),reported,,,,21.0,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,DLAE600,lot_size,A_structural,dummy,m2,-0.301,0.085,,,***,,,high,"Segment dummy: additional site area 250-600 m2. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",pct_premium,-26.259093495180565,6.290661068347015,100*(exp(b - se^2/2) - 1),reported,,,,-3.5411764705882347,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,True
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,LLAE600,lot_size,A_structural,log,m2,0.077,0.014,,,***,,,high,"Slope of ln additional site area for segment 250-600 m2. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",elasticity,0.077,0.014,b (log-log),reported,,,,5.5,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,DLAE1800,lot_size,A_structural,dummy,m2,0.055,0.126,,,,,,high,"Segment dummy: additional site area above 600/1800 m2. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",pct_premium,4.818699465875076,13.312411744911227,100*(exp(b - se^2/2) - 1),reported,,,,0.4365079365079365,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,LLAE1800,lot_size,A_structural,log,m2,0.023,0.019,,,,,,high,"Slope of ln additional site area for upper segment. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",elasticity,0.023,0.019,b (log-log),reported,,,,1.2105263157894737,,m2,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,stand: 4,condition,A_structural,dummy,ordinal,0.123,0.004,,,***,,,high,"Standard (quality) factor level 4 vs reference. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",pct_premium,13.087537390830995,0.4523537683789957,100*(exp(b - se^2/2) - 1),reported,,,,30.75,,ordinal,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,8b40d59c2cf1fb45e2898b8a9d2bc70967606aa7:TB-c1,B,1,21,stand: 5,condition,A_structural,dummy,ordinal,0.215,0.007,,,***,,,high,"Standard (quality) factor level 5 vs reference. Standard error printed in a separate column; significance symbols: '.' 10%, * 5%, ** 1%, *** 0.1% (1 per mille).",ln transaction price (CHF),log,other,,0.937,se,"Single family houses, year 2004 cross-section; robust estimation; D.F. residuals 7,163; regional quarterly coefficients not shown",pct_premium,23.983152072169677,0.8679033278762432,100*(exp(b - se^2/2) - 1),reported,,,,30.71428571428571,,ordinal,,2008.0,Switzerland,Europe,High income,1985.0,2004.0,mixed,transaction,journal,True,True,unknown,,1994.5,other,journal,True,False,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c1,2,1,10,Close (within 1/2 mile of station),transit_distance,D_location,binary,binary (within 800 m of light rail station),0.0384,0.0136,,,**,,,high,Pre-opening proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1851.0,0.38,se,Beacon Hill station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,3.9050712627921147,1.413239659534471,100*(exp(b - se^2/2) - 1),reported,0.06566396622666694,0.023255988038611213,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8235294117647056,1841.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c2,2,2,10,Close (within 1/2 mile of station),transit_distance,D_location,binary,binary (within 800 m of light rail station),-0.1298,0.0148,,,***,,,high,Pre-opening proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2871.0,0.69,se,Mount Baker station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,-12.182511541041919,1.299841180003341,100*(exp(b - se^2/2) - 1),reported,-0.16180545856400075,0.0184493126868044,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.77027027027027,2861.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c3,2,3,10,Close (within 1/2 mile of station),transit_distance,D_location,binary,binary (within 800 m of light rail station),-0.1048,0.0096,,,***,,,high,Pre-opening proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,6015.0,0.52,se,Columbia City station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,-9.95368887977116,0.8644844212785346,100*(exp(b - se^2/2) - 1),reported,-0.13949746088542364,0.012778393363550258,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.916666666666668,6005.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c4,2,4,10,Close (within 1/2 mile of station),transit_distance,D_location,binary,binary (within 800 m of light rail station),-0.0828,0.0095,,,***,,,high,Pre-opening proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4506.0,0.66,se,Othello station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,-7.950630235748612,0.8745084740649279,100*(exp(b - se^2/2) - 1),reported,-0.12890070231875414,0.014789331787779761,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.715789473684211,4496.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c5,2,5,10,Close (within 1/2 mile of station),transit_distance,D_location,binary,binary (within 800 m of light rail station),-0.0031,0.0085,,,,,,high,Pre-opening proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,5921.0,0.57,se,Rainier Beach station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,-0.3131212496742086,0.8473690800328773,100*(exp(b - se^2/2) - 1),reported,-0.004743592811047946,0.013006625449647598,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.36470588235294116,5911.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c6,2,6,10,Close (within 1/2 mile of station),transit_distance,D_location,binary,binary (within 800 m of light rail station),-0.0106,0.0096,,,,,,high,Pre-opening proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4673.0,0.63,se,Tukwila/Intl Blvd station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,-1.0589611058926751,0.9498777427413619,100*(exp(b - se^2/2) - 1),reported,-0.016167585144659317,0.014642341263087682,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1041666666666667,4663.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c7,2,7,10,Close (within 1/2 mile of station),transit_distance,D_location,binary,binary (within 800 m of light rail station),-0.0222,0.0154,,,,,,high,Pre-opening proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3817.0,0.7,se,SeaTac Airport station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,-2.2071363085769957,1.5061886941142584,100*(exp(b - se^2/2) - 1),reported,-0.023357282608144198,0.01620279964709102,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4415584415584415,3807.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c1,2,1,10,Baths,bathrooms,A_structural,level,count,0.0285,0.0107,,,**,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1851.0,0.38,se,Beacon Hill station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,2.85,1.0699999999999998,100*b/1 (per unit count),reported,0.06195822883483158,0.0232615104748315,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6635514018691593,1841.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c2,2,2,10,Baths,bathrooms,A_structural,level,count,0.0565,0.0091,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2871.0,0.69,se,Mount Baker station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,5.65,0.91,100*b/1 (per unit count),reported,0.11530332273964798,0.01857097764479286,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.208791208791209,2861.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c3,2,3,10,Baths,bathrooms,A_structural,level,count,0.0204,0.0064,,,**,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,6015.0,0.52,se,Columbia City station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,2.04,0.64,100*b/1 (per unit count),reported,0.04109855909484502,0.01289366559838275,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1875,6005.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c4,2,4,10,Baths,bathrooms,A_structural,level,count,0.0347,0.0067,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4506.0,0.66,se,Othello station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,3.47,0.67,100*b/1 (per unit count),reported,0.07701048706448495,0.014869460038387582,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.179104477611941,4496.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c5,2,5,10,Baths,bathrooms,A_structural,level,count,0.0241,0.0055,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,5921.0,0.57,se,Rainier Beach station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,2.41,0.5499999999999999,100*b/1 (per unit count),reported,0.05690097010306409,0.012985698571238692,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.381818181818182,5911.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c6,2,6,10,Baths,bathrooms,A_structural,level,count,0.0185,0.0053,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4673.0,0.63,se,Tukwila/Intl Blvd station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,1.8499999999999999,0.53,100*b/1 (per unit count),reported,0.0510500888677439,0.014625160594542847,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.490566037735849,4663.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c7,2,7,10,Baths,bathrooms,A_structural,level,count,0.0192,0.0057,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3817.0,0.7,se,SeaTac Airport station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,1.92,0.5700000000000001,100*b/1 (per unit count),reported,0.05451157352095769,0.016183123389034316,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3684210526315783,3807.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c1,2,1,10,Size (ft2),living_area,A_structural,level,sqft,0.00035,4e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1851.0,0.38,se,Beacon Hill station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,0.37673686458484024,0.04305564166683889,100*b/0.092903 (X per sqft->m2),reported,0.19981739325112938,0.022836273514414782,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.75,1841.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c2,2,2,10,Size (ft2),living_area,A_structural,level,sqft,0.00048,2e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2871.0,0.69,se,Mount Baker station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,0.5166677000020666,0.021527820833419444,100*b/0.092903 (X per sqft->m2),reported,0.40937514922362117,0.01705729788431755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.0,2861.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c3,2,3,10,Size (ft2),living_area,A_structural,level,sqft,0.0003,2e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,6015.0,0.52,se,Columbia City station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,0.32291731250129163,0.021527820833419444,100*b/0.092903 (X per sqft->m2),reported,0.19004096880261104,0.012669397920174071,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.999999999999998,6005.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c4,2,4,10,Size (ft2),living_area,A_structural,level,sqft,0.00031,2e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4506.0,0.66,se,Othello station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,0.33368122291800134,0.021527820833419444,100*b/0.092903 (X per sqft->m2),reported,0.2252238556804993,0.014530571334225764,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.499999999999998,4496.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c5,2,5,10,Size (ft2),living_area,A_structural,level,sqft,0.000431,2e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,5921.0,0.57,se,Rainier Beach station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,0.463924538960189,0.021527820833419444,100*b/0.092903 (X per sqft->m2),reported,0.2698941494043267,0.01252409045959753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.549999999999997,5911.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c6,2,6,10,Size (ft2),living_area,A_structural,level,sqft,0.0003,2e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4673.0,0.63,se,Tukwila/Intl Blvd station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,0.32291731250129163,0.021527820833419444,100*b/0.092903 (X per sqft->m2),reported,0.21454858788398362,0.014303239192265577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.999999999999998,4663.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c7,2,7,10,Size (ft2),living_area,A_structural,level,sqft,0.00031,2e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3817.0,0.7,se,SeaTac Airport station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,0.33368122291800134,0.021527820833419444,100*b/0.092903 (X per sqft->m2),reported,0.24364173432784875,0.015718821569538632,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.499999999999998,3807.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c1,2,1,10,Age,age,A_structural,level,years,-0.00593,0.00089,,,***,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1851.0,0.38,se,Beacon Hill station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,-0.5930000000000001,0.089,100*b/1 (per year),reported,-0.15344882469082996,0.023030262053092526,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.662921348314607,1841.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c2,2,2,10,Age,age,A_structural,level,years,-0.00213,0.000821,,,**,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2871.0,0.69,se,Mount Baker station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,-0.213,0.0821,100*b/1 (per year),reported,-0.048447040092301746,0.018673718270319124,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5943970767356883,2861.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c3,2,3,10,Age,age,A_structural,level,years,-0.00509,0.000474,,,***,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,6015.0,0.52,se,Columbia City station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,-0.509,0.0474,100*b/1 (per year),reported,-0.1372627256148782,0.012782422778281387,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.738396624472575,6005.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c4,2,4,10,Age,age,A_structural,level,years,-0.00484,0.000497,,,***,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4506.0,0.66,se,Othello station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,-0.484,0.04970000000000001,100*b/1 (per year),reported,-0.1437285469049373,0.014758902440445011,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.738430583501005,4496.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c5,2,5,10,Age,age,A_structural,level,years,-0.004017,0.00039,,,***,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,5921.0,0.57,se,Rainier Beach station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,-0.40169999999999995,0.039,100*b/1 (per year),reported,-0.13278345691419913,0.01289159775866011,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.299999999999999,5911.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c6,2,6,10,Age,age,A_structural,level,years,-0.006067,0.000376,,,***,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4673.0,0.63,se,Tukwila/Intl Blvd station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,-0.6067,0.037599999999999995,100*b/1 (per year),reported,-0.22996164437386885,0.014251784784007694,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.135638297872344,4663.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c7,2,7,10,Age,age,A_structural,level,years,-0.006522,0.000495,,,***,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3817.0,0.7,se,SeaTac Airport station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,-0.6522,0.0495,100*b/1 (per year),reported,-0.2088340418918817,0.01584986978480243,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.175757575757576,3807.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c2,2,2,10,Waterfront,waterfront,C_exterior,binary,binary,0.6723,0.0712,,,***,,,high,Not estimable for Beacon Hill (no waterfront lots),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2871.0,0.69,se,Mount Baker station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,95.3778675880694,13.946209144501388,100*(exp(b - se^2/2) - 1),reported,0.17384427383745343,0.018410995533581265,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.442415730337078,2861.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c3,2,3,10,Waterfront,waterfront,C_exterior,binary,binary,0.2902,0.0253,,,***,,,high,Not estimable for Beacon Hill (no waterfront lots),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,6015.0,0.52,se,Columbia City station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,33.62670662167828,3.3818378446411246,100*(exp(b - se^2/2) - 1),reported,0.14642460929480527,0.012765481099788329,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.470355731225297,6005.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c4,2,4,10,Waterfront,waterfront,C_exterior,binary,binary,0.2269,0.0234,,,***,,,high,Not estimable for Beacon Hill (no waterfront lots),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4506.0,0.66,se,Othello station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,25.436092527839428,2.9360082754721755,100*(exp(b - se^2/2) - 1),reported,0.1431235748116552,0.014760210007019532,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.696581196581196,4496.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c5,2,5,10,Waterfront,waterfront,C_exterior,binary,binary,0.4724,0.0201,,,***,,,high,Not estimable for Beacon Hill (no waterfront lots),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,5921.0,0.57,se,Rainier Beach station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,60.3514840218927,3.223715969815445,100*(exp(b - se^2/2) - 1),reported,0.29233743081934743,0.012438574003956147,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.502487562189053,5911.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c6,2,6,10,Waterfront,waterfront,C_exterior,binary,binary,0.0372,0.0498,,,,,,high,Not estimable for Beacon Hill (no waterfront lots),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4673.0,0.63,se,Tukwila/Intl Blvd station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,3.661436035409027,5.168744889383892,100*(exp(b - se^2/2) - 1),reported,0.010938427845183125,0.014643379212099992,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7469879518072289,4663.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c7,2,7,10,Waterfront,waterfront,C_exterior,binary,binary,0.0584,0.0077,,,***,,,high,Not estimable for Beacon Hill (no waterfront lots),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3817.0,0.7,se,SeaTac Airport station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,6.010753914324862,0.8163070042027487,100*(exp(b - se^2/2) - 1),reported,0.12200402357843669,0.016086146944417165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.584415584415584,3807.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c1,2,1,10,View,view,E_environment,binary,binary (outstanding view),0.0509,0.0181,,,**,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1851.0,0.38,se,Beacon Hill station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,5.204532185631616,1.90451397592212,100*(exp(b - se^2/2) - 1),reported,0.06540056971235958,0.023256391194375413,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8121546961325965,1841.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c2,2,2,10,View,view,E_environment,binary,binary (outstanding view),0.1599,0.0142,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2871.0,0.69,se,Mount Baker station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,17.32752302001814,1.6662188065963393,100*(exp(b - se^2/2) - 1),reported,0.20600811913194086,0.01829465473216736,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.260563380281688,2861.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c3,2,3,10,View,view,E_environment,binary,binary (outstanding view),0.2325,0.0103,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,6015.0,0.52,se,Columbia City station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,26.168351858166684,1.299602959749756,100*(exp(b - se^2/2) - 1),reported,0.2796688661174585,0.012389631488214292,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.572815533980584,6005.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c4,2,4,10,View,view,E_environment,binary,binary (outstanding view),0.2869,0.0124,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4506.0,0.66,se,Othello station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,33.21885551230355,1.6520408123681216,100*(exp(b - se^2/2) - 1),reported,0.32618776468522465,0.01409804211257158,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.137096774193548,4496.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,True
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c5,2,5,10,View,view,E_environment,binary,binary (outstanding view),0.2198,0.0087,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,5921.0,0.57,se,Rainier Beach station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,24.578039271003238,1.0838699599401886,100*(exp(b - se^2/2) - 1),reported,0.31218453259979345,0.012356712618827129,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.264367816091955,5911.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c6,2,6,10,View,view,E_environment,binary,binary (outstanding view),0.0611,0.0119,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4673.0,0.63,se,Tukwila/Intl Blvd station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,6.292994597397916,1.2649761991780102,100*(exp(b - se^2/2) - 1),reported,0.07497860231511974,0.014603033838787643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.134453781512605,4663.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c7,2,7,10,View,view,E_environment,binary,binary (outstanding view),0.1484,0.0112,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3817.0,0.7,se,SeaTac Airport station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,15.990404283189186,1.2991740096103106,100*(exp(b - se^2/2) - 1),reported,0.20995903993277057,0.01584596527794495,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.25,3807.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c2,2,2,10,Lot (acres),lot_size,A_structural,level,acres,1.3753,0.1827,,,***,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2871.0,0.69,se,Mount Baker station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,0.03398440311317925,0.0045146153194051105,100*b/4046.86 (X per acre->m2),reported,0.13936096812286836,0.018513232659091144,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.527640941434044,2861.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c3,2,3,10,Lot (acres),lot_size,A_structural,level,acres,0.8103,0.0983,,,***,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,6015.0,0.52,se,Columbia City station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,0.020022949060284408,0.0024290458998222353,100*b/4046.86 (X per acre->m2),reported,0.10577730437738944,0.012832172060097968,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.243133265513734,6005.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c4,2,4,10,Lot (acres),lot_size,A_structural,level,acres,0.8986,0.0824,,,***,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4506.0,0.66,se,Othello station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,0.022204889578639475,0.0020361483432894422,100*b/4046.86 (X per acre->m2),reported,0.16053022383895174,0.014720332121444048,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.905339805825243,4496.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c5,2,5,10,Lot (acres),lot_size,A_structural,level,acres,-0.0818,0.0355,,,*,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,5921.0,0.57,se,Rainier Beach station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,-0.002021322020401412,0.0008772241042084369,100*b/4046.86 (X per acre->m2),reported,-0.029957082104010494,0.01300093416494343,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.304225352112676,5911.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c6,2,6,10,Lot (acres),lot_size,A_structural,level,acres,0.2,0.0267,,,***,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4673.0,0.63,se,Tukwila/Intl Blvd station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,0.004942107629343307,0.0006597713685173314,100*b/4046.86 (X per acre->m2),reported,0.1090407175211813,0.014556935789077704,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.49063670411985,4663.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c7,2,7,10,Lot (acres),lot_size,A_structural,level,acres,0.5928,0.0494,,,***,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3817.0,0.7,se,SeaTac Airport station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,semi_elasticity,0.014648407013373561,0.0012207005844477967,100*b/4046.86 (X per acre->m2),reported,0.19090958396133906,0.015909131996778257,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,3807.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c1,2,1,10,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.0775,0.014,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1851.0,0.38,se,Beacon Hill station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,8.047634058856534,1.5128151254419837,100*(exp(b - se^2/2) - 1),reported,0.12795640452819382,0.023114705334125338,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.535714285714286,1841.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c2,2,2,10,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.1413,0.0149,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2871.0,0.69,se,Mount Baker station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,15.164228205131746,1.7161374895256616,100*(exp(b - se^2/2) - 1),reported,0.1745727004528992,0.018408586247333318,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.483221476510067,2861.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c3,2,3,10,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.0701,0.0087,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,6015.0,0.52,se,Columbia City station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,7.257484507194567,0.9331754305685036,100*(exp(b - se^2/2) - 1),reported,0.10342063024283163,0.0128353706578122,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.057471264367816,6005.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c4,2,4,10,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.042,0.0102,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4506.0,0.66,se,Othello station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,4.284022879103233,1.0637523683257786,100*(exp(b - se^2/2) - 1),reported,0.06129409205737587,0.014885708071077001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.117647058823529,4496.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c5,2,5,10,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.0784,0.0079,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,5921.0,0.57,se,Rainier Beach station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,8.152144483163859,0.8544286034455687,100*(exp(b - se^2/2) - 1),reported,0.12801777635048672,0.012899750423072006,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.924050632911392,5911.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c6,2,6,10,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.048,0.0069,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4673.0,0.63,se,Tukwila/Intl Blvd station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,4.91456801142891,0.7239277521738847,100*(exp(b - se^2/2) - 1),reported,0.10134853410707163,0.014568851777891547,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.9565217391304355,4663.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T2-c7,2,7,10,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.073,0.0085,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3817.0,0.7,se,SeaTac Airport station neighbourhood (houses within 2 miles of station); sales 1992-2008 (before) vs 2010-2016 (after); DiD,pct_premium,7.569167685097167,0.914370956377498,100*(exp(b - se^2/2) - 1),reported,0.13786234634705907,0.01605246498561647,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.588235294117647,3807.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c1,3,1,12,Close,transit_distance,D_location,binary,binary (within 800 m of light rail station),0.0394,0.0159,,,*,,,high,Pre-construction proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1451.0,0.42,se,Beacon Hill station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,4.005499857478778,1.6538964953077941,100*(exp(b - se^2/2) - 1),reported,0.06513940094914977,0.02628722017998684,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4779874213836477,1441.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c2,3,2,12,Close,transit_distance,D_location,binary,binary (within 800 m of light rail station),-0.1449,0.0174,,,***,,,high,Pre-construction proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2264.0,0.7,se,Mount Baker station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,-13.502215059291023,1.5052893114176358,100*(exp(b - se^2/2) - 1),reported,-0.17276745668082177,0.020746402665605925,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.327586206896552,2254.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c3,3,3,12,Close,transit_distance,D_location,binary,binary (within 800 m of light rail station),-0.1234,0.0113,,,***,,,high,Pre-construction proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4697.0,0.55,se,Columbia City station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,-11.614640360681673,0.9988183314450279,100*(exp(b - se^2/2) - 1),reported,-0.1575191468762377,0.014424362720433436,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.920353982300885,4687.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c4,3,4,12,Close,transit_distance,D_location,binary,binary (within 800 m of light rail station),-0.0907,0.0119,,,***,,,high,Pre-construction proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3356.0,0.67,se,Othello station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,-8.677300602408344,1.0868170721899053,100*(exp(b - se^2/2) - 1),reported,-0.13063502848719433,0.017139546185199698,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.621848739495798,3346.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c5,3,5,12,Close,transit_distance,D_location,binary,binary (within 800 m of light rail station),-0.0098,0.0104,,,,,,high,Pre-construction proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4454.0,0.57,se,Rainier Beach station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,-0.980568763818801,1.029857778058964,100*(exp(b - se^2/2) - 1),reported,-0.01413391020946973,0.014999251650865835,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9423076923076923,4444.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c6,3,6,12,Close,transit_distance,D_location,binary,binary (within 800 m of light rail station),-0.005,0.0119,,,,,,high,Pre-construction proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3484.0,0.61,se,Tukwila/Intl Blvd station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,-0.505797017179388,1.184064850239292,100*(exp(b - se^2/2) - 1),reported,-0.007128482720592769,0.01696578887501079,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.42016806722689076,3474.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c7,3,7,12,Close,transit_distance,D_location,binary,binary (within 800 m of light rail station),-0.0206,0.0182,,,,,,high,Pre-construction proximity differential (DiD main effect),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2905.0,0.7,se,SeaTac Airport station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,-2.0551499191323486,1.782891529515916,100*(exp(b - se^2/2) - 1),reported,-0.02103175312813913,0.018581451792821953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1318681318681318,2895.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c1,3,1,12,Baths,bathrooms,A_structural,level,count,0.0282,0.0121,,,*,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1451.0,0.42,se,Beacon Hill station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,2.82,1.21,100*b/1 (per unit count),reported,0.061279440015605716,0.026293660432227983,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3305785123966944,1441.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c2,3,2,12,Baths,bathrooms,A_structural,level,count,0.0578,0.0101,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2264.0,0.7,se,Mount Baker station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,5.779999999999999,1.01,100*b/1 (per unit count),reported,0.11967325652430502,0.020911762818260914,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.7227722772277225,2254.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c3,3,3,12,Baths,bathrooms,A_structural,level,count,0.0154,0.0072,,,*,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4697.0,0.55,se,Columbia City station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,1.54,0.72,100*b/1 (per unit count),reported,0.031226901967501622,0.014599590530260498,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.138888888888889,4687.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c4,3,4,12,Baths,bathrooms,A_structural,level,count,0.0272,0.0078,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3356.0,0.67,se,Othello station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,2.7199999999999998,0.7799999999999999,100*b/1 (per unit count),reported,0.0601760368430701,0.01725636350646863,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4871794871794872,3346.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c5,3,5,12,Baths,bathrooms,A_structural,level,count,0.0198,0.0065,,,**,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4454.0,0.57,se,Rainier Beach station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,1.9800000000000002,0.65,100*b/1 (per unit count),reported,0.04564696199709757,0.014985113786925967,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0461538461538464,4444.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c6,3,6,12,Baths,bathrooms,A_structural,level,count,0.0088,0.0063,,,,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3484.0,0.61,se,Tukwila/Intl Blvd station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.88,0.63,100*b/1 (per unit count),reported,0.023692194663985897,0.01696145754353536,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.396825396825397,3474.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c7,3,7,12,Baths,bathrooms,A_structural,level,count,0.0193,0.0067,,,**,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2905.0,0.7,se,SeaTac Airport station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,1.9300000000000002,0.67,100*b/1 (per unit count),reported,0.05346095479835414,0.01855898430823693,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8805970149253732,2895.0,count,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c1,3,1,12,Size (ft2),living_area,A_structural,level,sqft,0.000352,5e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1451.0,0.42,se,Beacon Hill station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.3788896466681822,0.05381955208354861,100*b/0.092903 (X per sqft->m2),reported,0.18234661042923087,0.025901507163243024,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.039999999999999,1441.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c2,3,2,12,Size (ft2),living_area,A_structural,level,sqft,0.000483,2.4e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2264.0,0.7,se,Mount Baker station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.5198968731270796,0.025833385000103334,100*b/0.092903 (X per sqft->m2),reported,0.39027923438828,0.019392756988237513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.125,2254.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c3,3,3,12,Size (ft2),living_area,A_structural,level,sqft,0.000322,2.6e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4697.0,0.55,se,Columbia City station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.346597915418053,0.027986167083445274,100*b/0.092903 (X per sqft->m2),reported,0.17800936592476865,0.0143734270622484,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.384615384615387,4687.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c4,3,4,12,Size (ft2),living_area,A_structural,level,sqft,0.000307,1.7e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3356.0,0.67,se,Othello station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.3304520497929884,0.018298647708406526,100*b/0.092903 (X per sqft->m2),reported,0.2980100814415694,0.016502186920217196,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.058823529411764,3346.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c5,3,5,12,Size (ft2),living_area,A_structural,level,sqft,0.000447,2.3e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4454.0,0.57,se,Rainier Beach station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.4811467956269246,0.02475699395843236,100*b/0.092903 (X per sqft->m2),reported,0.2798846682868021,0.014401224542721358,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.434782608695652,4444.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c6,3,6,12,Size (ft2),living_area,A_structural,level,sqft,0.000323,1.7e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3484.0,0.61,se,Tukwila/Intl Blvd station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.347674306459724,0.018298647708406526,100*b/0.092903 (X per sqft->m2),reported,0.30681099337932694,0.016147947019964574,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.0,3474.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c7,3,7,12,Size (ft2),living_area,A_structural,level,sqft,0.000297,2.1e-05,,,***,,,high,Quadratic in size (Size2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2905.0,0.7,se,SeaTac Airport station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.3196881393762787,0.022604211875090412,100*b/0.092903 (X per sqft->m2),reported,0.2542174722241729,0.017974972783527374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.142857142857144,2895.0,sqft,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c1,3,1,12,Age,age,A_structural,level,years,-0.005313,0.001009,,,***,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1451.0,0.42,se,Beacon Hill station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,-0.5313,0.10089999999999999,100*b/1 (per year),reported,-0.1373972887863963,0.026093330394405017,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.265609514370665,1441.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c2,3,2,12,Age,age,A_structural,level,years,-0.001945,0.000932,,,*,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2264.0,0.7,se,Mount Baker station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,-0.19449999999999998,0.0932,100*b/1 (per year),reported,-0.04391446225212218,0.021042816873510475,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.086909871244635,2254.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c3,3,3,12,Age,age,A_structural,level,years,-0.004767,0.000535,,,***,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4697.0,0.55,se,Columbia City station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,-0.4767,0.0535,100*b/1 (per year),reported,-0.12906142070093218,0.01448455214495463,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.910280373831776,4687.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c4,3,4,12,Age,age,A_structural,level,years,-0.004454,0.000592,,,***,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3356.0,0.67,se,Othello station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,-0.44539999999999996,0.059199999999999996,100*b/1 (per year),reported,-0.12898010305657376,0.017143291650087936,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.523648648648648,3346.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c5,3,5,12,Age,age,A_structural,level,years,-0.00438,0.000465,,,***,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4454.0,0.57,se,Rainier Beach station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,-0.438,0.0465,100*b/1 (per year),reported,-0.13990766489389198,0.014853210999009077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.419354838709678,4444.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c6,3,6,12,Age,age,A_structural,level,years,-0.006907,0.000462,,,***,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3484.0,0.61,se,Tukwila/Intl Blvd station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,-0.6907,0.0462,100*b/1 (per year),reported,-0.24586282205121046,0.016445435614254992,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.95021645021645,3474.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c7,3,7,12,Age,age,A_structural,level,years,-0.006782,0.000571,,,***,,,high,Quadratic in age (Age2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2905.0,0.7,se,SeaTac Airport station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,-0.6782,0.0571,100*b/1 (per year),reported,-0.21555871456094564,0.018148632558876433,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.87740805604203,2895.0,years,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c2,3,2,12,Waterfront,waterfront,C_exterior,binary,binary,0.6472,0.0771,,,***,,,high,Not estimable for Beacon Hill (no waterfront lots),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2264.0,0.7,se,Mount Baker station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,90.45157846823066,14.727524936057584,100*(exp(b - se^2/2) - 1),reported,0.1741095943390026,0.020741424171101825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.394293125810636,2254.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c3,3,3,12,Waterfront,waterfront,C_exterior,binary,binary,0.2623,0.0283,,,***,,,high,Not estimable for Beacon Hill (no waterfront lots),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4697.0,0.55,se,Columbia City station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,29.93960180411983,3.6787635786209285,100*(exp(b - se^2/2) - 1),reported,0.13415918537468924,0.014474666207028995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.268551236749117,4687.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c4,3,4,12,Waterfront,waterfront,C_exterior,binary,binary,0.204,0.0276,,,***,,,high,Not estimable for Beacon Hill (no waterfront lots),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3356.0,0.67,se,Othello station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,22.583116995350583,3.384582903539141,100*(exp(b - se^2/2) - 1),reported,0.12674805579101378,0.017148266371725392,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.391304347826087,3346.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c5,3,5,12,Waterfront,waterfront,C_exterior,binary,binary,0.4644,0.0227,,,***,,,high,Not estimable for Beacon Hill (no waterfront lots),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4454.0,0.57,se,Rainier Beach station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,59.064939121767864,3.6117045358153734,100*(exp(b - se^2/2) - 1),reported,0.2933829991137706,0.014340641860212304,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.45814977973568,4444.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c6,3,6,12,Waterfront,waterfront,C_exterior,binary,binary,0.0394,0.0584,,,,,,high,Not estimable for Beacon Hill (no waterfront lots),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3484.0,0.61,se,Tukwila/Intl Blvd station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,3.8414177405534433,6.074689014212275,100*(exp(b - se^2/2) - 1),reported,0.011445638340214922,0.016965108605800798,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6746575342465753,3474.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c7,3,7,12,Waterfront,waterfront,C_exterior,binary,binary,0.0471,0.0091,,,***,,,high,Not estimable for Beacon Hill (no waterfront lots),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2905.0,0.7,se,SeaTac Airport station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,4.818342558811017,0.953886412134427,100*(exp(b - se^2/2) - 1),reported,0.09575359282742424,0.018500163370054362,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.175824175824176,2895.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c1,3,1,12,View,view,E_environment,binary,binary (outstanding view),0.0611,0.02,,,**,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1451.0,0.42,se,Beacon Hill station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,6.279262961009402,2.1260104187865716,100*(exp(b - se^2/2) - 1),reported,0.08021901895830995,0.0262582713447823,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.055,1441.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c2,3,2,12,View,view,E_environment,binary,binary (outstanding view),0.1537,0.0162,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2264.0,0.7,se,Mount Baker station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,16.59879810175471,1.8891484070387803,100*(exp(b - se^2/2) - 1),reported,0.19596504228002876,0.020654740955995222,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.487654320987655,2254.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c3,3,3,12,View,view,E_environment,binary,binary (outstanding view),0.2521,0.0115,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4697.0,0.55,se,Columbia City station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,28.66396214638065,1.4797334088200282,100*(exp(b - se^2/2) - 1),reported,0.30495245233725593,0.013910960737320281,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.921739130434784,4687.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c4,3,4,12,View,view,E_environment,binary,binary (outstanding view),0.2952,0.0145,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3356.0,0.67,se,Othello station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,34.32537938446669,1.9479227656923814,100*(exp(b - se^2/2) - 1),reported,0.3319915945870396,0.016307175208374235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.358620689655172,3346.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,True
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c5,3,5,12,View,view,E_environment,binary,binary (outstanding view),0.2219,0.0102,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4454.0,0.57,se,Rainier Beach station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,24.838158446998193,1.2734154575085288,100*(exp(b - se^2/2) - 1),reported,0.31023789744752206,0.014260597359011832,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.75490196078431,4444.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c6,3,6,12,View,view,E_environment,binary,binary (outstanding view),0.062,0.0144,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3484.0,0.61,se,Tukwila/Intl Blvd station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,6.385203883048884,1.5321057764083685,100*(exp(b - se^2/2) - 1),reported,0.07285487866809066,0.016921133110008153,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.305555555555555,3474.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c7,3,7,12,View,view,E_environment,binary,binary (outstanding view),0.1446,0.013,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2905.0,0.7,se,SeaTac Airport station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,15.547960475882515,1.502250420983975,100*(exp(b - se^2/2) - 1),reported,0.20244792056542787,0.01820071208402878,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.123076923076924,2895.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c1,3,1,12,Lot (acres),lot_size,A_structural,level,acres,0.588,0.6628,,,,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1451.0,0.42,se,Beacon Hill station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.014529796430269321,0.01637814468364372,100*b/4046.86 (X per acre->m2),reported,0.0233638424819003,0.02633597754592435,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8871454435727218,1441.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c2,3,2,12,Lot (acres),lot_size,A_structural,level,acres,1.4153,0.2061,,,***,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2264.0,0.7,se,Mount Baker station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.03497282463904791,0.005092841912038277,100*b/4046.86 (X per acre->m2),reported,0.14315200741617176,0.020846201320195715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.867054827753518,2254.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c3,3,3,12,Lot (acres),lot_size,A_structural,level,acres,0.867,0.1091,,,***,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4697.0,0.55,se,Columbia City station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.021424036573203235,0.002695919711806774,100*b/4046.86 (X per acre->m2),reported,0.11530299358824118,0.01450929250343381,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.9468377635197065,4687.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c4,3,4,12,Lot (acres),lot_size,A_structural,level,acres,0.9429,0.0931,,,***,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3356.0,0.67,se,Othello station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.023299566418539017,0.0023005511014593093,100*b/4046.86 (X per acre->m2),reported,0.17246312850958617,0.017028653371770574,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.12781954887218,3346.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c5,3,5,12,Lot (acres),lot_size,A_structural,level,acres,-0.0913,0.0417,,,*,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4454.0,0.57,se,Rainier Beach station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,-0.0022560721327952197,0.0010304294407180795,100*b/4046.86 (X per acre->m2),reported,-0.03282566929065133,0.014992666039651265,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1894484412470026,4444.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c6,3,6,12,Lot (acres),lot_size,A_structural,level,acres,0.2292,0.0313,,,***,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3484.0,0.61,se,Tukwila/Intl Blvd station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.005663655343227429,0.0007734398439922276,100*b/4046.86 (X per acre->m2),reported,0.12329040329785543,0.01683677846083279,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.322683706070287,3474.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c7,3,7,12,Lot (acres),lot_size,A_structural,level,acres,0.578,0.0567,,,***,,,high,Quadratic in lot size (Lot2 also included),log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2905.0,0.7,se,SeaTac Airport station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,semi_elasticity,0.014282691048802155,0.0014010875129188275,100*b/4046.86 (X per acre->m2),reported,0.18614977053984294,0.018260712784790824,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.194003527336859,2895.0,acre,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c1,3,1,12,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.0829,0.0156,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,1451.0,0.42,se,Beacon Hill station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,8.63009706555773,1.6948357292878615,100*(exp(b - se^2/2) - 1),reported,0.1386384220999339,0.026088774243172116,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.314102564102565,1441.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c2,3,2,12,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.1489,0.0168,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2264.0,0.7,se,Mount Baker station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,16.03931614753149,1.9497356385584046,100*(exp(b - se^2/2) - 1),reported,0.18351413462721897,0.020705422845784274,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.863095238095239,2254.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c3,3,3,12,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.066,0.0099,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4697.0,0.55,se,Columbia City station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,6.817436999836546,1.0575444499943334,100*(exp(b - se^2/2) - 1),reported,0.09691965698120014,0.014537948547180022,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.666666666666666,4687.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c4,3,4,12,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.0415,0.012,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3356.0,0.67,se,Othello station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,4.229811368558645,1.2508477942217682,100*(exp(b - se^2/2) - 1),reported,0.059680037439536905,0.017256878295769707,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4583333333333335,3346.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c5,3,5,12,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.0823,0.0092,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,4454.0,0.57,se,Rainier Beach station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,8.573554612230193,0.9989189757890629,100*(exp(b - se^2/2) - 1),reported,0.1329993518509124,0.014867485261584379,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.945652173913043,4444.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c6,3,6,12,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.0452,0.0082,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,3484.0,0.61,se,Tukwila/Intl Blvd station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,4.6201912503082365,0.8579144108501736,100*(exp(b - se^2/2) - 1),reported,0.09311480106198257,0.01689250815726233,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.512195121951219,3474.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a,8c46154fbaf164447e17b77d9874009c161a116a:T3-c7,3,7,12,Detached Garage,garage,A_structural,binary,binary (garage is detached),0.0729,0.01,,,***,,,high,,log of real relative sale price (sale price deflated by Seattle metro Case-Shiller index),log,OLS,2905.0,0.7,se,SeaTac Airport station neighbourhood; sales 1992-2003 (before construction) vs 2010-2016 (after opening); DiD,pct_premium,7.5569189435529704,1.0756229692394854,100*(exp(b - se^2/2) - 1),reported,0.13426201930388304,0.018417286598612213,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.290000000000001,2895.0,binary,,2018.0,United States,North America,High income,1992.0,2016.0,single_family,transaction,journal,False,False,clustered,,2004.0,ols,journal,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c1,3,1,38,Age,age,A_structural,level,years,-0.013,0.001,,,***,,,high,,Ln(sale price),log,OLS,40851.0,0.76,se,"full sample hedonic, no uniqueness control",semi_elasticity,-1.3,0.1,100*b/1 (per year),reported,-0.06419459565029369,0.004938045819253361,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.0,40841.0,years,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c2,3,2,38,Age,age,A_structural,level,years,-0.012,0.001,,,***,,,high,,Ln(sale price),log,OLS,40851.0,0.769,se,full sample hedonic with uniqueness control,semi_elasticity,-1.2,0.1,100*b/1 (per year),reported,-0.05927461970912663,0.004939551642427219,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.0,40841.0,years,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c3,3,3,38,Age,age,A_structural,level,years,-0.014,0.002,,,***,,,high,,Ln(sale price),log,FE_panel,7317.0,0.956,se,"repeat-sale sample with property FE, no uniqueness control",semi_elasticity,-1.4000000000000001,0.2,100*b/1 (per year),reported,-0.08161635209175691,0.011659478870250987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,7307.0,years,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c4,3,4,38,Age,age,A_structural,level,years,-0.014,0.002,,,***,,,high,,Ln(sale price),log,FE_panel,7317.0,0.958,se,"repeat-sale sample with property FE, with uniqueness control",semi_elasticity,-1.4000000000000001,0.2,100*b/1 (per year),reported,-0.08161635209175691,0.011659478870250987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,7307.0,years,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c1,3,1,38,Bed,bedrooms,A_structural,level,count,-0.047,0.021,,,**,,,high,,Ln(sale price),log,OLS,40851.0,0.76,se,"full sample hedonic, no uniqueness control",semi_elasticity,-4.7,2.1,100*b/1 (per unit count),reported,-0.011073980348086692,0.004947948666166394,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.238095238095238,40841.0,count,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,True
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c2,3,2,38,Bed,bedrooms,A_structural,level,count,-0.042,0.02,,,**,,,high,,Ln(sale price),log,OLS,40851.0,0.769,se,full sample hedonic with uniqueness control,semi_elasticity,-4.2,2.0,100*b/1 (per unit count),reported,-0.010390768397624072,0.004947984951249558,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1,40841.0,count,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c3,3,3,38,Bed,bedrooms,A_structural,level,count,-0.014,0.021,,,,,,high,,Ln(sale price),log,FE_panel,7317.0,0.956,se,"repeat-sale sample with property FE, no uniqueness control",semi_elasticity,-1.4000000000000001,2.1,100*b/1 (per unit count),reported,-0.007798767619131272,0.011698151428696908,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6666666666666666,7307.0,count,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c4,3,4,38,Bed,bedrooms,A_structural,level,count,-0.013,0.021,,,,,,high,,Ln(sale price),log,FE_panel,7317.0,0.958,se,"repeat-sale sample with property FE, with uniqueness control",semi_elasticity,-1.3,2.1,100*b/1 (per unit count),reported,-0.007241743126266714,0.011698200434738541,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.619047619047619,7307.0,count,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c1,3,1,38,Bath,bathrooms,A_structural,level,count,0.247,0.018,,,***,,,high,,Ln(sale price),log,OLS,40851.0,0.76,se,"full sample hedonic, no uniqueness control",semi_elasticity,24.7,1.7999999999999998,100*b/1 (per unit count),reported,0.0677450234828826,0.004936884302396302,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.722222222222223,40841.0,count,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c2,3,2,38,Bath,bathrooms,A_structural,level,count,0.245,0.016,,,***,,,high,,Ln(sale price),log,OLS,40851.0,0.769,se,full sample hedonic with uniqueness control,semi_elasticity,24.5,1.6,100*b/1 (per unit count),reported,0.07555353987036179,0.004934108726227709,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.3125,40841.0,count,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c3,3,3,38,Bath,bathrooms,A_structural,level,count,0.32,0.035,,,***,,,high,,Ln(sale price),log,FE_panel,7317.0,0.956,se,"repeat-sale sample with property FE, no uniqueness control",semi_elasticity,32.0,3.5000000000000004,100*b/1 (per unit count),reported,0.10635118295801178,0.011632160636032542,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.142857142857142,7307.0,count,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c4,3,4,38,Bath,bathrooms,A_structural,level,count,0.315,0.033,,,***,,,high,,Ln(sale price),log,FE_panel,7317.0,0.958,se,"repeat-sale sample with property FE, with uniqueness control",semi_elasticity,31.5,3.3000000000000003,100*b/1 (per unit count),reported,0.11097778546723713,0.011626244191805796,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.545454545454545,7307.0,count,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c1,3,1,38,Ranch,dwelling_type,A_structural,binary,binary,-0.26,0.021,,,***,,,high,ranch-style house dummy,Ln(sale price),log,OLS,40851.0,0.76,se,"full sample hedonic, no uniqueness control",pct_premium,-22.91184123281206,1.6192083301874893,100*(exp(b - se^2/2) - 1),reported,-0.06114942524825239,0.004938992039281924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.380952380952381,40841.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c2,3,2,38,Ranch,dwelling_type,A_structural,binary,binary,-0.244,0.02,,,***,,,high,ranch-style house dummy,Ln(sale price),log,OLS,40851.0,0.769,se,full sample hedonic with uniqueness control,pct_premium,-21.666904759528194,1.5669752685257252,100*(exp(b - se^2/2) - 1),reported,-0.06025897209183984,0.004939260007527856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.2,40841.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c3,3,3,38,Ranch,dwelling_type,A_structural,binary,binary,-0.036,0.042,,,,,,high,ranch-style house dummy,Ln(sale price),log,FE_panel,7317.0,0.956,se,"repeat-sale sample with property FE, no uniqueness control",pct_premium,-3.6210144157598156,4.051489232629117,100*(exp(b - se^2/2) - 1),reported,-0.010026787810405125,0.011697919112139315,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.857142857142857,7307.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c4,3,4,38,Ranch,dwelling_type,A_structural,binary,binary,-0.038,0.041,,,,,,high,ranch-style house dummy,Ln(sale price),log,FE_panel,7317.0,0.958,se,"repeat-sale sample with property FE, with uniqueness control",pct_premium,-3.809587938128478,3.947123057653918,100*(exp(b - se^2/2) - 1),reported,-0.010841881591019517,0.011697819611363163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9268292682926829,7307.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c1,3,1,38,Renovated,renovation,A_structural,binary,binary,0.253,0.032,,,***,,,high,,Ln(sale price),log,OLS,40851.0,0.76,se,"full sample hedonic, no uniqueness control",pct_premium,28.72240493735221,4.121226485870817,100*(exp(b - se^2/2) - 1),reported,0.03909221338527812,0.004944469677189329,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.90625,40841.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c2,3,2,38,Renovated,renovation,A_structural,binary,binary,0.225,0.027,,,***,,,high,,Ln(sale price),log,OLS,40851.0,0.769,se,full sample hedonic with uniqueness control,pct_premium,25.186632774366014,3.3812713337180336,100*(exp(b - se^2/2) - 1),reported,0.04120042112451108,0.004944050534941329,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.333333333333334,40841.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c3,3,3,38,Renovated,renovation,A_structural,binary,binary,0.359,0.042,,,***,,,high,,Ln(sale price),log,FE_panel,7317.0,0.956,se,"repeat-sale sample with property FE, no uniqueness control",pct_premium,43.06344253824079,6.013966566600967,100*(exp(b - se^2/2) - 1),reported,0.09949818512010357,0.011640456197895126,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.547619047619047,7307.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c4,3,4,38,Renovated,renovation,A_structural,binary,binary,0.345,0.038,,,***,,,high,,Ln(sale price),log,FE_panel,7317.0,0.958,se,"repeat-sale sample with property FE, with uniqueness control",pct_premium,41.09708308809805,5.365561694737104,100*(exp(b - se^2/2) - 1),reported,0.1056160956007964,0.01163307719660946,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.078947368421051,7307.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c1,3,1,38,Sqft,living_area,A_structural,level,100 sqft,0.009,0.001,,,***,,,high,square footage in hundreds (Table 6: Sqft (100)),Ln(sale price),log,OLS,40851.0,0.76,se,"full sample hedonic, no uniqueness control",semi_elasticity,0.09687519375038749,0.010763910416709722,100*b/9.2903 (X per 100sqft->m2),reported,0.04449017191579412,0.004943352435088236,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.0,40841.0,100sqft,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c2,3,2,38,Sqft,living_area,A_structural,level,100 sqft,0.009,0.001,,,***,,,high,square footage in hundreds (Table 6: Sqft (100)),Ln(sale price),log,OLS,40851.0,0.769,se,full sample hedonic with uniqueness control,semi_elasticity,0.09687519375038749,0.010763910416709722,100*b/9.2903 (X per 100sqft->m2),reported,0.04449017191579412,0.004943352435088236,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.0,40841.0,100sqft,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c3,3,3,38,Sqft,living_area,A_structural,level,100 sqft,-0.001,0.001,,,,,,high,square footage in hundreds (Table 6: Sqft (100)),Ln(sale price),log,FE_panel,7317.0,0.956,se,"repeat-sale sample with property FE, no uniqueness control",semi_elasticity,-0.010763910416709722,0.010763910416709722,100*b/9.2903 (X per 100sqft->m2),reported,-0.011697706772393275,0.011697706772393273,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,7307.0,100sqft,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,True
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c4,3,4,38,Sqft,living_area,A_structural,level,100 sqft,-0.001,0.001,,,,,,high,square footage in hundreds (Table 6: Sqft (100)),Ln(sale price),log,FE_panel,7317.0,0.958,se,"repeat-sale sample with property FE, with uniqueness control",semi_elasticity,-0.010763910416709722,0.010763910416709722,100*b/9.2903 (X per 100sqft->m2),reported,-0.011697706772393275,0.011697706772393273,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,7307.0,100sqft,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,True
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c1,3,1,38,Large Lot,lot_size,A_structural,binary,binary,0.012,0.028,,,,,,high,large lot indicator,Ln(sale price),log,OLS,40851.0,0.76,se,"full sample hedonic, no uniqueness control",pct_premium,1.1675634278220715,2.8338024088250178,100*(exp(b - se^2/2) - 1),reported,0.0021206746963994072,0.004948240958265284,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.42857142857142855,40841.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c2,3,2,38,Large Lot,lot_size,A_structural,binary,binary,0.004,0.025,,,,,,high,large lot indicator,Ln(sale price),log,OLS,40851.0,0.769,se,full sample hedonic with uniqueness control,pct_premium,0.3694307192727564,2.510020026693355,100*(exp(b - se^2/2) - 1),reported,0.0007917200854776199,0.004948250534235124,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.16,40841.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c3,3,3,38,Large Lot,lot_size,A_structural,binary,binary,0.066,0.07,,,,,,high,large lot indicator,Ln(sale price),log,FE_panel,7317.0,0.956,se,"repeat-sale sample with property FE, no uniqueness control",pct_premium,6.561276510772851,7.477587020161954,100*(exp(b - se^2/2) - 1),reported,0.011029350162602938,0.011697795627003118,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9428571428571428,7307.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c4,3,4,38,Large Lot,lot_size,A_structural,binary,binary,0.077,0.073,,,,,,high,large lot indicator,Ln(sale price),log,FE_panel,7317.0,0.958,se,"repeat-sale sample with property FE, with uniqueness control",pct_premium,7.716813478906337,7.884307157665983,100*(exp(b - se^2/2) - 1),reported,0.012338581959024365,0.01169761666245167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0547945205479452,7307.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c1,3,1,38,Pool,pool,C_exterior,binary,binary,0.049,0.018,,,***,,,high,,Ln(sale price),log,OLS,40851.0,0.76,se,"full sample hedonic, no uniqueness control",pct_premium,5.005022882345567,1.8903966313320504,100*(exp(b - se^2/2) - 1),reported,0.013469019883144832,0.004947803222379734,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7222222222222223,40841.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c2,3,2,38,Pool,pool,C_exterior,binary,binary,0.051,0.016,,,***,,,high,,Ln(sale price),log,OLS,40851.0,0.769,se,full sample hedonic with uniqueness control,pct_premium,5.218820457312501,1.683716629253126,100*(exp(b - se^2/2) - 1),reported,0.015770591990896973,0.004947636703026502,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1874999999999996,40841.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,ols,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c3,3,3,38,Pool,pool,C_exterior,binary,binary,0.026,0.056,,,,,,high,,Ln(sale price),log,FE_panel,7317.0,0.956,se,"repeat-sale sample with property FE, no uniqueness control",pct_premium,2.4732906900293283,5.747509311451275,100*(exp(b - se^2/2) - 1),reported,0.005431369653034972,0.011698334637306095,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.46428571428571425,7307.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7,8d5f6b09f9058fc5a131a22d58a856d18ce849c7:T3-c4,3,4,38,Pool,pool,C_exterior,binary,binary,0.01,0.057,,,,,,high,,Ln(sale price),log,FE_panel,7317.0,0.958,se,"repeat-sale sample with property FE, with uniqueness control",pct_premium,0.8410672627664262,5.757285952379757,100*(exp(b - se^2/2) - 1),reported,0.002052365359996223,0.011698482551978471,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.17543859649122806,7307.0,binary,,2021.0,United States,North America,High income,2010.0,2016.0,single_family,transaction,working_paper,True,True,clustered,NLP text analysis of listing descriptions (uniqueness score),2013.0,panel,other,True,True,False
8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2:T3-c1,3,Estimate,34,Secchi,water_quality,E_environment,log,m (Secchi depth),0.231,0.034,,,***,,,high,"ln(summer mean Secchi depth, metres); main effect = elasticity for a lake with mean log lake area (interactions demeaned); excluded categories MN and Ecoregion 8.1","ln(sale price, 2020 $)",log,OLS,485860.0,,se,"National baseline model: summer-mean Secchi within +/-5 years, lot size/building size/building age controls, 150 m lakefront buffer, properties within 1,000 m of lake, census tract x year FE, quarter FE; SE clustered by tract",elasticity,0.231,0.034,b (log-log),reported,0.009746783723741185,0.0014345915437541138,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.794117647058823,485850.0,m,,2023.0,United States,North America,High income,,,single_family,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2:T3-c1,3,Estimate,34,<150 m,water_proximity,E_environment,binary,binary,0.124,0.009,,,***,,,high,Lakefront buffer dummy: property within 150 m of the lake =1,"ln(sale price, 2020 $)",log,OLS,485860.0,,se,"National baseline model: summer-mean Secchi within +/-5 years, lot size/building size/building age controls, 150 m lakefront buffer, properties within 1,000 m of lake, census tract x year FE, quarter FE; SE clustered by tract",pct_premium,13.197002528478174,1.0188142838992575,100*(exp(b - se^2/2) - 1),reported,0.019762562064385022,0.0014343795046731064,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.777777777777779,485850.0,binary,,2023.0,United States,North America,High income,,,single_family,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2:T3-c1,3,Estimate,34,Lake Distance,water_proximity,E_environment,log,m,-0.095,0.005,,,***,,,high,"ln(distance from property to nearest lake, metres)","ln(sale price, 2020 $)",log,OLS,485860.0,,se,"National baseline model: summer-mean Secchi within +/-5 years, lot size/building size/building age controls, 150 m lakefront buffer, properties within 1,000 m of lake, census tract x year FE, quarter FE; SE clustered by tract",elasticity,-0.095,0.005,b (log-log),reported,-0.027248412856838294,0.0014341269924651734,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-19.0,485850.0,m,,2023.0,United States,North America,High income,,,single_family,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2:T3-c1,3,Estimate,34,Median Income,income,F_neighbourhood,log,"currency (2016 $, block group median)",0.131,0.014,,,***,,,high,ln(block-group median income),"ln(sale price, 2020 $)",log,OLS,485860.0,,se,"National baseline model: summer-mean Secchi within +/-5 years, lot size/building size/building age controls, 150 m lakefront buffer, properties within 1,000 m of lake, census tract x year FE, quarter FE; SE clustered by tract",elasticity,0.131,0.014,b (log-log),reported,0.013423106235694388,0.0014345304374024537,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.357142857142858,485850.0,currency,,2023.0,United States,North America,High income,,,single_family,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2:T3-c1,3,Estimate,34,Lot Size,lot_size,A_structural,log,sqft,0.101,0.004,,,***,,,high,"ln(lot size, sq ft)","ln(sale price, 2020 $)",log,OLS,485860.0,,se,"National baseline model: summer-mean Secchi within +/-5 years, lot size/building size/building age controls, 150 m lakefront buffer, properties within 1,000 m of lake, census tract x year FE, quarter FE; SE clustered by tract",elasticity,0.101,0.004,b (log-log),reported,0.03620141213025096,0.0014337192922871667,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.25,485850.0,sqft,,2023.0,United States,North America,High income,,,single_family,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2:T3-c1,3,Estimate,34,Building Age,age,A_structural,log,years,-0.125,0.003,,,***,,,high,ln(building age in years),"ln(sale price, 2020 $)",log,OLS,485860.0,,se,"National baseline model: summer-mean Secchi within +/-5 years, lot size/building size/building age controls, 150 m lakefront buffer, properties within 1,000 m of lake, census tract x year FE, quarter FE; SE clustered by tract",elasticity,-0.125,0.003,b (log-log),reported,-0.059670969650351464,0.0014321032716084353,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-41.666666666666664,485850.0,years,,2023.0,United States,North America,High income,,,single_family,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2:T3-c1,3,Estimate,34,Building Size,living_area,A_structural,log,sqft,0.547,0.01,,,***,,,high,"ln(building size, sq ft)","ln(sale price, 2020 $)",log,OLS,485860.0,,se,"National baseline model: summer-mean Secchi within +/-5 years, lot size/building size/building age controls, 150 m lakefront buffer, properties within 1,000 m of lake, census tract x year FE, quarter FE; SE clustered by tract",elasticity,0.547,0.01,b (log-log),reported,0.07823535007665969,0.00143026234143802,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),54.7,485850.0,sqft,,2023.0,United States,North America,High income,,,single_family,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2:T3-c1,3,Estimate,34,Quarter 2,transaction_timing,G_market,dummy,binary,0.044,0.002,,,***,,,high,Sale quarter 2 dummy (reference quarter 1),"ln(sale price, 2020 $)",log,OLS,485860.0,,se,"National baseline model: summer-mean Secchi within +/-5 years, lot size/building size/building age controls, 150 m lakefront buffer, properties within 1,000 m of lake, census tract x year FE, quarter FE; SE clustered by tract",pct_premium,4.4980264925823965,0.20899647097768878,100*(exp(b - se^2/2) - 1),reported,0.03154680378516759,0.0014339456265985268,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,485850.0,binary,,2023.0,United States,North America,High income,,,single_family,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2:T3-c1,3,Estimate,34,Quarter 3,transaction_timing,G_market,dummy,binary,0.05,0.002,,,***,,,high,Sale quarter 3 dummy (reference quarter 1),"ln(sale price, 2020 $)",log,OLS,485860.0,,se,"National baseline model: summer-mean Secchi within +/-5 years, lot size/building size/building age controls, 150 m lakefront buffer, properties within 1,000 m of lake, census tract x year FE, quarter FE; SE clustered by tract",pct_premium,5.126899383593386,0.21025421927520482,100*(exp(b - se^2/2) - 1),reported,0.03584344510029118,0.0014337378040116472,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.0,485850.0,binary,,2023.0,United States,North America,High income,,,single_family,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2,8fb41eefcd89b6d6746d9ab5af9f6f61e2da05b2:T3-c1,3,Estimate,34,Quarter 4,transaction_timing,G_market,dummy,binary,0.015,0.002,,,***,,,high,Sale quarter 4 dummy (reference quarter 1),"ln(sale price, 2020 $)",log,OLS,485860.0,,se,"National baseline model: summer-mean Secchi within +/-5 years, lot size/building size/building age controls, 150 m lakefront buffer, properties within 1,000 m of lake, census tract x year FE, quarter FE; SE clustered by tract",pct_premium,1.511103439161987,0.20302261292314377,100*(exp(b - se^2/2) - 1),reported,0.01075932486637363,0.0014345766488498173,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.5,485850.0,binary,,2023.0,United States,North America,High income,,,single_family,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T2-c1,2,1,10,Grocery store distance 0-399.9 meters,commercial_distance,D_location,dummy,binary (within 0-399.9 m of a grocery store site; ref > 800 m),0.076,0.028,,,***,,,high,Distance-band dummy (pre- and post-opening location effect); clustered (block group) robust SE,log sale price,log,OLS,33849.0,0.589,se,"All observations; 800 m split into two buffers (0-399.9, 400-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,7.853970371623564,3.021095207640395,100*(exp(b - se^2/2) - 1),reported,0.014753651786630696,0.0054355559213902565,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.714285714285714,33839.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T2-c2,2,2,10,Grocery store distance 0-399.9 meters,commercial_distance,D_location,dummy,binary (within 0-399.9 m of a grocery store site; ref > 800 m),0.073,0.027,,,***,,,high,Distance-band dummy (pre- and post-opening location effect); clustered (block group) robust SE,log sale price,log,OLS,33583.0,0.599,se,"Excludes properties with top 1% prices; 800 m split into two buffers (0-399.9, 400-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,7.533850458623048,2.9044724496696994,100*(exp(b - se^2/2) - 1),reported,0.014754236660817946,0.005457046436192939,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7037037037037037,33573.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T2-c3,2,3,10,Grocery store distance 0-399.9 meters,commercial_distance,D_location,dummy,binary (within 0-399.9 m of a grocery store site; ref > 800 m),0.072,0.027,,,***,,,high,Distance-band dummy (pre- and post-opening location effect); clustered (block group) robust SE,log sale price,log,OLS,32619.0,0.584,se,"Excludes properties with top 5% prices; 800 m split into two buffers (0-399.9, 400-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,7.426370357171819,2.9015694289722966,100*(exp(b - se^2/2) - 1),reported,0.014765652497915996,0.005537119686718498,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6666666666666665,32609.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T2-c1,2,1,10,Grocery store distance 400-800 meters,commercial_distance,D_location,dummy,binary (400-800 m of a grocery store site; ref > 800 m),0.081,0.018,,,***,,,high,Distance-band dummy; clustered (block group) robust SE,log sale price,log,OLS,33849.0,0.589,se,"All observations; 800 m split into two buffers (0-399.9, 400-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,8.419524270986312,1.9518676138201687,100*(exp(b - se^2/2) - 1),reported,0.02445534797416125,0.005434521772035832,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.500000000000001,33839.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T2-c2,2,2,10,Grocery store distance 400-800 meters,commercial_distance,D_location,dummy,binary (400-800 m of a grocery store site; ref > 800 m),0.08,0.018,,,***,,,high,Distance-band dummy; clustered (block group) robust SE,log sale price,log,OLS,33583.0,0.599,se,"Excludes properties with top 1% prices; 800 m split into two buffers (0-399.9, 400-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,8.311158938412056,1.9499167218149254,100*(exp(b - se^2/2) - 1),reported,0.024249047430402546,0.0054560356718405725,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.444444444444445,33573.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T2-c3,2,3,10,Grocery store distance 400-800 meters,commercial_distance,D_location,dummy,binary (400-800 m of a grocery store site; ref > 800 m),0.076,0.017,,,***,,,high,Distance-band dummy; clustered (block group) robust SE,log sale price,log,OLS,32619.0,0.584,se,"Excludes properties with top 5% prices; 800 m split into two buffers (0-399.9, 400-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,7.880667532927976,1.8342363760673828,100*(exp(b - se^2/2) - 1),reported,0.02474929777956894,0.005536027134903579,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.470588235294117,32609.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T3-c1,3,1,11,Grocery store distance 0-199.9 meters,commercial_distance,D_location,dummy,binary (0-199.9 m; ref > 800 m),0.10366,0.06349,,,,,,high,Distance-ring dummy; clustered (block group) robust SE,log sale price,log,OLS,33849.0,0.58925,se,"All observations; four 200 m rings (0-199.9, 200-399.9, 400-599.9, 600-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,10.698987788569191,7.042458445287401,100*(exp(b - se^2/2) - 1),reported,0.00887523807946204,0.0054359334908840925,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6326980626870373,33839.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T3-c2,3,2,11,Grocery store distance 0-199.9 meters,commercial_distance,D_location,dummy,binary (0-199.9 m; ref > 800 m),0.10062,0.06409,,,,,,high,Distance-ring dummy; clustered (block group) robust SE,log sale price,log,OLS,33583.0,0.59944,se,"Excludes properties with top 1% prices; four 200 m rings (0-199.9, 200-399.9, 400-599.9, 600-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,10.358749914002829,7.087433260645231,100*(exp(b - se^2/2) - 1),reported,0.00856807036394695,0.005457440167216855,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.569979716024341,33573.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T3-c3,3,3,11,Grocery store distance 0-199.9 meters,commercial_distance,D_location,dummy,binary (0-199.9 m; ref > 800 m),0.09851,0.06452,,,,,,high,Distance-ring dummy; clustered (block group) robust SE,log sale price,log,OLS,32619.0,0.58413,se,"Excludes properties with top 5% prices; four 200 m rings (0-199.9, 200-399.9, 400-599.9, 600-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,10.123093370813962,7.119946136257979,100*(exp(b - se^2/2) - 1),reported,0.008454768040060666,0.005537525468934261,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5268133911965283,32609.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T3-c1,3,1,11,Grocery store distance 200-399.9 meters,commercial_distance,D_location,dummy,binary (200-399.9 m; ref > 800 m),0.07078,0.0284,,,**,,,high,Distance-ring dummy; clustered (block group) robust SE,log sale price,log,OLS,33849.0,0.58925,se,"All observations; four 200 m rings (0-199.9, 200-399.9, 400-599.9, 600-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,7.291229264990173,3.0482999816958927,100*(exp(b - se^2/2) - 1),reported,0.01354701473481514,0.005435648749205285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4922535211267602,33839.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T3-c2,3,2,11,Grocery store distance 200-399.9 meters,commercial_distance,D_location,dummy,binary (200-399.9 m; ref > 800 m),0.06747,0.02844,,,**,,,high,Distance-ring dummy; clustered (block group) robust SE,log sale price,log,OLS,33583.0,0.59944,se,"Excludes properties with top 1% prices; four 200 m rings (0-199.9, 200-399.9, 400-599.9, 600-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,6.936560829345817,3.0425059817478397,100*(exp(b - se^2/2) - 1),reported,0.012946418562846182,0.005457183102524758,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3723628691983123,33573.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T3-c3,3,3,11,Grocery store distance 200-399.9 meters,commercial_distance,D_location,dummy,binary (200-399.9 m; ref > 800 m),0.06674,0.02763,,,**,,,high,Distance-ring dummy; clustered (block group) robust SE,log sale price,log,OLS,32619.0,0.58413,se,"Excludes properties with top 5% prices; four 200 m rings (0-199.9, 200-399.9, 400-599.9, 600-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,6.860952234607365,2.9536953455630184,100*(exp(b - se^2/2) - 1),reported,0.013375121234434201,0.005537228044762016,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4154904089757507,32609.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T3-c1,3,1,11,Grocery store distance 400-599.9 meters,commercial_distance,D_location,dummy,binary (400-599.9 m; ref > 800 m),0.0749,0.02149,,,***,,,high,Distance-ring dummy; clustered (block group) robust SE,log sale price,log,OLS,33849.0,0.58925,se,"All observations; four 200 m rings (0-199.9, 200-399.9, 400-599.9, 600-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,7.752752719480394,2.316141414528527,100*(exp(b - se^2/2) - 1),reported,0.01894343376999218,0.005435172119053832,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4853420195439737,33839.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T3-c2,3,2,11,Grocery store distance 400-599.9 meters,commercial_distance,D_location,dummy,binary (400-599.9 m; ref > 800 m),0.0705,0.02099,,,***,,,high,Distance-ring dummy; clustered (block group) robust SE,log sale price,log,OLS,33583.0,0.59944,se,"Excludes properties with top 1% prices; four 200 m rings (0-199.9, 200-399.9, 400-599.9, 600-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,7.280821442314478,2.2523205512350666,100*(exp(b - se^2/2) - 1),reported,0.018327728803278546,0.005456723795472578,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3587422582181987,33573.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T3-c3,3,3,11,Grocery store distance 400-599.9 meters,commercial_distance,D_location,dummy,binary (400-599.9 m; ref > 800 m),0.0713,0.02115,,,***,,,high,Distance-ring dummy; clustered (block group) robust SE,log sale price,log,OLS,32619.0,0.58413,se,"Excludes properties with top 5% prices; four 200 m rings (0-199.9, 200-399.9, 400-599.9, 600-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,7.366318484544676,2.271305582187701,100*(exp(b - se^2/2) - 1),reported,0.01866529043380363,0.005536758663042732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3711583924349884,32609.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T3-c1,3,1,11,Grocery store distance 600-800 meters,commercial_distance,D_location,dummy,binary (600-800 m; ref > 800 m),0.0845,0.02107,,,***,,,high,Distance-ring dummy; clustered (block group) robust SE,log sale price,log,OLS,33849.0,0.58925,se,"All observations; four 200 m rings (0-199.9, 200-399.9, 400-599.9, 600-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,8.793132664586324,2.2927801827968324,100*(exp(b - se^2/2) - 1),reported,0.021796172070951393,0.0054348561601768736,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0104413858566685,33839.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T3-c2,3,2,11,Grocery store distance 600-800 meters,commercial_distance,D_location,dummy,binary (600-800 m; ref > 800 m),0.0845,0.02056,,,***,,,high,Distance-ring dummy; clustered (block group) robust SE,log sale price,log,OLS,33583.0,0.59944,se,"Excludes properties with top 1% prices; four 200 m rings (0-199.9, 200-399.9, 400-599.9, 600-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,8.794287580535176,2.237283367741,100*(exp(b - se^2/2) - 1),reported,0.022424837176424125,0.0054562680751157385,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.109922178988327,33573.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06,90decb41b454a38dee63486b408022b766c2dc06:T3-c3,3,3,11,Grocery store distance 600-800 meters,commercial_distance,D_location,dummy,binary (600-800 m; ref > 800 m),0.0788,0.02026,,,***,,,high,Distance-ring dummy; clustered (block group) robust SE,log sale price,log,OLS,32619.0,0.58413,se,"Excludes properties with top 5% prices; four 200 m rings (0-199.9, 200-399.9, 400-599.9, 600-800 m); year FE, housing and neighbourhood controls included (not reported); SE clustered by block group",pct_premium,8.176586514528882,2.192107491171151,100*(exp(b - se^2/2) - 1),reported,0.021533633747108843,0.005536439336502858,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.889437314906219,32609.0,binary,,2017.0,United States,North America,High income,1988.0,2011.0,single_family,transaction,journal,True,False,clustered,,1999.5,ols,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T4-1988,4,1988,12,BATH,bathrooms,A_structural,level,count,0.08929,,,0.02,,,,high,; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,other,260.0,,p,listings in 1988,semi_elasticity,8.929,3.838204981996276,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.1455640394806681,0.06257191415995104,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3263478740408408,250.0,count,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,other,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T4-2005,4,2005,12,REHAB,condition,A_structural,binary,binary,-0.06733,,,0.008,,,,high,=1 if apartment must be remodeled; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,other,207.0,,p,listings in 2005,pct_premium,-6.541459777068381,2.373463818258092,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.18566679430835734,0.0700082606253947,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.652069807902196,197.0,binary,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,other,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T4-2005,4,2005,12,HEAT,heating,A_structural,binary,binary,0.04679,,,0.06,,,,high,=1 if central heating; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,other,207.0,,p,listings in 2005,pct_premium,4.75777010003946,2.606949052335213,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.13281388079565434,0.07061587205531039,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.880793608151251,197.0,binary,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,other,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T4-2005,4,2005,12,FLOOR,floor_level,A_structural,binary,binary,-0.1056,,,0.059,,,,high,=1 if apartment on a low floor; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,other,207.0,,p,listings in 2005,pct_premium,-10.162157016370067,5.032177599188474,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.13332714827111183,0.07061096216119284,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8881933369885062,197.0,binary,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,other,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T4-2005,4,2005,12,SPORT,recreation_private,C_exterior,binary,binary,0.1278,,,0.011,,,,high,=1 if complex has sports facilities; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,other,207.0,,p,listings in 2005,pct_premium,13.489131424805855,5.711349895112377,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.1782582860176834,0.07010593809132837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.542698819399048,197.0,binary,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,other,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T6-1988,6,1988,14,BATH,bathrooms,A_structural,level,count,0.1269,,,0.004,,,,high,; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,OLS,260.0,0.8176,p,listings in 1988,semi_elasticity,12.690000000000001,4.409064239728263,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.17908804655265503,0.06222306554910177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.878161739095483,250.0,count,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,ols,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T6-1995,6,1995,14,BATH,bathrooms,A_structural,level,count,0.09536,,,0.002,,,,high,; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,OLS,293.0,0.9234,p,listings in 1995,semi_elasticity,9.536,3.0858521480624743,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.18067223701239754,0.05846558417365346,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.090232306167813,283.0,count,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,ols,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T6-2005,6,2005,14,AGE,age,A_structural,level,years,-0.006583,,,0.001,,,,high,age of apartment in years adjusted for major rehabilitation; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,OLS,207.0,0.7745,p,listings in 2005,semi_elasticity,-0.6583,0.20005915578796496,100*b/1 (per year),|b/z(p)| (two-sided normal),-0.22825160886749504,0.06936628311905792,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,197.0,years,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,ols,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T6-2005,6,2005,14,BATH,bathrooms,A_structural,level,count,0.1107,,,0.002,,,,high,; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,OLS,207.0,0.7745,p,listings in 2005,semi_elasticity,11.07,3.582254957954236,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.21502007891332287,0.06958055499069214,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0902323061678127,197.0,count,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,ols,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T6-2005,6,2005,14,REHAB,condition,A_structural,binary,binary,-0.06925,,,0.048,,,,high,=1 if apartment must be remodeled; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,OLS,207.0,0.7745,p,listings in 2005,pct_premium,-6.747866232221423,3.2678137000642917,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.13950405581764838,0.07055036068615331,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9773684281819468,197.0,binary,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,ols,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T6-2005,6,2005,14,HEAT,heating,A_structural,binary,binary,0.07201,,,0.053,,,,high,=1 if central heating; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,OLS,207.0,0.7745,p,listings in 2005,pct_premium,7.392212591811886,3.9994763710419585,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.13656582167783368,0.07057953631142908,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9349209248873929,197.0,binary,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,ols,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T6-2005,6,2005,14,FLOOR,floor_level,A_structural,binary,binary,-0.1482,,,0.079,,,,high,=1 if apartment on a low floor; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,OLS,207.0,0.7745,p,listings in 2005,pct_premium,-14.080491199404154,7.275002649581315,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.12417808381232374,0.0706955940836923,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.756518004011915,197.0,binary,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,ols,journal,True,True,False
91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,91a343b71c11d4139d2606d6c4d1c5fc64cbc6c3:T6-2005,6,2005,14,SPORT,recreation_private,C_exterior,binary,binary,0.1376,,,0.041,,,,high,=1 if complex has sports facilities; only p-value printed (no SE),log listing price (PRICE in 1000 euros),log,OLS,207.0,0.7745,p,listings in 2005,pct_premium,14.4918018527753,7.726740649944538,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.14407642339463456,0.0705036984385339,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0435300074398564,197.0,binary,,2019.0,Spain,Europe,High income,1988.0,2005.0,condo_apartment,listing,journal,False,False,unknown,,1996.5,ols,journal,True,True,True
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Number of rooms,bedrooms,A_structural,level,count,0.0182,,4.9,,,,,high,Total number of rooms,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",semi_elasticity,1.82,0.37142857142857144,100*b/1 (per unit count),|b/t|,0.06726854714404812,0.013728274927356758,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.9,5282.0,count,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Number of bathrooms,bathrooms,A_structural,level,count,0.1071,,15.9,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",semi_elasticity,10.71,0.6735849056603773,100*b/1 (per unit count),|b/t|,0.21372029543539323,0.013441528014804605,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.9,5282.0,count,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,House with garden,garden,C_exterior,binary,binary,0.0193,,2.2,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,1.9448219478356954,0.8943685347867841,100*(exp(b - se^2/2) - 1),|b/t|,0.030256911657151206,0.013753141662341456,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,House with courtyard,terrace_balcony,C_exterior,binary,binary,0.0269,,1.2,,,,,high,Courtyard (patio),"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,2.700699962590636,2.302785867760399,100*(exp(b - se^2/2) - 1),|b/t|,0.016509079394883736,0.013757566162403114,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,House with garage,garage,A_structural,binary,binary,0.0631,,6.7,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,6.508611120190966,1.0031330479235536,100*(exp(b - se^2/2) - 1),|b/t|,0.09179899747248786,0.01370134290634147,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.7,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,House with terrace,terrace_balcony,C_exterior,binary,binary,-0.0139,,-1.4,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,-1.3852447752106034,0.9791519006697407,100*(exp(b - se^2/2) - 1),|b/t|,-0.019259644876568793,0.013756889197549138,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Parks in neighborhood,green_space,E_environment,binary,binary,0.0722,,5.6,,,,,high,Presence of parks in the neighbourhood (ECV2003 household report),"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,7.478096477070095,1.3858149181514536,100*(exp(b - se^2/2) - 1),|b/t|,0.07682514807761463,0.013718776442431187,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.6,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Factories in neighborhood,hazard_site,E_environment,binary,binary,-0.0131,,-1.1,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,-1.308455629454075,1.1754099230182498,100*(exp(b - se^2/2) - 1),|b/t|,-0.015133652183149209,0.013757865621044734,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Garbage collector in neighborhood,hazard_site,E_environment,binary,binary,-0.0728,,-2.6,,,,,high,Garbage dump/collection site in neighbourhood,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,-7.057763620026625,2.603402952598151,100*(exp(b - se^2/2) - 1),|b/t|,-0.035751677016432254,0.013750645006320096,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Market places in neighborhood,commercial_distance,D_location,binary,binary (presence in neighbourhood),0.0127,,0.7,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,1.2614316051326124,1.8374740772921496,100*(exp(b - se^2/2) - 1),|b/t|,0.009631162228261011,0.013758803183230018,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Airport in neighborhood,airport_distance,D_location,binary,binary (presence in neighbourhood),-0.0315,,-1.3,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,-3.1293463712438463,2.347939625253292,100*(exp(b - se^2/2) - 1),|b/t|,-0.01788441289187469,0.013757240686057453,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Terminals of ground transportation in neighborhood,transit_distance,D_location,binary,binary (presence in neighbourhood),0.047,,2.2,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,4.788285232765377,2.2391697466701737,100*(exp(b - se^2/2) - 1),|b/t|,0.030256911657151206,0.013753141662341456,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,House close to open sewers,hazard_site,E_environment,binary,binary,-0.0556,,-4.7,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,-5.414875815728504,1.119000190472492,100*(exp(b - se^2/2) - 1),|b/t|,-0.06453456925530268,0.013730759416021846,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.7,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Plants of residual water treatment in neighborhood,hazard_site,E_environment,binary,binary,0.2513,,6.4,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,28.47049811657292,5.0483646602510905,100*(exp(b - se^2/2) - 1),|b/t|,0.0877209593555123,0.013706399899298794,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.4,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Lines of hydrocarbon transportation in neighborhood,hazard_site,E_environment,binary,binary,0.1315,,3.8,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,13.985520123760153,3.9468614438287326,100*(exp(b - se^2/2) - 1),|b/t|,0.05221455345476955,0.013740671961781461,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,House close to high tension lines of electricity transmission,hazard_site,E_environment,binary,binary,-0.0084,,-0.3,,,,,high,Power lines,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,-0.8753463388659677,2.7765785079846754,100*(exp(b - se^2/2) - 1),|b/t|,-0.00412779724018239,0.0137593241339413,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Feeling of safety in your neighborhood,crime,F_neighbourhood,binary,binary (perceived safety),0.0121,,1.5,,,,,high,Perceived safety (inverse of crime),"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,1.2140570064034462,0.8164866242654321,100*(exp(b - se^2/2) - 1),|b/t|,0.020634767554292468,0.013756511702861645,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Daily supply of water,public_services,F_neighbourhood,binary,binary,0.0063,,0.2,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,0.5820750113728623,3.1699076432316935,100*(exp(b - se^2/2) - 1),|b/t|,0.0027518778513881998,0.013759389256940997,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Kitchen is separate room in the house,kitchen_quality,B_interior,binary,binary,0.1054,,2.7,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,11.03086668042408,4.337619824354986,100*(exp(b - se^2/2) - 1),|b/t|,0.03712488137459201,0.013749956064663706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,House,dwelling_type,A_structural,binary,binary (house vs apartment etc.),-0.1301,,-13.1,,,,,high,Dummy = 1 if living in a house (as opposed to an apartment),"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,-12.203567240660163,0.8719755123083267,100*(exp(b - se^2/2) - 1),|b/t|,-0.177390050350272,0.013541225217578015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.1,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,"Wall material: brick, block, stone, or polished wood",roof_materials,A_structural,binary,binary,0.0254,,0.6,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,2.480663339205802,4.342237224443861,100*(exp(b - se^2/2) - 1),|b/t|,0.008255383491432412,0.013758972485720687,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,"Floor material: marmol, parquet, or lacquered wood",flooring,B_interior,binary,binary,0.0049,,0.2,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,0.4610470665023181,2.462034460348915,100*(exp(b - se^2/2) - 1),|b/t|,0.0027518778513881998,0.013759389256940997,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Floor material is carpet,flooring,B_interior,binary,binary,0.0548,,2.4,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,5.605399905394215,2.411951964873815,100*(exp(b - se^2/2) - 1),|b/t|,0.03300466842795952,0.013751945178316467,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,"Floor material: floor tile, vinyl, tablet, or wood",flooring,B_interior,binary,binary,0.0136,,0.7,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,1.3501599705816103,1.969460492734128,100*(exp(b - se^2/2) - 1),|b/t|,0.009631162228261011,0.013758803183230018,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,"Floor material: cement, gravilla, earth, or sand",flooring,B_interior,binary,binary,-0.0971,,-4.1,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,-9.278919926878304,2.149143323593292,100*(exp(b - se^2/2) - 1),|b/t|,-0.05632415475734719,0.013737598721304195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.1,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,House with toilet connected to the public sewerage,public_services,F_neighbourhood,binary,binary,0.2671,,2.8,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,30.024161046562025,12.45993890355409,100*(exp(b - se^2/2) - 1),|b/t|,0.038497875457120696,0.013749241234685964,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,True
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,House with potable water service,public_services,F_neighbourhood,binary,binary,0.0894,,1.0,,,,,high,,"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,8.91568012050914,9.776050705859946,100*(exp(b - se^2/2) - 1),|b/t|,0.013758139056883268,0.013758139056883268,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Stratum 2,income,F_neighbourhood,dummy,binary,0.2364,,6.0,,,,,medium,"Official socioeconomic stratum of the block (1-6, base stratum 1), proxy for neighbourhood wealth","logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,26.56980902926933,4.990722671921691,100*(exp(b - se^2/2) - 1),|b/t|,0.08227674157279218,0.013712790262132029,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Stratum 3,income,F_neighbourhood,dummy,binary,0.6205,,13.6,,,,,medium,Official socioeconomic stratum (base stratum 1),"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,85.7922967608615,8.485600930866015,100*(exp(b - se^2/2) - 1),|b/t|,0.18393567067889652,0.01352468166756592,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.6,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Stratum 4,income,F_neighbourhood,dummy,binary,0.917,,17.8,,,,,medium,Official socioeconomic stratum (base stratum 1),"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",pct_premium,149.8456164397734,12.888351539038421,100*(exp(b - se^2/2) - 1),|b/t|,0.2378871448895374,0.013364446342108843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.8,5282.0,binary,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",45,Area of the land (square meters),lot_size,A_structural,level,m2,0.001,,5.4,,,,,high,Main effect (stratum 1); Land*stratum interactions also included (not extracted),"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",semi_elasticity,0.1,0.018518518518518517,100*b/1 (X per m2->m2),|b/t|,0.07409673427669865,0.013721617458647894,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.4,5282.0,m2,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d,91b7dd63d779b9bfc5961da2cf5599ed5160c16d:T6-cA,6,"A (whole sample, eq. 1)",46,Built area (square meters),living_area,A_structural,level,m2,0.0039,,21.2,,,,,high,Main effect (stratum 1); Constructed area*stratum interactions also included (not extracted),"logarithm of house valuation (DACD cadastral appraisal, Colombian pesos)",log,OLS,5292.0,0.8715,se,"Whole sample, no boundary dummies, 19 Bogota neighbourhood FE, disaggregated subsidies; full set of hedonic controls reported in Appendix A-5 (pp.45-46, t-statistics)",semi_elasticity,0.38999999999999996,0.01839622641509434,100*b/1 (X per m2->m2),|b/t|,0.2800296294799057,0.013208944786788003,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.2,5282.0,m2,,2006.0,Colombia,South America,Upper middle income,2000.0,2003.0,mixed,appraisal,working_paper,False,True,robust,,2001.5,ols,other,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c1,2,1,12,Distance<200m (dist2),transit_distance,D_location,dummy,m,0.09,0.052,,,*,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.674,se,"Pre-CL sales within 2,000 m of 6 existing MRT stations; distance dummies up to 1,000 m",pct_premium,9.269595964589117,5.689706275267094,100*(exp(b - se^2/2) - 1),reported,0.019759911462649046,0.011416837733975007,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7307692307692308,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c2,2,2,12,Distance<200m (dist2),transit_distance,D_location,dummy,m,0.09,0.049,,,*,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.706,se,"Same as col 1, with additional fixed effects (text: year-of-sale FE)",pct_premium,9.286151562432622,5.361453990155531,100*(exp(b - se^2/2) - 1),reported,0.020969185345768786,0.011416556466029671,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8367346938775508,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,Distance<200m (dist2),transit_distance,D_location,dummy,m,0.172,0.051,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,18.613426211647077,6.05715694939092,100*(exp(b - se^2/2) - 1),reported,0.03848283724195168,0.011410608717090324,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.372549019607843,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,Distance<200m (dist2),transit_distance,D_location,dummy,m,0.173,0.048,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,18.749731990261665,5.706557304403354,100*(exp(b - se^2/2) - 1),reported,0.041121409893882535,0.0114094085254703,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6041666666666665,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c1,2,1,12,201 to 300m (dist3),transit_distance,D_location,dummy,m,0.118,0.024,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.674,se,"Pre-CL sales within 2,000 m of 6 existing MRT stations; distance dummies up to 1,000 m",pct_premium,12.492008772491259,2.700585867281622,100*(exp(b - se^2/2) - 1),reported,0.05605547008959727,0.011401112560596057,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.916666666666666,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c2,2,2,12,201 to 300m (dist3),transit_distance,D_location,dummy,m,0.125,0.023,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.706,se,"Same as col 1, with additional fixed effects (text: year-of-sale FE)",pct_premium,13.284877493517012,2.6062414420537006,100*(exp(b - se^2/2) - 1),reported,0.0619409811298128,0.011397140527885553,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.434782608695652,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,201 to 300m (dist3),transit_distance,D_location,dummy,m,0.191,0.023,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,21.013932789451406,2.7840567397869886,100*(exp(b - se^2/2) - 1),reported,0.09440439850806982,0.011368068930291129,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.304347826086957,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,201 to 300m (dist3),transit_distance,D_location,dummy,m,0.193,0.022,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,21.2589311395857,2.668342145742063,100*(exp(b - se^2/2) - 1),reported,0.09967746451439607,0.011362198027547737,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.772727272727273,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c1,2,1,12,301 to 400m (dist4),transit_distance,D_location,dummy,m,-0.029,0.022,,,,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.674,se,"Pre-CL sales within 2,000 m of 6 existing MRT stations; distance dummies up to 1,000 m",pct_premium,-2.8818589875073575,2.1371162218265303,100*(exp(b - se^2/2) - 1),reported,-0.015050701886498385,0.011417773844929808,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3181818181818183,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c2,2,2,12,301 to 400m (dist4),transit_distance,D_location,dummy,m,0.009,0.021,,,,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.706,se,"Same as col 1, with additional fixed effects (text: year-of-sale FE)",pct_premium,0.8818152844867422,2.118985305725123,100*(exp(b - se^2/2) - 1),reported,0.004893827366096075,0.011418930520890843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4285714285714285,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,301 to 400m (dist4),transit_distance,D_location,dummy,m,0.054,0.022,,,**,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,5.522920578556567,2.322066124741176,100*(exp(b - se^2/2) - 1),reported,0.02801761643577474,0.011414584473834153,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4545454545454546,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,301 to 400m (dist4),transit_distance,D_location,dummy,m,0.085,0.021,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,8.84770310500944,2.2863058400666376,100*(exp(b - se^2/2) - 1),reported,0.04617074338370794,0.011406889541857257,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0476190476190474,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c1,2,1,12,401 to 500m (dist5),transit_distance,D_location,dummy,m,-0.063,0.025,,,**,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.674,se,"Pre-CL sales within 2,000 m of 6 existing MRT stations; distance dummies up to 1,000 m",pct_premium,-6.134990030432064,2.347358684222833,100*(exp(b - se^2/2) - 1),reported,-0.02876414273298955,0.011414342354360932,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.52,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c2,2,2,12,401 to 500m (dist5),transit_distance,D_location,dummy,m,-0.04,0.023,,,*,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.706,se,"Same as col 1, with additional fixed effects (text: year-of-sale FE)",pct_premium,-3.9464656048760816,2.2098157100503433,100*(exp(b - se^2/2) - 1),reported,-0.019855332429547335,0.011416816146989715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7391304347826089,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,401 to 500m (dist5),transit_distance,D_location,dummy,m,0.014,0.024,,,,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,1.3806440634972272,2.4338363014523816,100*(exp(b - se^2/2) - 1),reported,0.006660974795830864,0.011418813935710051,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5833333333333334,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,401 to 500m (dist5),transit_distance,D_location,dummy,m,0.034,0.023,,,,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,3.4310995286346735,2.3795445954746715,100*(exp(b - se^2/2) - 1),reported,0.016877955814530304,0.011417440698064616,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4782608695652175,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c1,2,1,12,501 to 600m (dist6),transit_distance,D_location,dummy,m,0.069,0.026,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.674,se,"Pre-CL sales within 2,000 m of 6 existing MRT stations; distance dummies up to 1,000 m",pct_premium,7.107412490533838,2.7857341437857004,100*(exp(b - se^2/2) - 1),reported,0.030290542122463075,0.011413827466435359,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.653846153846154,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c2,2,2,12,501 to 600m (dist6),transit_distance,D_location,dummy,m,0.088,0.025,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.706,se,"Same as col 1, with additional fixed effects (text: year-of-sale FE)",pct_premium,9.164692905424253,2.729970305070494,100*(exp(b - se^2/2) - 1),reported,0.04016268548848491,0.011409853831955941,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5199999999999996,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,501 to 600m (dist6),transit_distance,D_location,dummy,m,0.14,0.026,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,14.988507201175128,2.990711877028791,100*(exp(b - se^2/2) - 1),reported,0.061371381735220845,0.011397542322255299,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.384615384615385,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,501 to 600m (dist6),transit_distance,D_location,dummy,m,0.158,0.025,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,17.08002624517162,2.927915486769174,100*(exp(b - se^2/2) - 1),reported,0.07198129868692903,0.011389445994767253,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.319999999999999,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c1,2,1,12,601 to 700m (dist7),transit_distance,D_location,dummy,m,-0.035,0.019,,,*,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.674,se,"Pre-CL sales within 2,000 m of 6 existing MRT stations; distance dummies up to 1,000 m",pct_premium,-3.4568859791181406,1.8346502908893763,100*(exp(b - se^2/2) - 1),reported,-0.021030471674986208,0.011416541766421083,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.842105263157895,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c2,2,2,12,601 to 700m (dist7),transit_distance,D_location,dummy,m,-0.053,0.018,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.706,se,"Same as col 1, with additional fixed effects (text: year-of-sale FE)",pct_premium,-5.177361263575342,1.7070840224681365,100*(exp(b - se^2/2) - 1),reported,-0.033603820080239426,0.01141261814045867,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.9444444444444446,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,601 to 700m (dist7),transit_distance,D_location,dummy,m,0.03,0.019,,,,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,3.026855369536152,1.9578636145116823,100*(exp(b - se^2/2) - 1),reported,0.0180271762621068,0.011417211632667639,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5789473684210527,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,601 to 700m (dist7),transit_distance,D_location,dummy,m,0.008,0.018,,,,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,0.7868797533104432,1.814457753907692,100*(exp(b - se^2/2) - 1),reported,0.005075075646449613,0.011418920204511627,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4444444444444445,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c1,2,1,12,701 to 800m (dist8),transit_distance,D_location,dummy,m,-0.156,0.019,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.674,se,"Pre-CL sales within 2,000 m of 6 existing MRT stations; distance dummies up to 1,000 m",pct_premium,-14.459522412651582,1.625562461704935,100*(exp(b - se^2/2) - 1),reported,-0.09334717550431697,0.01136920727296168,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.210526315789474,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c2,2,2,12,701 to 800m (dist8),transit_distance,D_location,dummy,m,-0.161,0.018,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.706,se,"Same as col 1, with additional fixed effects (text: year-of-sale FE)",pct_premium,-14.884582703831683,1.532325727992872,100*(exp(b - se^2/2) - 1),reported,-0.1016085968305756,0.01135996734751777,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.944444444444445,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,701 to 800m (dist8),transit_distance,D_location,dummy,m,-0.087,0.019,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,-8.348834965072339,1.7416864817029893,100*(exp(b - se^2/2) - 1),reported,-0.05221597844552184,0.011403489545573737,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.578947368421052,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,701 to 800m (dist8),transit_distance,D_location,dummy,m,-0.096,0.018,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,-9.168314318167582,1.635235228923671,100*(exp(b - se^2/2) - 1),reported,-0.06078906260002511,0.011397949237504708,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.333333333333334,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c1,2,1,12,801 to 900m (dist9),transit_distance,D_location,dummy,m,-0.026,0.017,,,,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.674,se,"Pre-CL sales within 2,000 m of 6 existing MRT stations; distance dummies up to 1,000 m",pct_premium,-2.58056916400089,1.6563696523348739,100*(exp(b - se^2/2) - 1),reported,-0.01746179302973811,0.011417326211751844,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5294117647058822,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c2,2,2,12,801 to 900m (dist9),transit_distance,D_location,dummy,m,-0.052,0.016,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.706,se,"Same as col 1, with additional fixed effects (text: year-of-sale FE)",pct_premium,-5.079263947549606,1.5189261869486235,100*(exp(b - se^2/2) - 1),reported,-0.03708643784850335,0.01141121164569334,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.25,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,801 to 900m (dist9),transit_distance,D_location,dummy,m,0.062,0.017,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,6.380861327658538,1.8087359860376575,100*(exp(b - se^2/2) - 1),reported,0.041609941711816416,0.011409177566143212,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6470588235294117,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,801 to 900m (dist9),transit_distance,D_location,dummy,m,0.033,0.016,,,**,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,3.341825323876746,1.653680862786089,100*(exp(b - se^2/2) - 1),reported,0.02354529698114883,0.011415901566617613,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0625,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c1,2,1,12,901 to 1000m (dist10),transit_distance,D_location,dummy,m,0.03,0.017,,,*,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.674,se,"Pre-CL sales within 2,000 m of 6 existing MRT stations; distance dummies up to 1,000 m",pct_premium,3.0305644030916623,1.751772707720979,100*(exp(b - se^2/2) - 1),reported,0.020147204949147738,0.01141674947118372,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.764705882352941,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c2,2,2,12,901 to 1000m (dist10),transit_distance,D_location,dummy,m,0.087,0.016,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.706,se,"Same as col 1, with additional fixed effects (text: year-of-sale FE)",pct_premium,9.075705387951816,1.7454346875492446,100*(exp(b - se^2/2) - 1),reported,0.061971832707566045,0.011397118658862723,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.437499999999999,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,901 to 1000m (dist10),transit_distance,D_location,dummy,m,0.113,0.017,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,11.947015782280923,1.9033742860125964,100*(exp(b - se^2/2) - 1),reported,0.0756855015784734,0.011386314396761486,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.647058823529411,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,901 to 1000m (dist10),transit_distance,D_location,dummy,m,0.162,0.016,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,17.57097408423467,1.8813763861135997,100*(exp(b - se^2/2) - 1),reported,0.11485295399187302,0.011343501628826965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.125,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,1001 to 1100m (dist11),transit_distance,D_location,dummy,m,0.197,0.013,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,21.76411456818448,1.5830672529176808,100*(exp(b - se^2/2) - 1),reported,0.17050877715631488,0.011251848238741589,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.153846153846155,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,1001 to 1100m (dist11),transit_distance,D_location,dummy,m,0.166,0.012,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,18.048810351992394,1.4166877220679315,100*(exp(b - se^2/2) - 1),reported,0.15602909619399122,0.011279211773059607,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.833333333333334,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,1101 to 1200m (dist12),transit_distance,D_location,dummy,m,0.279,0.018,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,32.15932284236518,2.3792532189651707,100*(exp(b - se^2/2) - 1),reported,0.17428661960580769,0.011244298039084364,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.500000000000002,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,True
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,1101 to 1200m (dist12),transit_distance,D_location,dummy,m,0.229,0.018,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,25.713836609747087,2.2632156702177104,100*(exp(b - se^2/2) - 1),reported,0.14376672767880888,0.011300441476936941,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.722222222222223,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,1201 to 1300m (dist13),transit_distance,D_location,dummy,m,0.208,0.022,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,23.09152520113129,2.7086689730075086,100*(exp(b - se^2/2) - 1),reported,0.10733834494383435,0.01135309417675171,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.454545454545455,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,1201 to 1300m (dist13),transit_distance,D_location,dummy,m,0.236,0.021,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,26.58951495100814,2.658966051350448,100*(exp(b - se^2/2) - 1),reported,0.12728476841789355,0.011326187020236292,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.238095238095237,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,1301 to 1400m (dist14),transit_distance,D_location,dummy,m,0.15,0.018,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,16.164604082572676,2.0913016369109094,100*(exp(b - se^2/2) - 1),reported,0.0947309558482455,0.011367714701789457,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.333333333333334,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,1301 to 1400m (dist14),transit_distance,D_location,dummy,m,0.181,0.017,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,19.824202081079335,2.0373058047984394,100*(exp(b - se^2/2) - 1),reported,0.12069075358062646,0.011335595640169336,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.647058823529411,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,1401 to 1500m (dist15),transit_distance,D_location,dummy,m,0.055,0.023,,,**,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,5.626119663757723,2.4300434137536366,100*(exp(b - se^2/2) - 1),reported,0.027296290444631256,0.011414812367754889,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.391304347826087,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,1401 to 1500m (dist15),transit_distance,D_location,dummy,m,0.097,0.022,,,***,,,high,"Distance-band dummy to nearest existing MRT station (100-m bands); reference = sales beyond the last band up to 2,000 m. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,10.159375567266714,2.424092821966223,100*(exp(b - se^2/2) - 1),reported,0.05028401373602301,0.011404621672087693,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.409090909090909,7669.0,m,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c1,2,1,12,Floor level (floor),floor_level,A_structural,level,count,0.013,0.001,,,***,,,high,"Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.674,se,"Pre-CL sales within 2,000 m of 6 existing MRT stations; distance dummies up to 1,000 m",semi_elasticity,1.3,0.1,100*b/1 (per unit count),reported,0.14683876485102718,0.011295289603925165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,7669.0,count,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c2,2,2,12,Floor level (floor),floor_level,A_structural,level,count,0.013,0.001,,,***,,,high,"Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.706,se,"Same as col 1, with additional fixed effects (text: year-of-sale FE)",semi_elasticity,1.3,0.1,100*b/1 (per unit count),reported,0.14683876485102718,0.011295289603925165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,7669.0,count,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,Floor level (floor),floor_level,A_structural,level,count,0.013,0.001,,,***,,,high,"Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",semi_elasticity,1.3,0.1,100*b/1 (per unit count),reported,0.14683876485102718,0.011295289603925165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,7669.0,count,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,Floor level (floor),floor_level,A_structural,level,count,0.013,0.001,,,***,,,high,"Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",semi_elasticity,1.3,0.1,100*b/1 (per unit count),reported,0.14683876485102718,0.011295289603925165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,7669.0,count,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c1,2,1,12,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.226,0.009,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.674,se,"Pre-CL sales within 2,000 m of 6 existing MRT stations; distance dummies up to 1,000 m",pct_premium,25.3524896491818,1.128218098750368,100*(exp(b - se^2/2) - 1),reported,0.2756374278113392,0.010976711727000234,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.111111111111114,7669.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c2,2,2,12,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.219,0.008,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.706,se,"Same as col 1, with additional fixed effects (text: year-of-sale FE)",pct_premium,24.479144272402408,0.995865021350025,100*(exp(b - se^2/2) - 1),reported,0.29835930784584275,0.010898970149619826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.375,7669.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.231,0.009,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",pct_premium,25.98082161832618,1.1338733155043081,100*(exp(b - se^2/2) - 1),reported,0.28125801448813725,0.010958104460576774,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.66666666666667,7669.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.235,0.008,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",pct_premium,26.48682922999186,1.0119270149863133,100*(exp(b - se^2/2) - 1),reported,0.3180205875426816,0.010826232767410437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.374999999999996,7669.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c1,2,1,12,Age (age),age,A_structural,level,years,-0.011,0.001,,,***,,,high,"Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.674,se,"Pre-CL sales within 2,000 m of 6 existing MRT stations; distance dummies up to 1,000 m",semi_elasticity,-1.0999999999999999,0.1,100*b/1 (per year),reported,-0.12463039065457177,0.011330035514051979,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.0,7669.0,years,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c2,2,2,12,Age (age),age,A_structural,level,years,-0.012,0.001,,,***,,,high,"Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.706,se,"Same as col 1, with additional fixed effects (text: year-of-sale FE)",semi_elasticity,-1.2,0.1,100*b/1 (per year),reported,-0.13576015773227668,0.011313346477689723,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.0,7669.0,years,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c3,2,3,12,Age (age),age,A_structural,level,years,-0.01,0.001,,,***,,,high,"Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.692,se,"Pre-CL sales within 2,000 m; distance dummies up to 1,500 m",semi_elasticity,-1.0,0.1,100*b/1 (per year),reported,-0.11345338009741439,0.011345338009741437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.0,7669.0,years,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T2-c4,2,4,12,Age (age),age,A_structural,level,years,-0.011,0.001,,,***,,,high,"Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,7679.0,0.722,se,"Same as col 3, with planning sector FE (table note) / year-of-sale FE (text)",semi_elasticity,-1.0999999999999999,0.1,100*b/1 (per year),reported,-0.12463039065457177,0.011330035514051979,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.0,7669.0,years,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T3-c1,3,1,17,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.133,0.003,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.669,se,"Sales within 4,000 m of CL stations; no FE",pct_premium,14.224485821746713,0.3426749994992683,100*(exp(b - se^2/2) - 1),reported,0.15363223096886325,0.0034653886684705994,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),44.333333333333336,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T3-c2,3,2,17,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.165,0.002,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.865,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE",pct_premium,17.939075992751196,0.23587862374227814,100*(exp(b - se^2/2) - 1),reported,0.27793024027107677,0.0033688513972251733,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),82.5,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T3-c3,3,3,17,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.154,0.002,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,57417.0,0.859,se,"Sales within 2,000 m; planning sector FE + year-of-sale FE",pct_premium,16.648855379899885,0.23329817735568792,100*(exp(b - se^2/2) - 1),reported,0.3059605332754418,0.003973513419161582,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),77.0,57407.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T3-c1,3,1,17,After the opening of MRT line (after),transaction_timing,G_market,binary,binary,0.051,0.002,,,***,,,high,"Post-Circle-Line-opening period dummy (DiD time indicator). Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.669,se,"Sales within 4,000 m of CL stations; no FE",pct_premium,5.232078863952205,0.21046457865664076,100*(exp(b - se^2/2) - 1),reported,0.08907362790058182,0.003493083447081641,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.499999999999996,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T3-c2,3,2,17,After the opening of MRT line (after),transaction_timing,G_market,binary,binary,0.016,0.002,,,***,,,high,"Post-Circle-Line-opening period dummy (DiD time indicator). Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.865,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE",pct_premium,1.6126653150756232,0.203225737081219,100*(exp(b - se^2/2) - 1),reported,0.0280451539914883,0.0035056442489360376,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T3-c3,3,3,17,After the opening of MRT line (after),transaction_timing,G_market,binary,binary,0.015,0.003,,,***,,,high,"Post-Circle-Line-opening period dummy (DiD time indicator). Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,57417.0,0.859,se,"Sales within 2,000 m; planning sector FE + year-of-sale FE",pct_premium,1.5108496617206146,0.3045339193847157,100*(exp(b - se^2/2) - 1),reported,0.020863781900230534,0.004172756380046107,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,57407.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T3-c1,3,1,17,Proximity to MRT (<= 400m) (dumMRT),transit_distance,D_location,binary,binary,0.126,0.007,,,***,,,high,"Difference-in-differences interaction term (Circle Line opening x within 400 m of CL station); x_transform other. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.669,se,"Sales within 4,000 m of CL stations; no FE",pct_premium,13.425437871032564,0.7939975177981176,100*(exp(b - se^2/2) - 1),reported,0.06300102377495459,0.003500056876386366,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T3-c2,3,2,17,Proximity to MRT (<= 400m) (dumMRT),transit_distance,D_location,binary,binary,0.042,0.005,,,***,,,high,"Difference-in-differences interaction term (Circle Line opening x within 400 m of CL station); x_transform other. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.865,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE",pct_premium,4.288144265125471,0.5214472393753816,100*(exp(b - se^2/2) - 1),reported,0.029446224746603838,0.0035055029460242665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.4,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T3-c3,3,3,17,Proximity to MRT (<= 400m) (dumMRT),transit_distance,D_location,binary,binary,0.049,0.005,,,***,,,high,"Difference-in-differences interaction term (Circle Line opening x within 400 m of CL station); x_transform other. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,57417.0,0.859,se,"Sales within 2,000 m; planning sector FE + year-of-sale FE",pct_premium,5.020722306769199,0.525110175370014,100*(exp(b - se^2/2) - 1),reported,0.040867744839514886,0.004170178044848457,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.8,57407.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T4-c1,4,1,19,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.163,0.002,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.864,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE; triple interaction with existing-station dummy",pct_premium,17.703433561744177,0.23540733793769342,100*(exp(b - se^2/2) - 1),reported,0.2748172614807181,0.0033719909384137188,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),81.5,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T4-c2,4,2,19,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.163,0.002,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.864,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE; triple interaction with interchange dummy",pct_premium,17.703433561744177,0.23540733793769342,100*(exp(b - se^2/2) - 1),reported,0.2748172614807181,0.0033719909384137188,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),81.5,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T4-c1,4,1,19,After the opening of MRT line (after),transaction_timing,G_market,binary,binary,0.026,0.002,,,***,,,high,"Post-Circle-Line-opening period dummy (DiD time indicator). Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.864,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE; triple interaction with existing-station dummy",pct_premium,2.633889579359794,0.2052681896946884,100*(exp(b - se^2/2) - 1),reported,0.045543999678550995,0.0035033845906577684,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T4-c2,4,2,19,After the opening of MRT line (after),transaction_timing,G_market,binary,binary,0.026,0.002,,,***,,,high,"Post-Circle-Line-opening period dummy (DiD time indicator). Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.864,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE; triple interaction with interchange dummy",pct_premium,2.633889579359794,0.2052681896946884,100*(exp(b - se^2/2) - 1),reported,0.045543999678550995,0.0035033845906577684,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T4-c1,4,1,19,Proximity to MRT (<= 400m) (dumMRT),transit_distance,D_location,binary,binary,0.129,0.003,,,***,,,high,"Difference-in-differences interaction term (Circle Line opening x within 400 m of CL station); x_transform other. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.864,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE; triple interaction with existing-station dummy",pct_premium,13.768500457169196,0.3413070372497195,100*(exp(b - se^2/2) - 1),reported,0.14911600903350777,0.0034678141635699484,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),43.0,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T4-c2,4,2,19,Proximity to MRT (<= 400m) (dumMRT),transit_distance,D_location,binary,binary,0.13,0.003,,,***,,,high,"Difference-in-differences interaction term (Circle Line opening x within 400 m of CL station); x_transform other. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.864,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE; triple interaction with interchange dummy",pct_premium,13.882325860842748,0.3416485149973865,100*(exp(b - se^2/2) - 1),reported,0.15024595123343726,0.0034672142592331676,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),43.333333333333336,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T5-c1,5,1,21,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.164,0.002,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.864,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE; heterogeneity by resale",pct_premium,17.821195866644835,0.23564286301854445,100*(exp(b - se^2/2) - 1),reported,0.2763748382768127,0.003370424857034301,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),82.0,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T5-c2,5,2,21,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.163,0.002,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.864,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE; heterogeneity by HDB-upgrader buyer",pct_premium,17.703433561744177,0.23540733793769342,100*(exp(b - se^2/2) - 1),reported,0.2748172614807181,0.0033719909384137188,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),81.5,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T5-c1,5,1,21,After the opening of MRT line (after),transaction_timing,G_market,binary,binary,0.026,0.002,,,***,,,high,"Post-Circle-Line-opening period dummy (DiD time indicator). Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.864,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE; heterogeneity by resale",pct_premium,2.633889579359794,0.2052681896946884,100*(exp(b - se^2/2) - 1),reported,0.045543999678550995,0.0035033845906577684,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T5-c2,5,2,21,After the opening of MRT line (after),transaction_timing,G_market,binary,binary,0.024,0.002,,,***,,,high,"Post-Circle-Line-opening period dummy (DiD time indicator). Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.864,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE; heterogeneity by HDB-upgrader buyer",pct_premium,2.4288269312034316,0.2048580635781243,100*(exp(b - se^2/2) - 1),reported,0.04204706649821094,0.0035039222081842446,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T5-c1,5,1,21,Proximity to MRT (<= 400m) (dumMRT),transit_distance,D_location,binary,binary,0.134,0.003,,,***,,,high,"Difference-in-differences interaction term (Circle Line opening x within 400 m of CL station); x_transform other. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.864,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE; heterogeneity by resale",pct_premium,14.338767438853539,0.3430178458933941,100*(exp(b - se^2/2) - 1),reported,0.1547597952627518,0.0034647715357332483,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),44.66666666666667,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T5-c2,5,2,21,Proximity to MRT (<= 400m) (dumMRT),transit_distance,D_location,binary,binary,0.111,0.003,,,***,,,high,"Difference-in-differences interaction term (Circle Line opening x within 400 m of CL station); x_transform other. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.864,se,"Sales within 4,000 m; planning sector FE + year-of-sale FE; heterogeneity by HDB-upgrader buyer",pct_premium,11.738987858869109,0.3352184720563375,100*(exp(b - se^2/2) - 1),reported,0.12868105779648148,0.003477866426931932,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.0,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T6-c1,6,1,22,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.168,0.002,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.866,se,"Sales within 4,000 m; FE; phase-specific opening dummies (aftph1-4 period dummies not extracted)",pct_premium,18.293424477695552,0.23658732212956216,100*(exp(b - se^2/2) - 1),reported,0.2825833162400669,0.0033640870980960343,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),84.0,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T6-c2,6,2,22,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.165,0.002,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.865,se,"Sales within 4,000 m; FE; 6-month anticipation window + after",pct_premium,17.939075992751196,0.23587862374227814,100*(exp(b - se^2/2) - 1),reported,0.27793024027107677,0.0033688513972251733,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),82.5,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T6-c3,6,3,22,Condominium dummy (dumcond),dwelling_type,A_structural,binary,binary,0.168,0.002,,,***,,,high,"Condominium vs apartment (non-landed) dummy. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.866,se,"Sales within 4,000 m; FE; anticipation window + phase-specific dummies",pct_premium,18.293424477695552,0.23658732212956216,100*(exp(b - se^2/2) - 1),reported,0.2825833162400669,0.0033640870980960343,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),84.0,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T6-c1,6,1,22,Proximity to MRT (<= 400m) (dumMRT),transit_distance,D_location,binary,binary,0.038,0.005,,,***,,,high,"Difference-in-differences interaction term (Circle Line opening x within 400 m of CL station); x_transform other. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.866,se,"Sales within 4,000 m; FE; phase-specific opening dummies (aftph1-4 period dummies not extracted)",pct_premium,3.8718248819237244,0.5193656164392488,100*(exp(b - se^2/2) - 1),reported,0.02664391792909864,0.0035057786748814,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.6,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T6-c2,6,2,22,Proximity to MRT (<= 400m) (dumMRT),transit_distance,D_location,binary,binary,0.031,0.005,,,***,,,high,"Difference-in-differences interaction term (Circle Line opening x within 400 m of CL station); x_transform other. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.865,se,"Sales within 4,000 m; FE; 6-month anticipation window + after",pct_premium,3.147261039830851,0.5157427519432614,100*(exp(b - se^2/2) - 1),reported,0.021738408853487993,0.0035061949763690314,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.2,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T6-c3,6,3,22,Proximity to MRT (<= 400m) (dumMRT),transit_distance,D_location,binary,binary,0.028,0.005,,,***,,,high,"Difference-in-differences interaction term (Circle Line opening x within 400 m of CL station); x_transform other. Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.866,se,"Sales within 4,000 m; FE; anticipation window + phase-specific dummies",pct_premium,2.838282955571292,0.5141978422107125,100*(exp(b - se^2/2) - 1),reported,0.01963554639868067,0.003506347571192977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.6,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T6-c2,6,2,22,6 months before MRT opening (bef6mth),transaction_timing,G_market,binary,binary,-0.007,0.003,,,**,,,high,"Sold within 180 days before opening of nearest CL station (anticipation dummy). Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.865,se,"Sales within 4,000 m; FE; 6-month anticipation window + after",pct_premium,-0.6980025666703749,0.2979073328799705,100*(exp(b - se^2/2) - 1),reported,-0.008182781361118227,0.0035069062976220977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3333333333333335,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T6-c3,6,3,22,6 months before MRT opening (bef6mth),transaction_timing,G_market,binary,binary,-0.017,0.003,,,***,,,high,"Sold within 180 days before opening of nearest CL station (anticipation dummy). Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.866,se,"Sales within 4,000 m; FE; anticipation window + phase-specific dummies",pct_premium,-1.686073950171696,0.2949431053904729,100*(exp(b - se^2/2) - 1),reported,-0.019869211162369508,0.0035063313815946184,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.666666666666667,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,True
933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68,933204aac69df35d44733b61b90a1210852e7b68:T6-c2,6,2,22,After the opening of MRT line (after),transaction_timing,G_market,binary,binary,0.021,0.003,,,***,,,high,"Post-Circle-Line-opening period dummy (DiD time indicator). Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.",ln sale price (lnprice),log,OLS,81316.0,0.865,se,"Sales within 4,000 m; FE; 6-month anticipation window + after",pct_premium,2.121745614863624,0.30636661549125854,100*(exp(b - se^2/2) - 1),reported,0.02454177190026069,0.0035059674143229553,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,81306.0,binary,,2017.0,Singapore,Asia,High income,2009.0,2013.0,condo_apartment,transaction,journal,True,True,unknown,,2011.0,ols,journal,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Area,living_area,A_structural,level,m2,0.015,,37.546,,,,,high,"Area in m2; SE printed 0.000 (rounded); p printed '-' meaning <0.000; SE printed as 0.000 (rounded), stored as null; use z-value","ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",semi_elasticity,1.5,0.03995099344803707,100*b/1 (X per m2->m2),|b/t|,0.422647528698053,0.011256792433229988,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.546,6482.0,m2,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Number of bathrooms,bathrooms,A_structural,level,count,0.098,0.008,11.842,,,,,high,p printed '-' (<0.000),"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",semi_elasticity,9.8,0.8,100*b/1 (per unit count),reported,0.14552004801922622,0.012288468841346581,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.842,6482.0,count,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Air conditioner,air_conditioning,A_structural,dummy,binary,0.074,0.008,8.905,,,,,high,p printed '-' (<0.000),"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,7.677234822976331,0.8614454443969759,100*(exp(b - se^2/2) - 1),reported,0.10993576640999868,0.012345397687815687,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.905,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Central heating,heating,A_structural,dummy,binary,0.041,0.009,4.686,,,,,high,p printed '-' (<0.000),"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,4.180991138964241,0.9376668949909315,100*(exp(b - se^2/2) - 1),reported,0.05810498592427124,0.012399698233946061,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.686,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Retrofitted apartment,renovation,A_structural,dummy,binary,0.034,0.01,3.437,0.001,,,,high,,"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,3.453287879099065,1.034584606728118,100*(exp(b - se^2/2) - 1),reported,0.042651041827716216,0.01240938080527094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.437,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Swimming pool,pool,C_exterior,dummy,binary,0.186,0.015,11.976,,,,,high,p printed '-' (<0.000),"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,20.428677049478594,1.8066333905664447,100*(exp(b - se^2/2) - 1),reported,0.14713125186349657,0.012285508672636655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.976,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Lift,accessibility,B_interior,dummy,binary,0.089,0.008,10.452,,,,,high,p printed '-' (<0.000),"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,9.304567830497913,0.8744645250610642,100*(exp(b - se^2/2) - 1),reported,0.12874064971146412,0.012317322016022208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.452,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Energy class A,energy_efficiency,A_structural,dummy,binary,0.086,0.034,2.492,0.013,,,,high,EPC class A vs reference G (2014 baseline; year-2016 interactions separate),"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,8.917660225572831,3.705341516237438,100*(exp(b - se^2/2) - 1),reported,0.030937526398574635,0.012414737720134284,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.492,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Energy class C,energy_efficiency,A_structural,dummy,binary,-0.011,0.029,-0.375,0.708,,,,high,EPC class C vs G (2014 baseline); class B absent in 2014,"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,-1.1355533641168813,2.8682748084485694,100*(exp(b - se^2/2) - 1),reported,-0.004657705695564641,0.01242054852150571,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.375,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Energy class D,energy_efficiency,A_structural,dummy,binary,0.0,0.019,0.02,0.984,,,,high,EPC class D vs G (2014 baseline),"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,-0.018048371085510606,1.9,100*(exp(b - se^2/2) - 1),reported,0.0002484136573506475,0.012420682867532373,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.02,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Energy class E,energy_efficiency,A_structural,dummy,binary,0.007,0.013,0.572,0.567,,,,high,EPC class E vs G (2014 baseline),"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,0.69394672868619,1.309131924446903,100*(exp(b - se^2/2) - 1),reported,0.007104451520339401,0.01242036979080315,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.572,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Energy class F,energy_efficiency,A_structural,dummy,binary,0.019,0.016,1.132,0.258,,,,high,EPC class F vs G (2014 baseline),"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,1.9051201715164723,1.630690637787853,100*(exp(b - se^2/2) - 1),reported,0.014058823866895335,0.012419455712805066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.132,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,<200m from sea shore,water_proximity,E_environment,dummy,binary,0.131,0.029,4.532,,,,,high,Within 200 m of the sea shore; p printed '-' (<0.000),"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,13.948852563051762,3.305906565804772,100*(exp(b - se^2/2) - 1),reported,0.05620156608561427,0.012401051651724242,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.532,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,Highway ramp,highway_distance,D_location,dummy,binary,0.081,0.022,3.712,,,,,high,Municipality with highway access dummy; p printed '-' (<0.000),"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,8.410851055977853,2.385615972446873,100*(exp(b - se^2/2) - 1),reported,0.04605665034661409,0.012407502787342156,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.712,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,True
942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937,942f0ff361a49b68c1333c31381f78c02a3d0937:T2-SEM,2,1,7,<800 m from railway station,transit_distance,D_location,dummy,binary,0.033,0.011,3.12,0.002,,,,high,Within 800 m of a railway station,"ln(asking price, EUR)",log,spatial_error,6492.0,0.764,se,"Pooled 2014 and 2016 listings, spatial error ML; z-values and p-values in separate columns",pct_premium,3.3488011325169875,1.1369055931654362,100*(exp(b - se^2/2) - 1),reported,0.038723465999439204,0.012411367307512565,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.12,6482.0,binary,,2019.0,Spain,Europe,High income,2014.0,2016.0,condo_apartment,listing,conference,True,False,unknown,,2015.0,spatial,other,True,True,False
96e0ec640b350c1ec477b4a65c34f99c77d53503,96e0ec640b350c1ec477b4a65c34f99c77d53503,96e0ec640b350c1ec477b4a65c34f99c77d53503:T1-c1,1,1,5,Terraced,dwelling_type,A_structural,binary,"binary (terraced house, reference detached)",-0.12,,-4.63,0.0,,,,high,Property type dummy; reference category detached,"LnP: natural log of sold house price (Land Registry via Nethouseprices), indexed to 2009Q1 with Nationwide Greater London index",log,OLS,1251.0,0.44,t,"Single LSDV regression (eq. 1); t-statistic and p-value in separate columns; R2 is adjusted; S.E. of regression 0.17; N = 1,251 sold houses (Goldfeld-Quandt subsamples of 469 each); plot/house over-sail and plot-tower dummies in eq. 1 not reported in Table 1",pct_premium,-11.337740274947539,2.2987138748608835,100*(exp(b - se^2/2) - 1),|b/t|,-0.13030952177259159,0.028144605134469022,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.63,1241.0,binary,,2011.0,United Kingdom,Europe,High income,2000.0,2009.0,mixed,transaction,journal,False,False,OLS,,2004.5,ols,journal,True,True,False
96e0ec640b350c1ec477b4a65c34f99c77d53503,96e0ec640b350c1ec477b4a65c34f99c77d53503,96e0ec640b350c1ec477b4a65c34f99c77d53503:T1-c1,1,1,5,Semi-detached,dwelling_type,A_structural,binary,"binary (semi-detached, reference detached)",-0.08,,-3.48,0.005,,,,high,Property type dummy; reference category detached,"LnP: natural log of sold house price (Land Registry via Nethouseprices), indexed to 2009Q1 with Nationwide Greater London index",log,OLS,1251.0,0.44,t,"Single LSDV regression (eq. 1); t-statistic and p-value in separate columns; R2 is adjusted; S.E. of regression 0.17; N = 1,251 sold houses (Goldfeld-Quandt subsamples of 469 each); plot/house over-sail and plot-tower dummies in eq. 1 not reported in Table 1",pct_premium,-7.712754168232494,2.1221065434175537,100*(exp(b - se^2/2) - 1),|b/t|,-0.09830703025828706,0.028249146625944556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.48,1241.0,binary,,2011.0,United Kingdom,Europe,High income,2000.0,2009.0,mixed,transaction,journal,False,False,OLS,,2004.5,ols,journal,True,True,False
96e0ec640b350c1ec477b4a65c34f99c77d53503,96e0ec640b350c1ec477b4a65c34f99c77d53503,96e0ec640b350c1ec477b4a65c34f99c77d53503:T1-c1,1,1,5,Flat,dwelling_type,A_structural,binary,"binary (flat, reference detached)",-0.33,,,0.002,,,,medium,"Property type dummy; t-statistic printed as '-373' (typo, presumably -3.73), not recorded","LnP: natural log of sold house price (Land Registry via Nethouseprices), indexed to 2009Q1 with Nationwide Greater London index",log,OLS,1251.0,0.44,t,"Single LSDV regression (eq. 1); t-statistic and p-value in separate columns; R2 is adjusted; S.E. of regression 0.17; N = 1,251 sold houses (Goldfeld-Quandt subsamples of 469 each); plot/house over-sail and plot-tower dummies in eq. 1 not reported in Table 1",pct_premium,-28.516379602962203,7.677249103862427,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.08738576223740169,0.02827805600989541,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.090232306167813,1241.0,binary,,2011.0,United Kingdom,Europe,High income,2000.0,2009.0,mixed,transaction,journal,False,False,OLS,,2004.5,ols,journal,True,True,False
96e0ec640b350c1ec477b4a65c34f99c77d53503,96e0ec640b350c1ec477b4a65c34f99c77d53503,96e0ec640b350c1ec477b4a65c34f99c77d53503:T1-c1,1,1,5,LnDCL,hazard_site,E_environment,log,m (ln distance to centre line of high-voltage overhead transmission line),0.03,,3.63,0.003,,,,high,Elasticity of price w.r.t. distance to HVOTL centre line (positive = closer to line lowers value),"LnP: natural log of sold house price (Land Registry via Nethouseprices), indexed to 2009Q1 with Nationwide Greater London index",log,OLS,1251.0,0.44,t,"Single LSDV regression (eq. 1); t-statistic and p-value in separate columns; R2 is adjusted; S.E. of regression 0.17; N = 1,251 sold houses (Goldfeld-Quandt subsamples of 469 each); plot/house over-sail and plot-tower dummies in eq. 1 not reported in Table 1",elasticity,0.03,0.008264462809917356,b (log-log),|b/t|,0.10250079322682493,0.028237133120337446,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.63,1241.0,m,,2011.0,United Kingdom,Europe,High income,2000.0,2009.0,mixed,transaction,journal,False,False,OLS,,2004.5,ols,journal,True,True,False
96e0ec640b350c1ec477b4a65c34f99c77d53503,96e0ec640b350c1ec477b4a65c34f99c77d53503,96e0ec640b350c1ec477b4a65c34f99c77d53503:T1-c1,1,1,5,LnDPK,green_space,E_environment,log,m (ln distance to public park),1.08,,5.98,0.0,,,,high,Main effect of ln distance to public park; enters interactions with LnDRA and LnDPY (full elasticity = 1.08 - 0.09 LnDRA - 0.08 LnDPY),"LnP: natural log of sold house price (Land Registry via Nethouseprices), indexed to 2009Q1 with Nationwide Greater London index",log,OLS,1251.0,0.44,t,"Single LSDV regression (eq. 1); t-statistic and p-value in separate columns; R2 is adjusted; S.E. of regression 0.17; N = 1,251 sold houses (Goldfeld-Quandt subsamples of 469 each); plot/house over-sail and plot-tower dummies in eq. 1 not reported in Table 1",elasticity,1.08,0.1806020066889632,b (log-log),|b/t|,0.16735800181379998,0.027986287928729096,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.98,1241.0,m,,2011.0,United Kingdom,Europe,High income,2000.0,2009.0,mixed,transaction,journal,False,False,OLS,,2004.5,ols,journal,True,True,True
96e0ec640b350c1ec477b4a65c34f99c77d53503,96e0ec640b350c1ec477b4a65c34f99c77d53503,96e0ec640b350c1ec477b4a65c34f99c77d53503:T1-c1,1,1,5,LnDWS,transit_distance,D_location,log,m (ln distance to Welling railway station),-0.89,,-7.77,0.0,,,,high,Main effect of ln distance to Welling station; interacts with LnDPY (full elasticity = -0.89 + 0.11 LnDPY),"LnP: natural log of sold house price (Land Registry via Nethouseprices), indexed to 2009Q1 with Nationwide Greater London index",log,OLS,1251.0,0.44,t,"Single LSDV regression (eq. 1); t-statistic and p-value in separate columns; R2 is adjusted; S.E. of regression 0.17; N = 1,251 sold houses (Goldfeld-Quandt subsamples of 469 each); plot/house over-sail and plot-tower dummies in eq. 1 not reported in Table 1",elasticity,-0.89,0.11454311454311455,b (log-log),|b/t|,-0.21538732345438844,0.02772037624895604,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.77,1241.0,m,,2011.0,United Kingdom,Europe,High income,2000.0,2009.0,mixed,transaction,journal,False,False,OLS,,2004.5,ols,journal,True,True,True
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c1,A1,1,17,Finsqft,living_area,A_structural,level,1000 sqft,0.283044,0.024368,,,,,,medium,Total finished square footage in thousands (Table 1); not stated whether logged. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,1033.0,0.8296,se,Pre-project cross-section (Aug 2010-Jul 2011); month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,0.30466602599871867,0.02622949690343825,100*b/92.903 (X per 1000sqft->m2),reported,0.34134635295842775,0.029387402414080378,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.615397242284963,1023.0,1000sqft,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,Finsqft,living_area,A_structural,level,1000 sqft,0.280172,0.010226,,,,,,medium,Total finished square footage in thousands (Table 1); not stated whether logged. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,0.3015746309270396,0.011007174792127363,100*b/92.903 (X per 1000sqft->m2),reported,0.4011093927302134,0.014640094834812767,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.39800508507725,3915.0,1000sqft,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,17,Finsqft,living_area,A_structural,level,1000 sqft,0.28005,0.010258,,,,,,medium,Total finished square footage in thousands (Table 1); not stated whether logged. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,0.30144331121995577,0.011041619305460833,100*b/92.903 (X per 1000sqft->m2),reported,0.39991231122084636,0.014648457377266352,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.30064340027296,3915.0,1000sqft,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c1,A1,1,17,Bdrms,bedrooms,A_structural,level,count,-0.039027,0.016597,,,,,,high,Number of bedrooms. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,1033.0,0.8296,se,Pre-project cross-section (Aug 2010-Jul 2011); month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,-3.9027,1.6597,100*b/1 (per unit count),reported,-0.07332080722926594,0.03118111660092057,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3514490570585043,1023.0,count,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,Bdrms,bedrooms,A_structural,level,count,-0.037703,0.00705,,,,,,high,Number of bedrooms. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,-3.7703,0.705,100*b/1 (per unit count),reported,-0.08516091808391656,0.015924050406906923,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.347943262411348,3915.0,count,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,17,Bdrms,bedrooms,A_structural,level,count,-0.037248,0.007058,,,,,,high,Number of bedrooms. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,-3.7248,0.7058,100*b/1 (per unit count),reported,-0.08404581936256406,0.0159255636023673,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.277415698498158,3915.0,count,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c1,A1,1,17,Fbath,bathrooms,A_structural,level,count,0.175602,0.026654,,,,,,high,Number of full bathrooms. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,1033.0,0.8296,se,Pre-project cross-section (Aug 2010-Jul 2011); month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,17.560200000000002,2.6654,100*b/1 (per unit count),reported,0.20174653889892968,0.030622386122094693,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.588204397088617,1023.0,count,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,Fbath,bathrooms,A_structural,level,count,0.14164,0.011502,,,,,,high,Number of full bathrooms. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,14.163999999999998,1.1502000000000001,100*b/1 (per unit count),reported,0.1931054270743434,0.015681294988767986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.314380107807336,3915.0,count,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,17,Fbath,bathrooms,A_structural,level,count,0.140987,0.011494,,,,,,high,Number of full bathrooms. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,14.098700000000001,1.1494,100*b/1 (per unit count),reported,0.19237699146247278,0.015683581747747397,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.26613885505481,3915.0,count,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c1,A1,1,17,Hbath,bathrooms,A_structural,level,count,0.126607,0.026258,,,,,,high,Number of half bathrooms. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,1033.0,0.8296,se,Pre-project cross-section (Aug 2010-Jul 2011); month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,12.6607,2.6258,100*b/1 (per unit count),reported,0.14906602851855724,0.030915950751856346,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.821654352959098,1023.0,count,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,Hbath,bathrooms,A_structural,level,count,0.124649,0.011963,,,,,,high,Number of half bathrooms. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,12.4649,1.1963,100*b/1 (per unit count),reported,0.16426426062803928,0.015765014961156797,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.419543592744295,3915.0,count,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,17,Hbath,bathrooms,A_structural,level,count,0.125128,0.011927,,,,,,high,Number of half bathrooms. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,12.512799999999999,1.1927,100*b/1 (per unit count),reported,0.1653624397490031,0.015762082178939648,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.49115452335038,3915.0,count,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c1,A1,1,17,Age,age,A_structural,level,years,-0.012805,0.002421,,,,,,high,"Age of property (2018 - year built), quadratic. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.",ln sale price (USD),log,OLS,1033.0,0.8296,se,Pre-project cross-section (Aug 2010-Jul 2011); month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,-1.2805,0.2421,100*b/1 (per year),reported,-0.16315057451065418,0.030846352275696508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.289136720363486,1023.0,years,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,Age,age,A_structural,level,years,-0.011156,0.001245,,,,,,high,"Age of property (2018 - year built), quadratic. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.",ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,-1.1156,0.1245,100*b/1 (per year),reported,-0.14176363178942164,0.015820699316764966,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.960642570281124,3915.0,years,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,17,Age,age,A_structural,level,years,-0.011028,0.001255,,,,,,high,"Age of property (2018 - year built), quadratic. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.",ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,-1.1028,0.1255,100*b/1 (per year),reported,-0.13907402634653993,0.01582679570773555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.787250996015935,3915.0,years,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,Waterfront,waterfront,C_exterior,binary,binary,0.987184,0.383445,,,,,,medium,Indicator for homes within 150 m of the water; magnitude in column 1 (4.50) is as printed and implausibly large. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,149.34541698499376,102.90385458087046,100*(exp(b - se^2/2) - 1),reported,0.04111135821333558,0.015968598306002186,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.574512641969513,3915.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,True
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,17,Waterfront,waterfront,C_exterior,binary,binary,0.98032,0.38374,,,,,,medium,Indicator for homes within 150 m of the water; magnitude in column 1 (4.50) is as printed and implausibly large. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,147.61174923986283,102.27856773337001,100*(exp(b - se^2/2) - 1),reported,0.04079465177402267,0.01596880576930335,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.554646375149841,3915.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c1,A1,1,17,Acres,lot_size,A_structural,level,acres,-11.70237,3.848793,,,,,,high,Acreage of lot (quadratic). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,1033.0,0.8296,se,Pre-project cross-section (Aug 2010-Jul 2011); month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,-0.28917186029199116,0.09510574624531556,100*b/4046.86 (X per acre->m2),reported,-0.09463633541169228,0.031124948645289235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0405298492280566,1023.0,acre,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,True
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,Acres,lot_size,A_structural,level,acres,-1.001644,0.705101,,,,,,high,Acreage of lot (quadratic). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,-0.024751162271429736,0.017423425157787973,100*b/4046.86 (X per acre->m2),reported,-0.022697826859662852,0.015977992596746086,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4205681171917215,3915.0,acre,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,17,Acres,lot_size,A_structural,level,acres,-1.014829,0.698689,,,,,,high,Acreage of lot (quadratic). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,semi_elasticity,-0.025076970716894194,0.017264981187191226,100*b/4046.86 (X per acre->m2),reported,-0.023207379116548934,0.015977805627906235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4524759943265173,3915.0,acre,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,True
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c1,A1,1,17,Cape Cod,architectural_style,H_ai_derived,binary,binary,0.153071,0.05142,,,,,,high,Assessor-classified Cape Cod style house (not AI-derived). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,1033.0,0.8296,se,Pre-project cross-section (Aug 2010-Jul 2011); month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,16.38680593376114,5.992526496000969,100*(exp(b - se^2/2) - 1),reported,0.09267232964992729,0.03113072489628513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9768767016725013,1023.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,Cape Cod,architectural_style,H_ai_derived,binary,binary,0.186078,0.017676,,,,,,high,Assessor-classified Cape Cod style house (not AI-derived). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,20.432805356516436,2.129102850989313,100*(exp(b - se^2/2) - 1),reported,0.16591429502256705,0.015760600816963292,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.527155465037337,3915.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,17,Cape Cod,architectural_style,H_ai_derived,binary,binary,0.188487,0.024864,,,,,,high,Assessor-classified Cape Cod style house (not AI-derived). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,20.704821896751756,3.0021325351612815,100*(exp(b - se^2/2) - 1),reported,0.12027634979710564,0.01586608711134049,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.5807191119691115,3915.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,True
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c1,A1,1,17,Colonial,architectural_style,H_ai_derived,binary,binary,0.145395,0.127,,,,,,high,Assessor-classified colonial style house (not AI-derived). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,1033.0,0.8296,se,Pre-project cross-section (Aug 2010-Jul 2011); month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,14.72072378645477,14.687502960415266,100*(exp(b - se^2/2) - 1),reported,0.03577090300616851,0.03124526071586644,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1448425196850394,1023.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,Colonial,architectural_style,H_ai_derived,binary,binary,-0.003397,0.052669,,,,,,high,Assessor-classified colonial style house (not AI-derived). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,-0.47725866227662506,5.249038695302065,100*(exp(b - se^2/2) - 1),reported,-0.0010307998821822851,0.01598210155862784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.06449714253165999,3915.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,17,Colonial,architectural_style,H_ai_derived,binary,binary,-0.007865,0.052892,,,,,,high,Assessor-classified colonial style house (not AI-derived). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,-0.9221005198128074,5.247763604224658,100*(exp(b - se^2/2) - 1),reported,-0.0023765208457507798,0.015982064917158326,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.1486992361793844,3915.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c1,A1,1,17,Condo,dwelling_type,A_structural,binary,binary,0.120879,0.048037,,,,,,high,Condominium indicator. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,1033.0,0.8296,se,Pre-project cross-section (Aug 2010-Jul 2011); month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,12.718708429307757,5.4209195205915774,100*(exp(b - se^2/2) - 1),reported,0.07843270917637929,0.0311689544975201,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5163727959697733,1023.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,Condo,dwelling_type,A_structural,binary,binary,0.081467,0.021277,,,,,,high,Condominium indicator. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,8.463187600630317,2.308293678105219,100*(exp(b - se^2/2) - 1),reported,0.06107926832256162,0.015952270147411147,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.828876251351224,3915.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,17,Condo,dwelling_type,A_structural,binary,binary,0.08111,0.021237,,,,,,high,Condominium indicator. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,8.424565344797074,2.303131803603789,100*(exp(b - se^2/2) - 1),reported,0.06092671835113499,0.01595241915451922,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8192776757545794,3915.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c1,A1,1,17,Ranch,architectural_style,H_ai_derived,binary,binary,-0.070964,0.084647,,,,,,high,Assessor-classified ranch style house (not AI-derived). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,1033.0,0.8296,se,Pre-project cross-section (Aug 2010-Jul 2011); month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,-7.183573977305802,7.884829327038894,100*(exp(b - se^2/2) - 1),reported,-0.026202308980416065,0.031254535373784996,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8383522156721444,1023.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,True
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,Ranch,architectural_style,H_ai_derived,binary,binary,0.142348,0.049215,,,,,,high,Assessor-classified ranch style house (not AI-derived). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,15.158233704622571,5.674380316569813,100*(exp(b - se^2/2) - 1),reported,0.046176868622587325,0.015965061604382467,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.892370212333638,3915.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,17,Ranch,architectural_style,H_ai_derived,binary,binary,0.162981,0.049872,,,,,,high,Assessor-classified ranch style house (not AI-derived). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,17.555149133089444,5.870005847643674,100*(exp(b - se^2/2) - 1),reported,0.052158219817880276,0.015960355739364253,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2679860442733397,3915.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c1,A1,1,17,DistancetoDowntown,cbd_distance,D_location,log,100 m,-0.256703,0.070046,,,,,,high,ln straight-line distance to downtown (hundreds of metres). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,1033.0,0.8296,se,Pre-project cross-section (Aug 2010-Jul 2011); month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,elasticity,-0.256703,0.070046,b (log-log),reported,-0.11383544046116843,0.031062033799928335,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.664777431973275,1023.0,100m,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,DistancetoDowntown,cbd_distance,D_location,log,100 m,-0.322434,0.038786,,,,,,high,ln straight-line distance to downtown (hundreds of metres). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,elasticity,-0.322434,0.038786,b (log-log),reported,-0.13170439190978614,0.015842890466306176,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.31315423090806,3915.0,100m,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c1,A1,1,17,DistancetoLake,water_proximity,E_environment,log,100 m,0.260477,0.130816,,,,,,high,ln straight-line distance to Lake Michigan (hundreds of metres). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,1033.0,0.8296,se,Pre-project cross-section (Aug 2010-Jul 2011); month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,elasticity,0.260477,0.130816,b (log-log),reported,0.06213420486956493,0.031204859331983265,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.991170804794521,1023.0,100m,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,True
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,17,DistancetoLake,water_proximity,E_environment,log,100 m,0.211159,0.088278,,,,,,high,ln straight-line distance to Lake Michigan (hundreds of metres). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,elasticity,0.211159,0.088278,b (log-log),reported,0.0382009453998449,0.015970444347659856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3919776161671087,3915.0,100m,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,17,DistancetoLake,water_proximity,E_environment,log,100 m,0.241554,0.092125,,,,,,high,ln straight-line distance to Lake Michigan (hundreds of metres). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,elasticity,0.241554,0.092125,b (log-log),reported,0.04186873680561891,0.015968095656530804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.622024423337856,3915.0,100m,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,18,Post,transaction_timing,G_market,binary,binary,-0.014117,0.01218,,,,,,high,Post-remediation period indicator (Dec 2015-Nov 2016 sales). Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,-1.4090956099514051,1.2009262923159043,100*(exp(b - se^2/2) - 1),reported,-0.01852058695773975,0.015979368785525975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.159031198686371,3915.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c3,A1,3,18,Post,transaction_timing,G_market,binary,binary,-0.014066,0.013048,,,,,,high,Post-remediation period indicator. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.,ln sale price (USD),log,OLS,3925.0,0.7971,se,Pre + post-project sales; Treated-segment x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,pct_premium,-1.405146861832085,1.2865751589914665,100*(exp(b - se^2/2) - 1),reported,-0.017226471642063163,0.015979738517392303,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0780196198651133,3915.0,binary,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b,9848e68efcee710bc05a55f8576e298c00f7e04b:TA1-c2,A1,2,18,ln distance to LP,water_quality,E_environment,log,100 m,0.014304,0.017707,,,,,,high,"ln distance to Lincoln Park remediation site (hundreds of metres), truncated to homes within 5 km. Standard errors in parentheses; * and ** indicate significance at 10% and 5% (Table 2/3 legend); Table A1 prints full coefficients without stars.",ln sale price (USD),log,OLS,3925.0,0.7966,se,Pre + post-project sales; Lincoln Park proximity x Post design; month + tract FE; same models as Table 2 (p.10) which reports only coefficients of interest with stars,elasticity,0.014304,0.017707,b (log-log),reported,0.012909530236735496,0.015980778236987934,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.807816117919467,3915.0,100m,,2022.0,United States,North America,High income,2010.0,2016.0,mixed,transaction,journal,True,True,unknown,,2013.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c1,2,1,10,Ln Rooms,bedrooms,A_structural,log,count (rooms excluding kitchen and bathrooms),0.5748,,21.73,,**,,,high,robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,401.0,0.7472,t,"Model 1: tourists, no geographical interaction terms (adj. R2)",elasticity,0.5748,0.026451909802116886,b (log-log),|b/t|,0.7396151467095151,0.03403659211732698,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.73,391.0,count,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c3,2,3,10,Ln Rooms,bedrooms,A_structural,log,count (rooms excluding kitchen and bathrooms),0.519,,14.56,,**,,,high,robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,105.0,0.8517,t,"Model 3: residents, no geographical interaction terms (adj. R2)",elasticity,0.519,0.035645604395604394,b (log-log),|b/t|,0.8309917537479088,0.057073609460708025,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.56,95.0,count,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c1,2,1,11,Ln Landscape-Quality (visibility-adjusted MACBETH score),view,E_environment,log,"index (visibility-adjusted MACBETH landscape-quality score, 10-110)",0.0449,,6.57,,**,,,high,Natural landscape quality score; robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,401.0,0.7472,t,"Model 1: tourists, no geographical interaction terms (adj. R2)",elasticity,0.0449,0.0068340943683409434,b (log-log),|b/t|,0.3153101960212747,0.04799241948573435,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.57,391.0,index,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,True
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c2,2,2,11,Ln Landscape-Quality (visibility-adjusted MACBETH score),view,E_environment,log,"index (visibility-adjusted MACBETH landscape-quality score, 10-110)",0.0225,,3.84,,**,,,high,Natural landscape quality score; robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,401.0,0.8151,t,"Model 2: tourists, Ln Rooms interacted with resort dummies (adj. R2)",elasticity,0.0225,0.005859375,b (log-log),|b/t|,0.19063573575140608,0.04964472285192866,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.84,391.0,index,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c3,2,3,11,Ln Landscape-Quality (visibility-adjusted MACBETH score),view,E_environment,log,"index (visibility-adjusted MACBETH landscape-quality score, 10-110)",0.0351,,4.28,,**,,,high,Natural landscape quality score; robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,105.0,0.8517,t,"Model 3: residents, no geographical interaction terms (adj. R2)",elasticity,0.0351,0.008200934579439252,b (log-log),|b/t|,0.40206248457180943,0.0939398328438807,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.28,95.0,index,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c4,2,4,11,Ln Landscape-Quality (visibility-adjusted MACBETH score),view,E_environment,log,"index (visibility-adjusted MACBETH landscape-quality score, 10-110)",0.0287,,2.67,,**,,,high,Natural landscape quality score; robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,105.0,0.8677,t,"Model 4: residents, Ln Rooms interacted with resort dummies (adj. R2)",elasticity,0.0287,0.010749063670411986,b (log-log),|b/t|,0.26420250696165765,0.09895224979837366,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.67,95.0,index,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c1,2,1,11,Ln Resort-Infrastructure,neighbourhood_amenities,F_neighbourhood,log,"index (share of the six resorts' total infrastructure, averaged over 7 types)",0.1297,,6.19,,**,,,high,"Resort-level infrastructure index (bars, sports stores, etc.); robust (Huber-White) t-value","ln monthly rent (CHF, incl. bills)",log,OLS,401.0,0.7472,t,"Model 1: tourists, no geographical interaction terms (adj. R2)",elasticity,0.1297,0.020953150242326333,b (log-log),|b/t|,0.2987459739865103,0.04826267754224722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.19,391.0,index,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c2,2,2,11,Ln Resort-Infrastructure,neighbourhood_amenities,F_neighbourhood,log,"index (share of the six resorts' total infrastructure, averaged over 7 types)",-0.026,,-0.54,,,,,high,"Resort-level infrastructure index (bars, sports stores, etc.); robust (Huber-White) t-value","ln monthly rent (CHF, incl. bills)",log,OLS,401.0,0.8151,t,"Model 2: tourists, Ln Rooms interacted with resort dummies (adj. R2)",elasticity,-0.026,0.04814814814814814,b (log-log),|b/t|,-0.02729879626926644,0.050553326424567474,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.54,391.0,index,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c3,2,3,11,Ln Resort-Infrastructure,neighbourhood_amenities,F_neighbourhood,log,"index (share of the six resorts' total infrastructure, averaged over 7 types)",0.1962,,0.82,,,,,high,"Resort-level infrastructure index (bars, sports stores, etc.); robust (Huber-White) t-value","ln monthly rent (CHF, incl. bills)",log,OLS,105.0,0.8517,t,"Model 3: residents, no geographical interaction terms (adj. R2)",elasticity,0.1962,0.23926829268292685,b (log-log),|b/t|,0.08383406365746704,0.10223666299691103,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.82,95.0,index,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,True
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c4,2,4,11,Ln Resort-Infrastructure,neighbourhood_amenities,F_neighbourhood,log,"index (share of the six resorts' total infrastructure, averaged over 7 types)",0.0156,,0.58,,,,,high,"Resort-level infrastructure index (bars, sports stores, etc.); robust (Huber-White) t-value","ln monthly rent (CHF, incl. bills)",log,OLS,105.0,0.8677,t,"Model 4: residents, Ln Rooms interacted with resort dummies (adj. R2)",elasticity,0.0156,0.02689655172413793,b (log-log),|b/t|,0.05940166515019167,0.10241666405205462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.58,95.0,index,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c1,2,1,11,Ln Distances-to-Infrastructure,neighbourhood_amenities,F_neighbourhood,log,"distance (sum of distances to ropeways, grocery stores and resort centre; unit not printed)",0.0428,,2.68,,**,,,high,Sum of distances to the resort's main infrastructures; positive sign = rents higher away from centre; robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,401.0,0.7472,t,"Model 1: tourists, no geographical interaction terms (adj. R2)",elasticity,0.0428,0.01597014925373134,b (log-log),|b/t|,0.1343054895033587,0.050113988620656226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.68,391.0,distance,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c2,2,2,11,Ln Distances-to-Infrastructure,neighbourhood_amenities,F_neighbourhood,log,"distance (sum of distances to ropeways, grocery stores and resort centre; unit not printed)",0.0001,,0.01,,,,,high,Sum of distances to the resort's main infrastructures; positive sign = rents higher away from centre; robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,401.0,0.8151,t,"Model 2: tourists, Ln Rooms interacted with resort dummies (adj. R2)",elasticity,0.0001,0.01,b (log-log),|b/t|,0.0005057216727538872,0.05057216727538871,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.01,391.0,distance,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c3,2,3,11,Ln Distances-to-Infrastructure,neighbourhood_amenities,F_neighbourhood,log,"distance (sum of distances to ropeways, grocery stores and resort centre; unit not printed)",0.1393,,2.63,,**,,,high,Sum of distances to the resort's main infrastructures; positive sign = rents higher away from centre; robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,105.0,0.8517,t,"Model 3: residents, no geographical interaction terms (adj. R2)",elasticity,0.1393,0.052965779467680614,b (log-log),|b/t|,0.26051494695599614,0.09905511291102516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.63,95.0,distance,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T2-c4,2,4,11,Ln Distances-to-Infrastructure,neighbourhood_amenities,F_neighbourhood,log,"distance (sum of distances to ropeways, grocery stores and resort centre; unit not printed)",0.1509,,2.91,,**,,,high,Sum of distances to the resort's main infrastructures; positive sign = rents higher away from centre; robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,105.0,0.8677,t,"Model 4: residents, Ln Rooms interacted with resort dummies (adj. R2)",elasticity,0.1509,0.051855670103092784,b (log-log),|b/t|,0.2860814852915927,0.09830978875999749,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.91,95.0,distance,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T4-c1,4,1,17,Ln Rooms,bedrooms,A_structural,log,count (rooms excluding kitchen and bathrooms),0.577,,25.76,,**,,,high,robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,506.0,0.827,t,"Model 5: joint tourists+residents, no geographical interaction terms; t-values in separate column; adj. pseudo-R2 0.8270 (R=1) / 0.7422 (T=1)",elasticity,0.577,0.022399068322981365,b (log-log),|b/t|,0.7564773863306632,0.029366358165010223,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.76,496.0,count,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T4-c1,4,1,17,Ln Landscape-Quality,view,E_environment,log,"index (visibility-adjusted MACBETH score, 10-110)",0.0417,,7.58,,**,,,high,robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,506.0,0.827,t,"Model 5: joint tourists+residents, no geographical interaction terms; t-values in separate column; adj. pseudo-R2 0.8270 (R=1) / 0.7422 (T=1)",elasticity,0.0417,0.00550131926121372,b (log-log),|b/t|,0.3222014560565706,0.042506788397964464,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.58,496.0,index,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T4-c2,4,2,17,Ln Landscape-Quality,view,E_environment,log,"index (visibility-adjusted MACBETH score, 10-110)",0.0249,,5.31,,**,,,high,95% CI 0.0157 to 0.0341 reported in text (p. 670); robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,506.0,0.8587,t,"Model 6: joint, with resort interactions for Ln Rooms; adj. pseudo-R2 0.8587 (R=1) / 0.8087 (T=1)",elasticity,0.0249,0.004689265536723164,b (log-log),|b/t|,0.23192503368016262,0.043677030824889385,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.31,496.0,index,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T4-c1,4,1,17,Ln Resort-Infrastructure,neighbourhood_amenities,F_neighbourhood,log,index (resort infrastructure share),0.1138,,6.39,,**,,,high,robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,506.0,0.827,t,"Model 5: joint tourists+residents, no geographical interaction terms; t-values in separate column; adj. pseudo-R2 0.8270 (R=1) / 0.7422 (T=1)",elasticity,0.1138,0.01780907668231612,b (log-log),|b/t|,0.2757919717646572,0.04315993298351443,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.39,496.0,index,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T4-c2,4,2,17,Ln Resort-Infrastructure,neighbourhood_amenities,F_neighbourhood,log,index (resort infrastructure share),-0.006,,-0.19,,,,,high,robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,506.0,0.8587,t,"Model 6: joint, with resort interactions for Ln Rooms; adj. pseudo-R2 0.8587 (R=1) / 0.8087 (T=1)",elasticity,-0.006,0.031578947368421054,b (log-log),|b/t|,-0.008530941401331125,0.044899691585953284,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.19,496.0,index,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df,9ba5bc20c4b8dd4891df1e9ed1d47b53aa5ee9df:T4-c1,4,1,17,Ln Distances-to-Infrastructure,neighbourhood_amenities,F_neighbourhood,log,"distance (sum of distances to ropeways, grocery, centre; unit not printed)",0.047,,3.11,,**,,,high,robust (Huber-White) t-value,"ln monthly rent (CHF, incl. bills)",log,OLS,506.0,0.827,t,"Model 5: joint tourists+residents, no geographical interaction terms; t-values in separate column; adj. pseudo-R2 0.8270 (R=1) / 0.7422 (T=1)",elasticity,0.047,0.015112540192926046,b (log-log),|b/t|,0.1383011822965704,0.044469833535874734,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.11,496.0,distance,,2008.0,Switzerland,Europe,High income,2003.0,2003.0,rental,rent,journal,False,False,robust,,2003.0,ols,journal,True,True,False
a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7:T2-c1,2,1,4,Area,living_area,A_structural,level,sqft,5e-05,,10.579,,,,,medium,"p printed as '< 0.0001'; Area of house in square feet; SE printed as '< 0.0001' (not recorded); Kaggle toy dataset of unverifiable provenance (compiled 'from various websites', published 2023; country/period unknown, paper labels it US)",log housing price (currency not stated; dataset labelled 'US'),log,OLS,544.0,0.697,none,"Full Kaggle 'Housing Price Prediction' dataset after removing 1 outlier (545 -> 544); adjusted R2 0.6896, RSE 0.2059; SE, t, p, VIF printed in columns",semi_elasticity,0.05381955208354861,0.005087395035783024,100*b/0.092903 (X per sqft->m2),|b/t|,0.41625249627793215,0.03934705513545062,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.579,534.0,sqft,,2024.0,United States,North America,High income,,,unknown,listing,conference,False,False,OLS,"random_forest (prediction comparison only, RMSE/MAPE; no marginal effects)",2021.0,ols,other,True,True,False
a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7:T2-c1,2,1,4,Bedrooms,bedrooms,A_structural,level,count,0.029,0.014,2.046,0.041,,,,medium,"Kaggle toy dataset of unverifiable provenance (compiled 'from various websites', published 2023; country/period unknown, paper labels it US)",log housing price (currency not stated; dataset labelled 'US'),log,OLS,544.0,0.697,none,"Full Kaggle 'Housing Price Prediction' dataset after removing 1 outlier (545 -> 544); adjusted R2 0.6896, RSE 0.2059; SE, t, p, VIF printed in columns",semi_elasticity,2.9000000000000004,1.4000000000000001,100*b/1 (per unit count),reported,0.088194069902095,0.04310560601275416,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.046,534.0,count,,2024.0,United States,North America,High income,,,unknown,listing,conference,False,False,OLS,"random_forest (prediction comparison only, RMSE/MAPE; no marginal effects)",2021.0,ols,other,True,True,False
a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7:T2-c1,2,1,4,Bathrooms,bathrooms,A_structural,level,count,0.262,0.02,8.121,,,,,medium,"p printed as '< 0.0001'; Kaggle toy dataset of unverifiable provenance (compiled 'from various websites', published 2023; country/period unknown, paper labels it US)",log housing price (currency not stated; dataset labelled 'US'),log,OLS,544.0,0.697,none,"Full Kaggle 'Housing Price Prediction' dataset after removing 1 outlier (545 -> 544); adjusted R2 0.6896, RSE 0.2059; SE, t, p, VIF printed in columns",semi_elasticity,26.200000000000003,2.0,100*b/1 (per unit count),reported,0.33155207453189395,0.04082650837728038,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.121,534.0,count,,2024.0,United States,North America,High income,,,unknown,listing,conference,False,False,OLS,"random_forest (prediction comparison only, RMSE/MAPE; no marginal effects)",2021.0,ols,other,True,True,False
a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7:T2-c1,2,1,4,Stories,storeys,A_structural,level,count,0.09,0.012,7.264,,,,,medium,"p printed as '< 0.0001'; Kaggle toy dataset of unverifiable provenance (compiled 'from various websites', published 2023; country/period unknown, paper labels it US)",log housing price (currency not stated; dataset labelled 'US'),log,OLS,544.0,0.697,none,"Full Kaggle 'Housing Price Prediction' dataset after removing 1 outlier (545 -> 544); adjusted R2 0.6896, RSE 0.2059; SE, t, p, VIF printed in columns",semi_elasticity,9.0,1.2,100*b/1 (per unit count),reported,0.2998772210509405,0.041282657083003924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.264,534.0,count,,2024.0,United States,North America,High income,,,unknown,listing,conference,False,False,OLS,"random_forest (prediction comparison only, RMSE/MAPE; no marginal effects)",2021.0,ols,other,True,True,False
a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7:T2-c1,2,1,4,Basement,basement,A_structural,binary,binary,0.091,0.021,4.293,,,,,medium,"p printed as '< 0.0001'; Kaggle toy dataset of unverifiable provenance (compiled 'from various websites', published 2023; country/period unknown, paper labels it US)",log housing price (currency not stated; dataset labelled 'US'),log,OLS,544.0,0.697,none,"Full Kaggle 'Housing Price Prediction' dataset after removing 1 outlier (545 -> 544); adjusted R2 0.6896, RSE 0.2059; SE, t, p, VIF printed in columns",pct_premium,9.502752506697544,2.3000649110427775,100*(exp(b - se^2/2) - 1),reported,0.1826511118644158,0.04254626411936077,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.293,534.0,binary,,2024.0,United States,North America,High income,,,unknown,listing,conference,False,False,OLS,"random_forest (prediction comparison only, RMSE/MAPE; no marginal effects)",2021.0,ols,other,True,True,False
a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7:T2-c1,2,1,4,Hot Water Heating,heating,A_structural,binary,binary,0.164,0.043,3.814,0.0002,,,,medium,"Hot water heating system; Kaggle toy dataset of unverifiable provenance (compiled 'from various websites', published 2023; country/period unknown, paper labels it US)",log housing price (currency not stated; dataset labelled 'US'),log,OLS,544.0,0.697,none,"Full Kaggle 'Housing Price Prediction' dataset after removing 1 outlier (545 -> 544); adjusted R2 0.6896, RSE 0.2059; SE, t, p, VIF printed in columns",pct_premium,17.712555931332474,5.066321554898705,100*(exp(b - se^2/2) - 1),reported,0.16284481176980894,0.0426965945909305,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.814,534.0,binary,,2024.0,United States,North America,High income,,,unknown,listing,conference,False,False,OLS,"random_forest (prediction comparison only, RMSE/MAPE; no marginal effects)",2021.0,ols,other,True,True,False
a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7:T2-c1,2,1,4,Airconditioning,air_conditioning,A_structural,binary,binary,0.173,0.021,8.298,,,,,medium,"p printed as '< 0.0001'; Kaggle toy dataset of unverifiable provenance (compiled 'from various websites', published 2023; country/period unknown, paper labels it US)",log housing price (currency not stated; dataset labelled 'US'),log,OLS,544.0,0.697,none,"Full Kaggle 'Housing Price Prediction' dataset after removing 1 outlier (545 -> 544); adjusted R2 0.6896, RSE 0.2059; SE, t, p, VIF printed in columns",pct_premium,18.860398900722064,2.4966188206764675,100*(exp(b - se^2/2) - 1),reported,0.3379608136949462,0.04072798429681202,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.298,534.0,binary,,2024.0,United States,North America,High income,,,unknown,listing,conference,False,False,OLS,"random_forest (prediction comparison only, RMSE/MAPE; no marginal effects)",2021.0,ols,other,True,True,False
a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7,a072fb43e67fcc553e457777f0c68324ace19eb7:T2-c1,2,1,4,Parking,parking,A_structural,level,count,0.044,0.011,3.872,,,,,medium,"p printed as '< 0.0001'; Number of parking spaces; Kaggle toy dataset of unverifiable provenance (compiled 'from various websites', published 2023; country/period unknown, paper labels it US)",log housing price (currency not stated; dataset labelled 'US'),log,OLS,544.0,0.697,none,"Full Kaggle 'Housing Price Prediction' dataset after removing 1 outlier (545 -> 544); adjusted R2 0.6896, RSE 0.2059; SE, t, p, VIF printed in columns",semi_elasticity,4.3999999999999995,1.0999999999999999,100*b/1 (per unit count),reported,0.16525407928059754,0.04267925601255102,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.872,534.0,count,,2024.0,United States,North America,High income,,,unknown,listing,conference,False,False,OLS,"random_forest (prediction comparison only, RMSE/MAPE; no marginal effects)",2021.0,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c1,3,1,25,house bedrooms,bedrooms,A_structural,level,count,0.01062,,1.09,,,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.697,t,"Full sample, linear in test score, neighbourhood (census block) controls and tax rate, no boundary FE",semi_elasticity,1.0619999999999998,0.9743119266055044,100*b/1 (per unit count),|b/t|,0.005544565872283473,0.005086757680994012,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.09,38646.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c2,3,2,25,house bedrooms,bedrooms,A_structural,level,count,0.01502,,1.52,,,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.699,t,"Full sample, quadratic in test score",semi_elasticity,1.502,0.9881578947368421,100*b/1 (per unit count),|b/t|,0.007731759412213918,0.0050866838238249465,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.52,38646.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c3,3,3,25,house bedrooms,bedrooms,A_structural,level,count,0.01575,,1.62,,,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.702,t,"Full sample, cubic in test score",semi_elasticity,1.575,0.9722222222222222,100*b/1 (per unit count),|b/t|,0.008240394319930455,0.005086663160450898,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.62,38646.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c1,3,1,25,house bathrooms,bathrooms,A_structural,level,count,0.14086,,4.75,,***,,,high,Quadratic in bathrooms (baths sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.697,t,"Full sample, linear in test score, neighbourhood (census block) controls and tax rate, no boundary FE",semi_elasticity,14.086000000000002,2.9654736842105267,100*b/1 (per unit count),|b/t|,0.02415542015154239,0.00508535161085103,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.75,38646.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c2,3,2,25,house bathrooms,bathrooms,A_structural,level,count,0.14413,,4.93,,***,,,high,Quadratic in bathrooms (baths sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.699,t,"Full sample, quadratic in test score",semi_elasticity,14.413,2.923529411764706,100*b/1 (per unit count),|b/t|,0.025070218617591785,0.005085237042107868,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.93,38646.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c3,3,3,25,house bathrooms,bathrooms,A_structural,level,count,0.13458,,4.44,,***,,,high,Quadratic in bathrooms (baths sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.702,t,"Full sample, cubic in test score",semi_elasticity,13.458,3.031081081081081,100*b/1 (per unit count),|b/t|,0.022579792948770522,0.005085538952425793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.44,38646.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c1,3,1,25,house age,age,A_structural,level,years,0.00065,,0.37,,,,,high,Quadratic in age (age sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.697,t,"Full sample, linear in test score, neighbourhood (census block) controls and tax rate, no boundary FE",semi_elasticity,0.065,0.17567567567567566,100*b/1 (per year),|b/t|,0.0018821259389689919,0.005086826862078357,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.37,38646.0,years,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c2,3,2,25,house age,age,A_structural,level,years,0.00057,,0.31,,,,,high,Quadratic in age (age sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.699,t,"Full sample, quadratic in test score",semi_elasticity,0.056999999999999995,0.18387096774193548,100*b/1 (per year),|b/t|,0.0015769171596462103,0.00508682954724584,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.31,38646.0,years,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c3,3,3,25,house age,age,A_structural,level,years,0.00123,,0.67,,,,,high,Quadratic in age (age sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.702,t,"Full sample, cubic in test score",semi_elasticity,0.123,0.1835820895522388,100*b/1 (per year),|b/t|,0.0034081602401521173,0.005086806328585249,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.67,38646.0,years,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c1,3,1,25,house lotarea,lot_size,A_structural,level,1000 sqft,0.00123,,4.21,,***,,,high,Lot area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.697,t,"Full sample, linear in test score, neighbourhood (census block) controls and tax rate, no boundary FE",semi_elasticity,0.0013239609812552957,0.00031448004305351443,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.021410669827542913,0.005085669792765538,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.21,38646.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c2,3,2,25,house lotarea,lot_size,A_structural,level,1000 sqft,0.0012,,4.27,,***,,,high,Lot area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.699,t,"Full sample, quadratic in test score",semi_elasticity,0.0012916692500051666,0.0003024986533969945,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.02171566713059185,0.00508563633034938,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.27,38646.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c3,3,3,25,house lotarea,lot_size,A_structural,level,1000 sqft,0.00119,,4.17,,***,,,high,Lot area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.702,t,"Full sample, cubic in test score",semi_elasticity,0.001280905339588457,0.000307171544265817,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.021207334965855248,0.005085691838334592,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.17,38646.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c1,3,1,25,house livingarea,living_area,A_structural,level,1000 sqft,0.45365,,20.02,,***,,,high,Internal living area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.697,t,"Full sample, linear in test score, neighbourhood (census block) controls and tax rate, no boundary FE",semi_elasticity,0.48830479605403654,0.024390848953748077,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.10131443968767803,0.005060661323060841,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.02,38646.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c2,3,2,25,house livingarea,living_area,A_structural,level,1000 sqft,0.44475,,17.35,,***,,,high,Internal living area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.699,t,"Full sample, quadratic in test score",semi_elasticity,0.47872491578316484,0.027592214166176642,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.08791487205472512,0.005067139599695972,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.35,38646.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c3,3,3,25,house livingarea,living_area,A_structural,level,1000 sqft,0.43526,,19.05,,***,,,high,Internal living area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.702,t,"Full sample, cubic in test score",semi_elasticity,0.4685099647977073,0.024593698939512198,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.09645241678338391,0.0050631189912537485,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.05,38646.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c1,3,1,25,house stories,storeys,A_structural,level,count,0.39693,,11.29,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.697,t,"Full sample, linear in test score, neighbourhood (census block) controls and tax rate, no boundary FE",semi_elasticity,39.693,3.515766164747564,100*b/1 (per unit count),|b/t|,0.057335900815049176,0.005078467742697004,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.29,38646.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,True
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c2,3,2,25,house stories,storeys,A_structural,level,count,0.38775,,10.58,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.699,t,"Full sample, quadratic in test score",semi_elasticity,38.775,3.6649338374291114,100*b/1 (per unit count),|b/t|,0.0537409506775155,0.005079484941164036,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.58,38646.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T3-c3,3,3,25,house stories,storeys,A_structural,level,count,0.37835,,10.87,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,38656.0,0.702,t,"Full sample, cubic in test score",semi_elasticity,37.835,3.4806807727690896,100*b/1 (per unit count),|b/t|,0.05520957102610711,0.005079077371307003,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.87,38646.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c1,5,1,27,house bedrooms,bedrooms,A_structural,level,count,0.03726,,3.88,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.769,t,"Boundary sample (houses within 0.1 mile of elementary attendance-zone boundaries), linear, boundary FE, no neighbourhood controls",semi_elasticity,3.726,0.9603092783505155,100*b/1 (per unit count),|b/t|,0.038427041717471064,0.009903876731306976,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.88,10180.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c2,5,2,27,house bedrooms,bedrooms,A_structural,level,count,0.0373,,3.89,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.77,t,"Boundary sample, quadratic, boundary FE, no neighbourhood controls",semi_elasticity,3.73,0.9588688946015423,100*b/1 (per unit count),|b/t|,0.038525933675398645,0.00990383899110505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.89,10180.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c3,5,3,27,house bedrooms,bedrooms,A_structural,level,count,0.03749,,3.9,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.77,t,"Boundary sample, cubic, boundary FE, no neighbourhood controls",semi_elasticity,3.749,0.9612820512820512,100*b/1 (per unit count),|b/t|,0.038624824501352135,0.009903801154192855,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9,10180.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c4,5,4,27,house bedrooms,bedrooms,A_structural,level,count,0.03816,,4.02,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, linear, boundary FE, with neighbourhood controls and tax",semi_elasticity,3.816,0.9492537313432837,100*b/1 (per unit count),|b/t|,0.03982705246703697,0.009907226981849995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.02,10172.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c5,5,5,27,house bedrooms,bedrooms,A_structural,level,count,0.03805,,4.01,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, quadratic, boundary FE, with neighbourhood controls",semi_elasticity,3.805,0.9488778054862843,100*b/1 (per unit count),|b/t|,0.03972813676010828,0.009907266024964658,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.01,10172.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c6,5,6,27,house bedrooms,bedrooms,A_structural,level,count,0.03809,,4.0,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, cubic, boundary FE, with neighbourhood controls",semi_elasticity,3.8089999999999997,0.9522499999999999,100*b/1 (per unit count),|b/t|,0.039629219885184266,0.009907304971296067,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,10172.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c1,5,1,27,house bathrooms,bathrooms,A_structural,level,count,0.10834,,5.78,,***,,,high,Quadratic in bathrooms (baths sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.769,t,"Boundary sample (houses within 0.1 mile of elementary attendance-zone boundaries), linear, boundary FE, no neighbourhood controls",semi_elasticity,10.834000000000001,1.8743944636678203,100*b/1 (per unit count),|b/t|,0.05719294886246734,0.009894973851637949,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.78,10180.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c2,5,2,27,house bathrooms,bathrooms,A_structural,level,count,0.10785,,5.8,,***,,,high,Quadratic in bathrooms (baths sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.77,t,"Boundary sample, quadratic, boundary FE, no neighbourhood controls",semi_elasticity,10.785,1.8594827586206897,100*b/1 (per unit count),|b/t|,0.05739019765101756,0.009894861663968545,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.8,10180.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c3,5,3,27,house bathrooms,bathrooms,A_structural,level,count,0.10792,,5.82,,***,,,high,Quadratic in bathrooms (baths sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.77,t,"Boundary sample, cubic, boundary FE, no neighbourhood controls",semi_elasticity,10.792,1.854295532646048,100*b/1 (per unit count),|b/t|,0.057587439719005186,0.009894749092612575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.82,10180.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c4,5,4,27,house bathrooms,bathrooms,A_structural,level,count,0.10349,,5.81,,***,,,high,Quadratic in bathrooms (baths sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, linear, boundary FE, with neighbourhood controls and tax",semi_elasticity,10.349,1.781239242685026,100*b/1 (per unit count),|b/t|,0.05751134703252018,0.00989868279389332,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.81,10172.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c5,5,5,27,house bathrooms,bathrooms,A_structural,level,count,0.10318,,5.82,,***,,,high,Quadratic in bathrooms (baths sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, quadratic, boundary FE, with neighbourhood controls",semi_elasticity,10.318,1.7728522336769759,100*b/1 (per unit count),|b/t|,0.05761000561312009,0.009898626394006887,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.82,10172.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c6,5,6,27,house bathrooms,bathrooms,A_structural,level,count,0.1032,,5.83,,***,,,high,Quadratic in bathrooms (baths sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, cubic, boundary FE, with neighbourhood controls",semi_elasticity,10.32,1.7701543739279588,100*b/1 (per unit count),|b/t|,0.0577086625059034,0.009898569898096638,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.83,10172.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c1,5,1,27,house age,age,A_structural,level,years,-0.00408,,-2.73,,***,,,high,Quadratic in age (age sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.769,t,"Boundary sample (houses within 0.1 mile of elementary attendance-zone boundaries), linear, boundary FE, no neighbourhood controls",semi_elasticity,-0.40800000000000003,0.14945054945054947,100*b/1 (per year),|b/t|,-0.02704766881713674,0.009907570995288184,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.73,10180.0,years,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c2,5,2,27,house age,age,A_structural,level,years,-0.00411,,-2.75,,***,,,high,Quadratic in age (age sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.77,t,"Boundary sample, quadratic, boundary FE, no neighbourhood controls",semi_elasticity,-0.411,0.14945454545454545,100*b/1 (per year),|b/t|,-0.0272456736784359,0.009907517701249417,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.75,10180.0,years,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c3,5,3,27,house age,age,A_structural,level,years,-0.00412,,-2.76,,***,,,high,Quadratic in age (age sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.77,t,"Boundary sample, cubic, boundary FE, no neighbourhood controls",semi_elasticity,-0.41200000000000003,0.14927536231884062,100*b/1 (per year),|b/t|,-0.027344674907948674,0.009907490908677057,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.76,10180.0,years,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c4,5,4,27,house age,age,A_structural,level,years,-0.00453,,-3.11,,***,,,high,Quadratic in age (age sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, linear, boundary FE, with neighbourhood controls and tax",semi_elasticity,-0.453,0.14565916398713827,100*b/1 (per year),|b/t|,-0.03082129170109757,0.00991038318363266,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.11,10172.0,years,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c5,5,5,27,house age,age,A_structural,level,years,-0.00454,,-3.13,,***,,,high,Quadratic in age (age sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, quadratic, boundary FE, with neighbourhood controls",semi_elasticity,-0.45399999999999996,0.1450479233226837,100*b/1 (per year),|b/t|,-0.03101930925857279,0.009910322446828367,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.13,10172.0,years,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c6,5,6,27,house age,age,A_structural,level,years,-0.00454,,-3.14,,***,,,high,Quadratic in age (age sq also included),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, cubic, boundary FE, with neighbourhood controls",semi_elasticity,-0.45399999999999996,0.1445859872611465,100*b/1 (per year),|b/t|,-0.031118316669135608,0.009910291932845735,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.14,10172.0,years,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c1,5,1,27,house lotarea,lot_size,A_structural,level,1000 sqft,0.00089,,2.41,,**,,,high,Lot area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.769,t,"Boundary sample (houses within 0.1 mile of elementary attendance-zone boundaries), linear, boundary FE, no neighbourhood controls",semi_elasticity,0.0009579880270871652,0.00039750540543035897,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.023879173864643388,0.009908370898192277,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.41,10180.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c2,5,2,27,house lotarea,lot_size,A_structural,level,1000 sqft,0.00089,,2.41,,**,,,high,Lot area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.77,t,"Boundary sample, quadratic, boundary FE, no neighbourhood controls",semi_elasticity,0.0009579880270871652,0.00039750540543035897,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.023879173864643388,0.009908370898192277,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.41,10180.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c3,5,3,27,house lotarea,lot_size,A_structural,level,1000 sqft,0.00089,,2.41,,**,,,high,Lot area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.77,t,"Boundary sample, cubic, boundary FE, no neighbourhood controls",semi_elasticity,0.0009579880270871652,0.00039750540543035897,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.023879173864643388,0.009908370898192277,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.41,10180.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c4,5,4,27,house lotarea,lot_size,A_structural,level,1000 sqft,0.00088,,2.39,,**,,,high,Lot area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, linear, boundary FE, with neighbourhood controls and tax",semi_elasticity,0.0009472241166704556,0.0003963280822888935,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.02369042326426138,0.009912310989230703,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.39,10172.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c5,5,5,27,house lotarea,lot_size,A_structural,level,1000 sqft,0.00088,,2.4,,**,,,high,Lot area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, quadratic, boundary FE, with neighbourhood controls",semi_elasticity,0.0009472241166704556,0.00039467671527935647,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.02378949039323981,0.00991228766384992,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4,10172.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c6,5,6,27,house lotarea,lot_size,A_structural,level,1000 sqft,0.00088,,2.39,,**,,,high,Lot area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, cubic, boundary FE, with neighbourhood controls",semi_elasticity,0.0009472241166704556,0.0003963280822888935,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.02369042326426138,0.009912310989230703,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.39,10172.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c1,5,1,27,house livingarea,living_area,A_structural,level,1000 sqft,0.35315,,15.43,,***,,,high,Internal living area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.769,t,"Boundary sample (houses within 0.1 mile of elementary attendance-zone boundaries), linear, boundary FE, no neighbourhood controls",semi_elasticity,0.3801274963661039,0.024635612207783784,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.15117221619598556,0.00979729204121747,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.43,10180.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c2,5,2,27,house livingarea,living_area,A_structural,level,1000 sqft,0.35228,,15.29,,***,,,high,Internal living area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.77,t,"Boundary sample, quadratic, boundary FE, no neighbourhood controls",semi_elasticity,0.3791910361598501,0.02479993696271093,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.14983152527233068,0.00979931492951803,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.29,10180.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c3,5,3,27,house livingarea,living_area,A_structural,level,1000 sqft,0.35236,,15.29,,***,,,high,Internal living area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.77,t,"Boundary sample, cubic, boundary FE, no neighbourhood controls",semi_elasticity,0.3792771474431838,0.024805568832124508,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.14983152527233068,0.00979931492951803,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.29,10180.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c4,5,4,27,house livingarea,living_area,A_structural,level,1000 sqft,0.34332,,15.52,,***,,,high,Internal living area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, linear, boundary FE, with neighbourhood controls and tax",semi_elasticity,0.3695465724264782,0.023810990491396792,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.15209204009072286,0.00979974485120637,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.52,10172.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c5,5,5,27,house livingarea,living_area,A_structural,level,1000 sqft,0.34297,,15.49,,***,,,high,Internal living area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, quadratic, boundary FE, with neighbourhood controls",semi_elasticity,0.3691698355618933,0.02383278473608091,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.15180482912157642,0.009800182641806094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.49,10172.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c6,5,6,27,house livingarea,living_area,A_structural,level,1000 sqft,0.34301,,15.49,,***,,,high,Internal living area in thousands of square feet (Table 1),log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, cubic, boundary FE, with neighbourhood controls",semi_elasticity,0.3692128912035601,0.023835564312689485,100*b/92.903 (X per 1000sqft->m2),|b/t|,0.15180482912157642,0.009800182641806094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.49,10172.0,1000sqft,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c1,5,1,27,house stories,storeys,A_structural,level,count,0.27574,,9.3,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.769,t,"Boundary sample (houses within 0.1 mile of elementary attendance-zone boundaries), linear, boundary FE, no neighbourhood controls",semi_elasticity,27.573999999999998,2.9649462365591397,100*b/1 (per unit count),|b/t|,0.09178505115932917,0.009869360339712812,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.3,10180.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c2,5,2,27,house stories,storeys,A_structural,level,count,0.27559,,9.3,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.77,t,"Boundary sample, quadratic, boundary FE, no neighbourhood controls",semi_elasticity,27.559,2.963333333333333,100*b/1 (per unit count),|b/t|,0.09178505115932917,0.009869360339712812,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.3,10180.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c3,5,3,27,house stories,storeys,A_structural,level,count,0.27558,,9.31,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10190.0,0.77,t,"Boundary sample, cubic, boundary FE, no neighbourhood controls",semi_elasticity,27.558,2.9600429645542428,100*b/1 (per unit count),|b/t|,0.09188291198869973,0.009869270890300721,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.31,10180.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c4,5,4,27,house stories,storeys,A_structural,level,count,0.26621,,9.55,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, linear, boundary FE, with neighbourhood controls and tax",semi_elasticity,26.621,2.7875392670157066,100*b/1 (per unit count),|b/t|,0.09426748545715484,0.00987094088556595,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.55,10172.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c5,5,5,27,house stories,storeys,A_structural,level,count,0.26625,,9.57,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, quadratic, boundary FE, with neighbourhood controls",semi_elasticity,26.625,2.782131661442006,100*b/1 (per unit count),|b/t|,0.09446314447474644,0.009870756998406104,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.57,10172.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636,a2a7539a9c4a1cf05650ab56eedb83ae824bb636:T5-c6,5,6,27,house stories,storeys,A_structural,level,count,0.26626,,9.57,,***,,,high,,log adj price: log of sale price deflated to 1998 US$ (OFHEO St. Louis index),log,OLS,10182.0,0.772,t,"Boundary sample, cubic, boundary FE, with neighbourhood controls",semi_elasticity,26.626,2.7822361546499477,100*b/1 (per unit count),|b/t|,0.09446314447474644,0.009870756998406104,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.57,10172.0,count,,2003.0,United States,North America,High income,1998.0,2001.0,single_family,transaction,working_paper,False,True,clustered,,1999.5,ols,other,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2013,4,2013,9,Log (size),living_area,A_structural,log,m2,0.664,,,2e-09,,,,high,natural log of structure size in m2; elasticity; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2013 (training split 70%); gamma GLM log link; deviance explained 0.89,elasticity,0.664,0.11070712984571564,b (log-log),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,m2,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2014,4,2014,9,Log (size),living_area,A_structural,log,m2,0.626,,,2e-09,,,,high,natural log of structure size in m2; elasticity; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2014 (training split 70%); gamma GLM log link; deviance explained 0.87,elasticity,0.626,0.10437148084852106,b (log-log),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,m2,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2015,4,2015,9,Log (size),living_area,A_structural,log,m2,0.558,,,2e-09,,,,high,natural log of structure size in m2; elasticity; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2015 (training split 70%); gamma GLM log link; deviance explained 0.87,elasticity,0.558,0.09303400369564657,b (log-log),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,m2,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2016,4,2016,9,Log (size),living_area,A_structural,log,m2,0.479,,,2e-09,,,,high,natural log of structure size in m2; elasticity; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2016 (training split 70%); gamma GLM log link; deviance explained 0.87,elasticity,0.479,0.07986252288568943,b (log-log),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,m2,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2017,4,2017,9,Log (size),living_area,A_structural,log,m2,0.512,,,2e-09,,,,high,natural log of structure size in m2; elasticity; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2017 (training split 70%); gamma GLM log link; deviance explained 0.88,elasticity,0.512,0.08536453385693735,b (log-log),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,m2,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2013,4,2013,9,Bedrooms,bedrooms,A_structural,level,count,0.003,,,0.313,,,,high,number of bedrooms; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2013 (training split 70%); gamma GLM log link; deviance explained 0.89,semi_elasticity,0.3,0.2973396691663207,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.0015658293383743241,0.0015519439248104679,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0089471103574519,415190.0,count,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2014,4,2014,9,Bedrooms,bedrooms,A_structural,level,count,0.017,,,2e-09,,,,high,number of bedrooms; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2014 (training split 70%); gamma GLM log link; deviance explained 0.87,semi_elasticity,1.7000000000000002,0.28343692882186233,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,count,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2015,4,2015,9,Bedrooms,bedrooms,A_structural,level,count,0.021,,,2e-09,,,,high,number of bedrooms; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2015 (training split 70%); gamma GLM log link; deviance explained 0.87,semi_elasticity,2.1,0.3501279708975946,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,count,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2016,4,2016,9,Bedrooms,bedrooms,A_structural,level,count,0.034,,,2e-09,,,,high,number of bedrooms; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2016 (training split 70%); gamma GLM log link; deviance explained 0.87,semi_elasticity,3.4000000000000004,0.5668738576437247,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,count,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2017,4,2017,9,Bedrooms,bedrooms,A_structural,level,count,0.025,,,2e-09,,,,high,number of bedrooms; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2017 (training split 70%); gamma GLM log link; deviance explained 0.88,semi_elasticity,2.5,0.4168190129733269,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.009307868343879795,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.997807015007687,415190.0,count,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2013,4,2013,9,Bathrooms,bathrooms,A_structural,level,count,0.111,,,2e-09,,,,high,number of bathrooms; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2013 (training split 70%); gamma GLM log link; deviance explained 0.89,semi_elasticity,11.1,1.8506764176015715,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,count,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2014,4,2014,9,Bathrooms,bathrooms,A_structural,level,count,0.096,,,2e-09,,,,high,number of bathrooms; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2014 (training split 70%); gamma GLM log link; deviance explained 0.87,semi_elasticity,9.6,1.6005850098175753,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,count,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2015,4,2015,9,Bathrooms,bathrooms,A_structural,level,count,0.112,,,2e-09,,,,high,number of bathrooms; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2015 (training split 70%); gamma GLM log link; deviance explained 0.87,semi_elasticity,11.200000000000001,1.8673491781205045,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,count,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2016,4,2016,9,Bathrooms,bathrooms,A_structural,level,count,0.117,,,2e-09,,,,high,number of bathrooms; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2016 (training split 70%); gamma GLM log link; deviance explained 0.87,semi_elasticity,11.700000000000001,1.9507129807151702,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,count,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2017,4,2017,9,Bathrooms,bathrooms,A_structural,level,count,0.112,,,2e-09,,,,high,number of bathrooms; only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2017 (training split 70%); gamma GLM log link; deviance explained 0.88,semi_elasticity,11.200000000000001,1.8673491781205045,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,count,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2013,4,2013,9,Cluster,dwelling_type,A_structural,dummy,binary,0.09,,,2e-09,,,,high,cluster home vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2013 (training split 70%); gamma GLM log link; deviance explained 0.89,pct_premium,9.405110600133915,1.6418615218372898,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2014,4,2014,9,Cluster,dwelling_type,A_structural,dummy,binary,0.136,,,2e-09,,,,high,cluster home vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2014 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,14.53874032418323,2.5978284586187463,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2015,4,2015,9,Cluster,dwelling_type,A_structural,dummy,binary,0.146,,,2e-09,,,,high,cluster home vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2015 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,15.68533939010026,2.816873617851803,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2016,4,2016,9,Cluster,dwelling_type,A_structural,dummy,binary,0.187,,,2e-09,,,,high,cluster home vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2016 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,20.504144943169187,3.7589122447622967,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2017,4,2017,9,Cluster,dwelling_type,A_structural,dummy,binary,0.187,,,2e-09,,,,high,cluster home vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2017 (training split 70%); gamma GLM log link; deviance explained 0.88,pct_premium,20.504144943169187,3.7589122447622967,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2013,4,2013,9,Duplex,dwelling_type,A_structural,dummy,binary,0.003,,,0.874,,,,high,duplex vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2013 (training split 70%); gamma GLM log link; deviance explained 0.89,pct_premium,0.28250389122423947,1.8974767570741184,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0002461071424419526,0.001551945780359029,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.15857972975384352,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2014,4,2014,9,Duplex,dwelling_type,A_structural,dummy,binary,0.025,,,0.104,,,,high,duplex vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2014 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,2.5193902547093305,1.5766671970944113,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.002523088672537373,0.0015519408875255647,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6257633862332344,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2015,4,2015,9,Duplex,dwelling_type,A_structural,dummy,binary,0.035,,,0.024,,,,high,duplex vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2015 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,3.5495209348074486,1.6058756890652666,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.003502920821377062,0.0015519363057893512,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2571292444862254,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2016,4,2016,9,Duplex,dwelling_type,A_structural,dummy,binary,0.086,,,2e-09,,,,high,duplex vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2016 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,8.969430485742592,1.5626268734510285,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2017,4,2017,9,Duplex,dwelling_type,A_structural,dummy,binary,0.079,,,2e-09,,,,high,duplex vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2017 (training split 70%); gamma GLM log link; deviance explained 0.88,pct_premium,8.211045146048402,1.4254233460601817,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2013,4,2013,9,House,dwelling_type,A_structural,dummy,binary,0.027,,,0.0003,,,,high,house vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2013 (training split 70%); gamma GLM log link; deviance explained 0.89,pct_premium,2.733915249184826,0.7672649744553345,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.005610661447841738,0.0015519213999101614,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.615300006924662,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2014,4,2014,9,House,dwelling_type,A_structural,dummy,binary,0.063,,,2e-09,,,,high,house vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2014 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,6.4968088307346905,1.118687058514607,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879795,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.997807015007687,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2015,4,2015,9,House,dwelling_type,A_structural,dummy,binary,0.103,,,2e-09,,,,high,house vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2015 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,10.832796853518945,1.9036060154843515,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.997807015007686,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2016,4,2016,9,House,dwelling_type,A_structural,dummy,binary,0.158,,,2e-09,,,,high,house vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2016 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,17.07598988560639,3.0851986117725168,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2017,4,2017,9,House,dwelling_type,A_structural,dummy,binary,0.141,,,2e-09,,,,high,house vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2017 (training split 70%); gamma GLM log link; deviance explained 0.88,pct_premium,15.11065222712662,2.70683726501395,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2013,4,2013,9,Simplex,dwelling_type,A_structural,dummy,binary,0.061,,,4e-05,,,,high,"simplex vs apartment (reference); p printed as '4-e5' (typo), read as 4e-5; only p-value printed","listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2013 (training split 70%); gamma GLM log link; deviance explained 0.89,pct_premium,6.27817089953473,1.5785065105075968,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.006374456398092487,0.0015519142963921974,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.10747965458625,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2014,4,2014,9,Simplex,dwelling_type,A_structural,dummy,binary,0.068,,,5e-07,,,,high,simplex vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2014 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,7.0267359265588025,1.4480762210905056,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.007800327916161132,0.0015518986124788757,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.026312836056685,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2015,4,2015,9,Simplex,dwelling_type,A_structural,dummy,binary,0.078,,,2e-09,,,,high,simplex vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2015 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,8.103124085412894,1.4059733360086846,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2016,4,2016,9,Simplex,dwelling_type,A_structural,dummy,binary,0.117,,,2e-09,,,,high,simplex vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2016 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,12.390557051317996,2.1928343633714644,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2017,4,2017,9,Simplex,dwelling_type,A_structural,dummy,binary,0.087,,,2e-09,,,,high,simplex vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2017 (training split 70%); gamma GLM log link; deviance explained 0.88,pct_premium,9.078192136446184,1.582378540990261,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2013,4,2013,9,Townhouse,dwelling_type,A_structural,dummy,binary,0.05,,,0.064,,,,high,townhouse vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2013 (training split 70%); gamma GLM log link; deviance explained 0.89,pct_premium,5.0888113546968095,2.8379292955779576,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0028744709279834167,0.0015519394158047815,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8521798587690466,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2014,4,2014,9,Townhouse,dwelling_type,A_structural,dummy,binary,0.063,,,2e-09,,,,high,townhouse vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2014 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,6.4968088307346905,1.118687058514607,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879795,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.997807015007687,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2015,4,2015,9,Townhouse,dwelling_type,A_structural,dummy,binary,0.077,,,2e-09,,,,high,townhouse vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2015 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,7.995307654566819,1.3865607825350088,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2016,4,2016,9,Townhouse,dwelling_type,A_structural,dummy,binary,0.09,,,2e-09,,,,high,townhouse vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2016 (training split 70%); gamma GLM log link; deviance explained 0.87,pct_premium,9.405110600133915,1.6418615218372898,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9978070150076865,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4,a7a83b631f85316bae926a6c965b325fb26c01c4:T4-2017,4,2017,9,Townhouse,dwelling_type,A_structural,dummy,binary,0.099,,,2e-09,,,,high,townhouse vs apartment (reference); only p-value printed,"listing price (ZAR), gamma GLM log link",log,other,415200.0,,p,Listings of year 2017 (training split 70%); gamma GLM log link; deviance explained 0.88,pct_premium,10.391590885529256,1.822375467947417,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009307868343879793,0.0015518785983926603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.997807015007686,415190.0,binary,,2019.0,South Africa,Africa,Upper middle income,2013.0,2017.0,mixed,listing,journal,False,True,unknown,autoencoder (H2O) used only for anomaly detection in data cleaning,2015.0,other,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c1,2,1,7,South,sunlight,E_environment,binary,binary,0.08,0.003,,,***,,,medium,indicator for south-facing orientation (access to sunlight); reference = other orientations; SE printed as negative in table (sign dropped),"log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.239,se,,pct_premium,8.328219289412232,0.3249861203024876,100*(exp(b - se^2/2) - 1),reported,0.13145844875624849,0.004929691828359318,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.666666666666668,40438.0,binary,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c2,2,2,7,South,sunlight,E_environment,binary,binary,0.066,0.003,,,***,,,medium,indicator for south-facing orientation (access to sunlight); reference = other orientations; SE printed as negative in table (sign dropped),"log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.239,se,,pct_premium,6.822191015658174,0.320468015149798,100*(exp(b - se^2/2) - 1),reported,0.10875375357194118,0.004943352435088236,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,40438.0,binary,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c3,2,3,7,South,sunlight,E_environment,binary,binary,0.067,0.003,,,***,,,medium,indicator for south-facing orientation (access to sunlight); reference = other orientations; SE printed as negative in table (sign dropped),"log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.234,se,,pct_premium,6.929066635577508,0.32078864345238006,100*(exp(b - se^2/2) - 1),reported,0.11038160897875766,0.004942460103526462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.333333333333336,40438.0,binary,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c4,2,4,7,South,sunlight,E_environment,binary,binary,0.071,0.006,,,***,,,medium,indicator for south-facing orientation (access to sunlight); reference = other orientations; SE printed as negative in table (sign dropped),"log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.372,se,,pct_premium,7.356190158021092,0.6441487355210145,100*(exp(b - se^2/2) - 1),reported,0.05874374510847941,0.004964260150012345,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.833333333333332,40438.0,binary,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c5,2,5,7,South,sunlight,E_environment,binary,binary,0.077,0.009,,,***,,,medium,indicator for south-facing orientation (access to sunlight); reference = other orientations; SE printed as negative in table (sign dropped),"log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.355,se,,pct_premium,7.999833557426395,0.9720378687533403,100*(exp(b - se^2/2) - 1),reported,0.04250702153776645,0.004968353166751923,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.555555555555555,40438.0,binary,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c6,2,6,7,South,sunlight,E_environment,binary,binary,0.072,0.002,,,***,,,medium,indicator for south-facing orientation (access to sunlight); reference = other orientations; SE printed as negative in table (sign dropped),"log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.479,se,,pct_premium,7.465319475527488,0.21493106881276272,100*(exp(b - se^2/2) - 1),reported,0.1762209324446923,0.004895025901241453,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),36.0,40438.0,binary,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c7,2,7,7,South,sunlight,E_environment,binary,binary,0.071,0.002,,,***,,,medium,indicator for south-facing orientation (access to sunlight); reference = other orientations; SE printed as negative in table (sign dropped),log price (column 7 adds Area as control; table header still says unit price but note implies total price - ambiguous),log,OLS,40448.0,0.421,se,,pct_premium,7.35790787080528,0.2147162451736715,100*(exp(b - se^2/2) - 1),reported,0.17384789586618524,0.004897123827216487,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.49999999999999,40438.0,binary,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c1,2,1,7,Age,age,A_structural,level,years,0.072,0.006,,,***,,,medium,"age of unit in years (mean 17.5); transformation not stated in paper, positive sign unusual; SE printed as negative in table (sign dropped)","log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.239,se,,semi_elasticity,7.199999999999999,0.6,100*b/1 (per year),reported,0.0595682062769542,0.004964017189746185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.999999999999998,40438.0,years,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c2,2,2,7,Age,age,A_structural,level,years,0.067,0.006,,,***,,,medium,"age of unit in years (mean 17.5); transformation not stated in paper, positive sign unusual; SE printed as negative in table (sign dropped)","log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.239,se,,semi_elasticity,6.7,0.6,100*b/1 (per year),reported,0.05544471485666451,0.004965198345372941,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.166666666666668,40438.0,years,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c3,2,3,7,Age,age,A_structural,level,years,0.081,0.006,,,***,,,medium,"age of unit in years (mean 17.5); transformation not stated in paper, positive sign unusual; SE printed as negative in table (sign dropped)","log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.234,se,,semi_elasticity,8.1,0.6,100*b/1 (per year),reported,0.06698267270274079,0.004961679459462281,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.5,40438.0,years,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,True
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c4,2,4,7,Age,age,A_structural,level,years,0.075,0.006,,,***,,,medium,"age of unit in years (mean 17.5); transformation not stated in paper, positive sign unusual; SE printed as negative in table (sign dropped)","log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.372,se,,semi_elasticity,7.5,0.6,100*b/1 (per year),reported,0.06204085181566509,0.004963268145253208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.5,40438.0,years,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,True
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c5,2,5,7,Age,age,A_structural,level,years,0.049,0.006,,,***,,,medium,"age of unit in years (mean 17.5); transformation not stated in paper, positive sign unusual; SE printed as negative in table (sign dropped)","log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.355,se,,semi_elasticity,4.9,0.6,100*b/1 (per year),reported,0.04057814124215719,0.0049687519888355755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.166666666666666,40438.0,years,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c6,2,6,7,Age,age,A_structural,level,years,0.025,0.005,,,***,,,medium,"age of unit in years (mean 17.5); transformation not stated in paper, positive sign unusual; SE printed as negative in table (sign dropped)","log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.479,se,,semi_elasticity,2.5,0.5,100*b/1 (per year),reported,0.02485655657397901,0.004971311314795801,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,40438.0,years,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:T2-c7,2,7,7,Age,age,A_structural,level,years,0.026,0.005,,,***,,,medium,"age of unit in years (mean 17.5); transformation not stated in paper, positive sign unusual; SE printed as negative in table (sign dropped)",log price (column 7 adds Area as control; table header still says unit price but note implies total price - ambiguous),log,OLS,40448.0,0.421,se,,semi_elasticity,2.6,0.5,100*b/1 (per year),reported,0.02585016720858074,0.0049711860016501425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.199999999999999,40438.0,years,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:TA2-c1,A2,1,11,South,sunlight,E_environment,binary,binary,0.067,0.003,,,***,,,high,indicator for south-facing orientation (access to sunlight); reference = other orientations; main effect in a model with interaction terms,"log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.644,se,,pct_premium,6.929066635577508,0.32078864345238006,100*(exp(b - se^2/2) - 1),reported,0.11038160897875766,0.004942460103526462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.333333333333336,40438.0,binary,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:TA2-c2,A2,2,11,South,sunlight,E_environment,binary,binary,0.071,0.006,,,***,,,high,indicator for south-facing orientation (access to sunlight); reference = other orientations; main effect in a model with interaction terms,"log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.643,se,,pct_premium,7.356190158021092,0.6441487355210145,100*(exp(b - se^2/2) - 1),reported,0.05874374510847941,0.004964260150012345,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.833333333333332,40438.0,binary,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:TA2-c3,A2,3,11,South,sunlight,E_environment,binary,binary,0.077,0.009,,,***,,,high,indicator for south-facing orientation (access to sunlight); reference = other orientations; main effect in a model with interaction terms,"log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.641,se,,pct_premium,7.999833557426395,0.9720378687533403,100*(exp(b - se^2/2) - 1),reported,0.04250702153776645,0.004968353166751923,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.555555555555555,40438.0,binary,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:TA2-c4,A2,4,11,South,sunlight,E_environment,binary,binary,0.072,0.002,,,***,,,high,indicator for south-facing orientation (access to sunlight); reference = other orientations; main effect in a model with interaction terms,"log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.642,se,,pct_premium,7.465319475527488,0.21493106881276272,100*(exp(b - se^2/2) - 1),reported,0.1762209324446923,0.004895025901241453,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),36.0,40438.0,binary,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:TA2-c1,A2,1,11,Age,age,A_structural,level,years,0.081,0.006,,,***,,,high,"age of unit in years (mean 17.5); transformation not stated in paper, positive sign unusual; main effect in a model with interaction terms","log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.644,se,,semi_elasticity,8.1,0.6,100*b/1 (per year),reported,0.06698267270274079,0.004961679459462281,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.5,40438.0,years,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,True
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:TA2-c2,A2,2,11,Age,age,A_structural,level,years,0.072,0.006,,,***,,,high,"age of unit in years (mean 17.5); transformation not stated in paper, positive sign unusual; main effect in a model with interaction terms","log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.643,se,,semi_elasticity,7.199999999999999,0.6,100*b/1 (per year),reported,0.0595682062769542,0.004964017189746185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.999999999999998,40438.0,years,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:TA2-c3,A2,3,11,Age,age,A_structural,level,years,0.047,0.006,,,***,,,high,"age of unit in years (mean 17.5); transformation not stated in paper, positive sign unusual; main effect in a model with interaction terms","log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.641,se,,semi_elasticity,4.7,0.6,100*b/1 (per year),reported,0.03892445329349993,0.004969079143851055,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.833333333333333,40438.0,years,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579,a7fe404df2e413395450e192cebe2f68aa921579:TA2-c4,A2,4,11,Age,age,A_structural,level,years,0.026,0.005,,,***,,,high,"age of unit in years (mean 17.5); transformation not stated in paper, positive sign unusual; main effect in a model with interaction terms","log(unit price per m2, 10,000 CNY/m2)",log,OLS,40448.0,0.642,se,,semi_elasticity,2.6,0.5,100*b/1 (per year),reported,0.02585016720858074,0.0049711860016501425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.199999999999999,40438.0,years,,2022.0,China,Asia,Upper middle income,2019.0,2021.0,condo_apartment,transaction,journal,True,True,clustered,,2020.0,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c1,2,1,24,ln (house area),living_area,A_structural,log,ping,0.904,0.003,,,***,,,high,Log of transaction area in pings (1 ping = 3.306 m2); elasticity,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy, county + year FE",elasticity,0.904,0.003,b (log-log),reported,0.4359511610810052,0.0014467405788086455,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),301.3333333333333,386968.0,pyeong,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c2,2,2,24,ln (house area),living_area,A_structural,log,ping,0.905,0.003,,,***,,,high,Log of transaction area in pings (1 ping = 3.306 m2); elasticity,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy, county-by-year FE",elasticity,0.905,0.003,b (log-log),reported,0.43634163210041366,0.0014464363495041335,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),301.6666666666667,386968.0,pyeong,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c3,2,3,24,ln (house area),living_area,A_structural,log,ping,0.904,0.003,,,***,,,high,Log of transaction area in pings (1 ping = 3.306 m2); elasticity,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy x effective tax rate, county + year FE",elasticity,0.904,0.003,b (log-log),reported,0.4359511610810052,0.0014467405788086455,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),301.3333333333333,386968.0,pyeong,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c4,2,4,24,ln (house area),living_area,A_structural,log,ping,0.905,0.003,,,***,,,high,Log of transaction area in pings (1 ping = 3.306 m2); elasticity,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy x effective tax rate, county-by-year FE",elasticity,0.905,0.003,b (log-log),reported,0.43634163210041366,0.0014464363495041335,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),301.6666666666667,386968.0,pyeong,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c1,2,1,24,Steel reinforced concrete,roof_materials,A_structural,binary,binary,0.0978,0.012,,,***,,,high,Exterior structure is steel reinforced concrete = 1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy, county + year FE",pct_premium,10.266282002805859,1.3232906575311254,100*(exp(b - se^2/2) - 1),reported,0.013100347396765036,0.001607404588560127,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.15,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c2,2,2,24,Steel reinforced concrete,roof_materials,A_structural,binary,binary,0.0967,0.012,,,***,,,high,Exterior structure is steel reinforced concrete = 1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy, county-by-year FE",pct_premium,10.145055779249379,1.3218358381052198,100*(exp(b - se^2/2) - 1),reported,0.01295302683848081,0.0016074076738549093,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.058333333333334,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c3,2,3,24,Steel reinforced concrete,roof_materials,A_structural,binary,binary,0.0978,0.012,,,***,,,high,Exterior structure is steel reinforced concrete = 1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy x effective tax rate, county + year FE",pct_premium,10.266282002805859,1.3232906575311254,100*(exp(b - se^2/2) - 1),reported,0.013100347396765036,0.001607404588560127,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.15,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c4,2,4,24,Steel reinforced concrete,roof_materials,A_structural,binary,binary,0.0967,0.012,,,***,,,high,Exterior structure is steel reinforced concrete = 1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy x effective tax rate, county-by-year FE",pct_premium,10.145055779249379,1.3218358381052198,100*(exp(b - se^2/2) - 1),reported,0.01295302683848081,0.0016074076738549093,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.058333333333334,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c1,2,1,24,Apartment,dwelling_type,A_structural,binary,binary,-0.209,0.003,,,***,,,high,Apartment-type unit = 1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy, county + year FE",pct_premium,-18.860841562693352,0.24341857069302344,100*(exp(b - se^2/2) - 1),reported,-0.11129635230575156,0.0015975552962548074,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-69.66666666666666,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c2,2,2,24,Apartment,dwelling_type,A_structural,binary,binary,-0.209,0.003,,,***,,,high,Apartment-type unit = 1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy, county-by-year FE",pct_premium,-18.860841562693352,0.24341857069302344,100*(exp(b - se^2/2) - 1),reported,-0.11129635230575156,0.0015975552962548074,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-69.66666666666666,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c3,2,3,24,Apartment,dwelling_type,A_structural,binary,binary,-0.209,0.003,,,***,,,high,Apartment-type unit = 1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy x effective tax rate, county + year FE",pct_premium,-18.860841562693352,0.24341857069302344,100*(exp(b - se^2/2) - 1),reported,-0.11129635230575156,0.0015975552962548074,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-69.66666666666666,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c4,2,4,24,Apartment,dwelling_type,A_structural,binary,binary,-0.209,0.003,,,***,,,high,Apartment-type unit = 1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy x effective tax rate, county-by-year FE",pct_premium,-18.860841562693352,0.24341857069302344,100*(exp(b - se^2/2) - 1),reported,-0.11129635230575156,0.0015975552962548074,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-69.66666666666666,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c1,2,1,24,Quarter 2,transaction_timing,G_market,dummy,binary,0.0206,0.007,,,***,,,high,Transaction in Q2 vs Q1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy, county + year FE",pct_premium,2.0788634875824608,0.7145695511526222,100*(exp(b - se^2/2) - 1),reported,0.004730715100605997,0.0016075245487496108,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9428571428571426,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c2,2,2,24,Quarter 2,transaction_timing,G_market,dummy,binary,0.02,0.007,,,***,,,high,Transaction in Q2 vs Q1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy, county-by-year FE",pct_premium,2.0176345400110485,0.714140938018729,100*(exp(b - se^2/2) - 1),reported,0.004592930232375474,0.001607525581331416,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.857142857142857,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c3,2,3,24,Quarter 2,transaction_timing,G_market,dummy,binary,0.0206,0.007,,,***,,,high,Transaction in Q2 vs Q1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy x effective tax rate, county + year FE",pct_premium,2.0788634875824608,0.7145695511526222,100*(exp(b - se^2/2) - 1),reported,0.004730715100605997,0.0016075245487496108,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9428571428571426,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c4,2,4,24,Quarter 2,transaction_timing,G_market,dummy,binary,0.02,0.007,,,***,,,high,Transaction in Q2 vs Q1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy x effective tax rate, county-by-year FE",pct_premium,2.0176345400110485,0.714140938018729,100*(exp(b - se^2/2) - 1),reported,0.004592930232375474,0.001607525581331416,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.857142857142857,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c1,2,1,24,Quarter 3,transaction_timing,G_market,dummy,binary,0.0148,0.006,,,***,,,high,Transaction in Q3 vs Q1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy, county + year FE",pct_premium,1.489179408699659,0.6089460373822223,100*(exp(b - se^2/2) - 1),reported,0.003965240417856927,0.0016075298991311867,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.466666666666667,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c2,2,2,24,Quarter 3,transaction_timing,G_market,dummy,binary,0.0143,0.006,,,**,,,high,Transaction in Q3 vs Q1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy, county-by-year FE",pct_premium,1.4384475030286614,0.608641640469101,100*(exp(b - se^2/2) - 1),reported,0.0038312815936792197,0.0016075307386066659,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3833333333333333,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c3,2,3,24,Quarter 3,transaction_timing,G_market,dummy,binary,0.0148,0.006,,,***,,,high,Transaction in Q3 vs Q1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy x effective tax rate, county + year FE",pct_premium,1.489179408699659,0.6089460373822223,100*(exp(b - se^2/2) - 1),reported,0.003965240417856927,0.0016075298991311867,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.466666666666667,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c4,2,4,24,Quarter 3,transaction_timing,G_market,dummy,binary,0.0143,0.006,,,**,,,high,Transaction in Q3 vs Q1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy x effective tax rate, county-by-year FE",pct_premium,1.4384475030286614,0.608641640469101,100*(exp(b - se^2/2) - 1),reported,0.0038312815936792197,0.0016075307386066659,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3833333333333333,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c1,2,1,24,Quarter 4,transaction_timing,G_market,dummy,binary,0.0475,0.006,,,***,,,high,Transaction in Q4 vs Q1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy, county + year FE",pct_premium,4.862732565954464,0.6291877206727712,100*(exp(b - se^2/2) - 1),reported,0.012725347956318255,0.0016074123734296742,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.916666666666667,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c2,2,2,24,Quarter 4,transaction_timing,G_market,dummy,binary,0.0468,0.006,,,***,,,high,Transaction in Q4 vs Q1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy, county-by-year FE",pct_premium,4.78935433853418,0.6287474433833294,100*(exp(b - se^2/2) - 1),reported,0.012537846212673094,0.0016074161811119353,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.8,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c3,2,3,24,Quarter 4,transaction_timing,G_market,dummy,binary,0.0475,0.006,,,***,,,high,Transaction in Q4 vs Q1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy x effective tax rate, county + year FE",pct_premium,4.862732565954464,0.6291877206727712,100*(exp(b - se^2/2) - 1),reported,0.012725347956318255,0.0016074123734296742,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.916666666666667,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T2-c4,2,4,24,Quarter 4,transaction_timing,G_market,dummy,binary,0.0468,0.006,,,***,,,high,Transaction in Q4 vs Q1,ln(transaction price),log,OLS,386978.0,0.6,se,"Houses transacted only once; tax dummy x effective tax rate, county-by-year FE",pct_premium,4.78935433853418,0.6287474433833294,100*(exp(b - se^2/2) - 1),reported,0.012537846212673094,0.0016074161811119353,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.8,386968.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,ols,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c1,3,1,26,Age,age,A_structural,level,years,-0.00353,0.007,,,,,,high,Years between construction and transaction; house fixed-effects model,ln(transaction price),log,FE_panel,26794.0,0.402,se,"Houses transacted more than once, short-term transactions only; tax dummy, county + year FE",semi_elasticity,-0.35300000000000004,0.7000000000000001,100*b/1 (per year),reported,-0.0030813205864771293,0.006110267451937649,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5042857142857143,26784.0,years,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c2,3,2,26,Age,age,A_structural,level,years,0.000662,0.006,,,,,,high,Years between construction and transaction; house fixed-effects model,ln(transaction price),log,FE_panel,26794.0,0.444,se,"Houses transacted more than once, short-term transactions only; tax dummy, county-by-year FE",semi_elasticity,0.06620000000000001,0.6,100*b/1 (per year),reported,0.0006741692227945397,0.006110295070645374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.11033333333333334,26784.0,years,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c3,3,3,26,Age,age,A_structural,level,years,-0.00273,0.006,,,,,,high,Years between construction and transaction; house fixed-effects model,ln(transaction price),log,FE_panel,26794.0,0.394,se,"Houses transacted more than once, short-term transactions only; tax dummy x effective tax rate, county + year FE",semi_elasticity,-0.27299999999999996,0.6,100*b/1 (per year),reported,-0.00278017414438929,0.006110272844811627,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.45499999999999996,26784.0,years,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c4,3,4,26,Age,age,A_structural,level,years,0.00119,0.006,,,,,,high,Years between construction and transaction; house fixed-effects model,ln(transaction price),log,FE_panel,26794.0,0.437,se,"Houses transacted more than once, short-term transactions only; tax dummy x effective tax rate, county-by-year FE",semi_elasticity,0.11900000000000001,0.6,100*b/1 (per year),reported,0.001211874574507864,0.006110291972308559,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.19833333333333333,26784.0,years,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c5,3,5,26,Age,age,A_structural,level,years,-0.00685,0.004,,,*,,,high,Years between construction and transaction; house fixed-effects model,ln(transaction price),log,FE_panel,29285.0,0.413,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy, county + year FE",semi_elasticity,-0.685,0.4,100*b/1 (per year),reported,-0.010008301417293374,0.005844263601339197,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7125,29275.0,years,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c6,3,6,26,Age,age,A_structural,level,years,-0.00368,0.004,,,,,,high,Years between construction and transaction; house fixed-effects model,ln(transaction price),log,FE_panel,29285.0,0.453,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy, county-by-year FE",semi_elasticity,-0.368,0.4,100*b/1 (per year),reported,-0.005376914087900153,0.005844471834674079,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.92,29275.0,years,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c7,3,7,26,Age,age,A_structural,level,years,-0.00624,0.003,,,*,,,high,Years between construction and transaction; house fixed-effects model,ln(transaction price),log,FE_panel,29285.0,0.406,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy x effective tax rate, county + year FE",semi_elasticity,-0.624,0.3,100*b/1 (per year),reported,-0.012155778962991573,0.0058441245014382555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.08,29275.0,years,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c8,3,8,26,Age,age,A_structural,level,years,-0.00332,0.003,,,,,,high,Years between construction and transaction; house fixed-effects model,ln(transaction price),log,FE_panel,29285.0,0.446,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy x effective tax rate, county-by-year FE",semi_elasticity,-0.332,0.3,100*b/1 (per year),reported,-0.006467840374171696,0.005844434073046713,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1066666666666667,29275.0,years,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c1,3,1,27,Apartment,dwelling_type,A_structural,binary,binary,0.0277,0.058,,,,,,high,Apartment-type unit = 1,ln(transaction price),log,FE_panel,26794.0,0.402,se,"Houses transacted more than once, short-term transactions only; tax dummy, county + year FE",pct_premium,2.6359422776782937,5.962905829537807,100*(exp(b - se^2/2) - 1),reported,0.0029181808836016895,0.006110270442198484,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4775862068965517,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c2,3,2,27,Apartment,dwelling_type,A_structural,binary,binary,0.0361,0.058,,,,,,high,Apartment-type unit = 1,ln(transaction price),log,FE_panel,26794.0,0.444,se,"Houses transacted more than once, short-term transactions only; tax dummy, county-by-year FE",pct_premium,3.5017153489705466,6.013205200102345,100*(exp(b - se^2/2) - 1),reported,0.003803105292557623,0.0061102522705911945,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6224137931034482,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c3,3,3,27,Apartment,dwelling_type,A_structural,binary,binary,0.0292,0.059,,,,,,high,Apartment-type unit = 1,ln(transaction price),log,FE_panel,26794.0,0.394,se,"Houses transacted more than once, short-term transactions only; tax dummy x effective tax rate, county + year FE",pct_premium,2.783998674482091,6.074819949904953,100*(exp(b - se^2/2) - 1),reported,0.0030240650979948677,0.006110268519921137,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.49491525423728816,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c4,3,4,27,Apartment,dwelling_type,A_structural,binary,binary,0.0374,0.059,,,,,,high,Apartment-type unit = 1,ln(transaction price),log,FE_panel,26794.0,0.437,se,"Houses transacted more than once, short-term transactions only; tax dummy x effective tax rate, county-by-year FE",pct_premium,3.6302925263442365,6.124838268330722,100*(exp(b - se^2/2) - 1),reported,0.0038732775147455154,0.006110250624865919,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6338983050847459,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c5,3,5,27,Apartment,dwelling_type,A_structural,binary,binary,0.0459,0.056,,,,,,high,Apartment-type unit = 1,ln(transaction price),log,FE_panel,29285.0,0.413,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy, county + year FE",pct_premium,4.532934662770827,5.863030369005819,100*(exp(b - se^2/2) - 1),reported,0.004790393876765919,0.0058444892614137565,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8196428571428572,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c6,3,6,27,Apartment,dwelling_type,A_structural,binary,binary,0.0488,0.058,,,,,,high,Apartment-type unit = 1,ln(transaction price),log,FE_panel,29285.0,0.453,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy, county-by-year FE",pct_premium,4.8245694774039505,6.0900599005027445,100*(exp(b - se^2/2) - 1),reported,0.004917429311834449,0.005844485657508157,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8413793103448276,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c7,3,7,27,Apartment,dwelling_type,A_structural,binary,binary,0.0479,0.056,,,,,,high,Apartment-type unit = 1,ln(transaction price),log,FE_panel,29285.0,0.406,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy x effective tax rate, county + year FE",pct_premium,4.7422097374126615,5.874768163625852,100*(exp(b - se^2/2) - 1),reported,0.004999120528544204,0.005844483290156063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8553571428571428,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c8,3,8,27,Apartment,dwelling_type,A_structural,binary,binary,0.0513,0.058,,,,,,high,Apartment-type unit = 1,ln(transaction price),log,FE_panel,29285.0,0.446,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy x effective tax rate, county-by-year FE",pct_premium,5.086958751028425,6.105304097560638,100*(exp(b - se^2/2) - 1),reported,0.005169340229338115,0.005844478232000208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8844827586206896,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c1,3,1,27,Quarter 2,transaction_timing,G_market,dummy,binary,-0.0156,0.031,,,,,,high,Transaction in Q2 vs Q1,ln(transaction price),log,FE_panel,26794.0,0.402,se,"Houses transacted more than once, short-term transactions only; tax dummy, county + year FE",pct_premium,-1.5951899005369308,3.052015254144373,100*(exp(b - se^2/2) - 1),reported,-0.003074844327432304,0.006110267573743683,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5032258064516129,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c2,3,2,27,Quarter 2,transaction_timing,G_market,dummy,binary,-0.0126,0.031,,,,,,high,Transaction in Q2 vs Q1,ln(transaction price),log,FE_panel,26794.0,0.444,se,"Houses transacted more than once, short-term transactions only; tax dummy, county-by-year FE",pct_premium,-1.2995322054391356,3.061185047719825,100*(exp(b - se^2/2) - 1),reported,-0.002483532192003624,0.006110277615247012,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4064516129032258,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c3,3,3,27,Quarter 2,transaction_timing,G_market,dummy,binary,-0.0156,0.031,,,,,,high,Transaction in Q2 vs Q1,ln(transaction price),log,FE_panel,26794.0,0.394,se,"Houses transacted more than once, short-term transactions only; tax dummy x effective tax rate, county + year FE",pct_premium,-1.5951899005369308,3.052015254144373,100*(exp(b - se^2/2) - 1),reported,-0.003074844327432304,0.006110267573743683,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5032258064516129,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c4,3,4,27,Quarter 2,transaction_timing,G_market,dummy,binary,-0.0124,0.031,,,,,,high,Transaction in Q2 vs Q1,ln(transaction price),log,FE_panel,26794.0,0.437,se,"Houses transacted more than once, short-term transactions only; tax dummy x effective tax rate, county-by-year FE",pct_premium,-1.2797901377392673,3.0617973459571517,100*(exp(b - se^2/2) - 1),reported,-0.00244411128348721,0.006110278208718025,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.39999999999999997,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c5,3,5,27,Quarter 2,transaction_timing,G_market,dummy,binary,-0.0106,0.03,,,,,,high,Transaction in Q2 vs Q1,ln(transaction price),log,FE_panel,29285.0,0.413,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy, county + year FE",pct_premium,-1.0989173002265318,2.9683679460667562,100*(exp(b - se^2/2) - 1),reported,-0.0020650721637720435,0.0058445438597321975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.35333333333333333,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c6,3,6,27,Quarter 2,transaction_timing,G_market,dummy,binary,-0.00312,0.03,,,,,,high,Transaction in Q2 vs Q1,ln(transaction price),log,FE_panel,29285.0,0.453,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy, county-by-year FE",pct_premium,-0.35636351264523025,2.9906545864261735,100*(exp(b - se^2/2) - 1),reported,-0.000607833745188551,0.005844555242197605,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.104,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c7,3,7,27,Quarter 2,transaction_timing,G_market,dummy,binary,-0.0104,0.03,,,,,,high,Transaction in Q2 vs Q1,ln(transaction price),log,FE_panel,29285.0,0.406,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy x effective tax rate, county + year FE",pct_premium,-1.0791351055330467,2.9689616790272866,100*(exp(b - se^2/2) - 1),reported,-0.002026108699528693,0.005844544325563538,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3466666666666667,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c8,3,8,27,Quarter 2,transaction_timing,G_market,dummy,binary,-0.00231,0.03,,,,,,high,Transaction in Q2 vs Q1,ln(transaction price),log,FE_panel,29285.0,0.446,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy x effective tax rate, county-by-year FE",pct_premium,-0.27561947016795374,2.9930779979903623,100*(exp(b - se^2/2) - 1),reported,-0.0004500307912119783,0.005844555730025692,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.077,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c1,3,1,27,Quarter 3,transaction_timing,G_market,dummy,binary,0.101,0.025,,,***,,,high,Transaction in Q3 vs Q1,ln(transaction price),log,FE_panel,26794.0,0.402,se,"Houses transacted more than once, short-term transactions only; tax dummy, county + year FE",pct_premium,10.59309843246603,2.765691604408559,100*(exp(b - se^2/2) - 1),reported,0.024678079691939706,0.006108435567311808,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.04,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c2,3,2,27,Quarter 3,transaction_timing,G_market,dummy,binary,0.0976,0.025,,,***,,,high,Transaction in Q3 vs Q1,ln(transaction price),log,FE_panel,26794.0,0.444,se,"Houses transacted more than once, short-term transactions only; tax dummy, county-by-year FE",pct_premium,10.217720402061437,2.7563042205493087,100*(exp(b - se^2/2) - 1),reported,0.023847813140349478,0.006108558693737059,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.904,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c3,3,3,27,Quarter 3,transaction_timing,G_market,dummy,binary,0.1,0.025,,,***,,,high,Transaction in Q3 vs Q1,ln(transaction price),log,FE_panel,26794.0,0.394,se,"Houses transacted more than once, short-term transactions only; tax dummy x effective tax rate, county + year FE",pct_premium,10.4825606121552,2.7629272951891193,100*(exp(b - se^2/2) - 1),reported,0.024433888871261047,0.006108472217815261,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c4,3,4,27,Quarter 3,transaction_timing,G_market,dummy,binary,0.0967,0.025,,,***,,,high,Transaction in Q3 vs Q1,ln(transaction price),log,FE_panel,26794.0,0.437,se,"Houses transacted more than once, short-term transactions only; tax dummy x effective tax rate, county-by-year FE",pct_premium,10.118569078487894,2.753824662719208,100*(exp(b - se^2/2) - 1),reported,0.02362802836949712,0.006108590581565957,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8679999999999994,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c5,3,5,27,Quarter 3,transaction_timing,G_market,dummy,binary,0.104,0.024,,,***,,,high,Transaction in Q3 vs Q1,ln(transaction price),log,FE_panel,29285.0,0.413,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy, county + year FE",pct_premium,10.928093599749955,2.663041091797398,100*(exp(b - se^2/2) - 1),reported,0.025318292110667162,0.005842682794769346,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.333333333333333,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c6,3,6,27,Quarter 3,transaction_timing,G_market,dummy,binary,0.102,0.024,,,***,,,high,Transaction in Q3 vs Q1,ln(transaction price),log,FE_panel,29285.0,0.453,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy, county-by-year FE",pct_premium,10.706459120907464,2.6577203321470404,100*(exp(b - se^2/2) - 1),reported,0.024831705042410345,0.005842754127625964,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.25,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c7,3,7,27,Quarter 3,transaction_timing,G_market,dummy,binary,0.103,0.025,,,***,,,high,Transaction in Q3 vs Q1,ln(transaction price),log,FE_panel,29285.0,0.406,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy x effective tax rate, county + year FE",pct_premium,10.814505963059041,2.771228522690018,100*(exp(b - se^2/2) - 1),reported,0.02407259410200236,0.005842862646117079,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.119999999999999,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c8,3,8,27,Quarter 3,transaction_timing,G_market,dummy,binary,0.102,0.024,,,***,,,high,Transaction in Q3 vs Q1,ln(transaction price),log,FE_panel,29285.0,0.446,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy x effective tax rate, county-by-year FE",pct_premium,10.706459120907464,2.6577203321470404,100*(exp(b - se^2/2) - 1),reported,0.024831705042410345,0.005842754127625964,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.25,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c1,3,1,27,Quarter 4,transaction_timing,G_market,dummy,binary,0.131,0.027,,,***,,,high,Transaction in Q4 vs Q1,ln(transaction price),log,FE_panel,26794.0,0.402,se,"Houses transacted more than once, short-term transactions only; tax dummy, county + year FE",pct_premium,13.95523387747042,3.077913009542374,100*(exp(b - se^2/2) - 1),reported,0.02963323372169805,0.006107613057143873,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.851851851851852,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c2,3,2,27,Quarter 4,transaction_timing,G_market,dummy,binary,0.131,0.027,,,***,,,high,Transaction in Q4 vs Q1,ln(transaction price),log,FE_panel,26794.0,0.444,se,"Houses transacted more than once, short-term transactions only; tax dummy, county-by-year FE",pct_premium,13.95523387747042,3.077913009542374,100*(exp(b - se^2/2) - 1),reported,0.02963323372169805,0.006107613057143873,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.851851851851852,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c3,3,3,27,Quarter 4,transaction_timing,G_market,dummy,binary,0.13,0.028,,,***,,,high,Transaction in Q4 vs Q1,ln(transaction price),log,FE_panel,26794.0,0.394,se,"Houses transacted more than once, short-term transactions only; tax dummy x effective tax rate, county + year FE",pct_premium,13.838205008538896,3.188719473308941,100*(exp(b - se^2/2) - 1),reported,0.028357824477013918,0.006107839118126074,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.642857142857143,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c4,3,4,27,Quarter 4,transaction_timing,G_market,dummy,binary,0.131,0.027,,,***,,,high,Transaction in Q4 vs Q1,ln(transaction price),log,FE_panel,26794.0,0.437,se,"Houses transacted more than once, short-term transactions only; tax dummy x effective tax rate, county-by-year FE",pct_premium,13.95523387747042,3.077913009542374,100*(exp(b - se^2/2) - 1),reported,0.02963323372169805,0.006107613057143873,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.851851851851852,26784.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c5,3,5,27,Quarter 4,transaction_timing,G_market,dummy,binary,0.133,0.026,,,***,,,high,Transaction in Q4 vs Q1,ln(transaction price),log,FE_panel,29285.0,0.413,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy, county + year FE",pct_premium,14.18639830717121,2.969849995660325,100*(exp(b - se^2/2) - 1),reported,0.029883800810680667,0.00584194602314058,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.115384615384616,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c6,3,6,27,Quarter 4,transaction_timing,G_market,dummy,binary,0.139,0.026,,,***,,,high,Transaction in Q4 vs Q1,ln(transaction price),log,FE_panel,29285.0,0.453,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy, county-by-year FE",pct_premium,14.873576169067594,2.9877226600093736,100*(exp(b - se^2/2) - 1),reported,0.031230655638697993,0.0058417053712672504,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.346153846153847,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c7,3,7,27,Quarter 4,transaction_timing,G_market,dummy,binary,0.133,0.027,,,***,,,high,Transaction in Q4 vs Q1,ln(transaction price),log,FE_panel,29285.0,0.406,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy x effective tax rate, county + year FE",pct_premium,14.183372407709417,3.0840749954934146,100*(exp(b - se^2/2) - 1),reported,0.028777927609201483,0.005842135680063459,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.9259259259259265,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,False
a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3,a842ed7c689fc0985af5ca73c3f97f4279427db3:T3-c8,3,8,27,Quarter 4,transaction_timing,G_market,dummy,binary,0.14,0.026,,,***,,,high,Transaction in Q4 vs Q1,ln(transaction price),log,FE_panel,29285.0,0.446,se,"Houses transacted more than once, whole (short- and long-term) transactions; tax dummy x effective tax rate, county-by-year FE",pct_premium,14.988507201175128,2.990711877028791,100*(exp(b - se^2/2) - 1),reported,0.03145511510287215,0.005841664233390541,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.384615384615385,29275.0,binary,,2025.0,Taiwan,Asia,High income,2012.0,2015.0,mixed,transaction,journal,True,True,unknown,,2013.5,panel,journal,True,True,True
a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7,a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7,a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7:T3-SVC,3,Mean mu_j,8,log (volume),living_area,A_structural,log,m3,0.5132,0.0222,,,***,,,high,"Building VOLUME in m3 (SIA Zurich 2003), not floor area; elasticity",log transaction price (CHF),log,other,1578.0,,se,Full sample; error variance tau2 = 0.0242,elasticity,0.5132,0.0222,b (log-log),reported,0.5041687060009393,0.02180932438273744,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.117117117117115,1568.0,m3,,2022.0,Switzerland,Europe,High income,2018.0,2019.0,single_family,transaction,journal,True,False,unknown,Gaussian process SVC,2018.5,other,journal,True,True,False
a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7,a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7,a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7:T3-SVC,3,Mean mu_j,8,log (plotsize),lot_size,A_structural,log,m2,0.172,0.0129,,,***,,,high,"Plot size m2, elasticity",log transaction price (CHF),log,other,1578.0,,se,Full sample; error variance tau2 = 0.0242,elasticity,0.172,0.0129,b (log-log),reported,0.31911282313630135,0.023933461735222605,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.333333333333332,1568.0,m2,,2022.0,Switzerland,Europe,High income,2018.0,2019.0,single_family,transaction,journal,True,False,unknown,Gaussian process SVC,2018.5,other,journal,True,True,False
a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7,a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7,a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7:T3-SVC,3,Mean mu_j,8,SFHtype 2,dwelling_type,A_structural,dummy,binary,-0.0062,0.012,,,n.s.,,,high,Semi-detached vs detached (reference),log transaction price (CHF),log,other,1578.0,,se,Full sample; error variance tau2 = 0.0242,pct_premium,-0.6252372064908585,1.1925830164081903,100*(exp(b - se^2/2) - 1),reported,-0.01304669317940572,0.02525166421820462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5166666666666666,1568.0,binary,,2022.0,Switzerland,Europe,High income,2018.0,2019.0,single_family,transaction,journal,True,False,unknown,Gaussian process SVC,2018.5,other,journal,True,True,False
a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7,a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7,a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7:T3-SVC,3,Mean mu_j,8,SFHtype3,dwelling_type,A_structural,dummy,binary,-0.0274,0.0165,,,.,,,high,Row house vs detached (reference); '.' = p<0.1,log transaction price (CHF),log,other,1578.0,,se,Full sample; error variance tau2 = 0.0242,pct_premium,-2.71604619096526,1.6054037585623042,100*(exp(b - se^2/2) - 1),reported,-0.041899807918440266,0.025231636155265125,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6606060606060606,1568.0,binary,,2022.0,Switzerland,Europe,High income,2018.0,2019.0,single_family,transaction,journal,True,False,unknown,Gaussian process SVC,2018.5,other,journal,True,True,False
a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7,a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7,a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7:T3-SVC,3,Mean mu_j,8,energy2,energy_efficiency,A_structural,dummy,binary,0.0119,0.0281,,,n.s.,,,high,Enhanced energy efficiency standard vs insulated shell (reference); only 40 obs,log transaction price (CHF),log,other,1578.0,,se,Full sample; error variance tau2 = 0.0242,pct_premium,1.1571634310588719,2.843638753619649,100*(exp(b - se^2/2) - 1),reported,0.01069406396107189,0.025252369521522697,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4234875444839858,1568.0,binary,,2022.0,Switzerland,Europe,High income,2018.0,2019.0,single_family,transaction,journal,True,False,unknown,Gaussian process SVC,2018.5,other,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c1,6,Model 1,30,Floor Area,living_area,A_structural,level,m2,0.007,,34.316,,***,,,high,,ln(transaction price),log,OLS,1478.0,0.674,t,Parsimonious OLS with continuous EPC score; spatial and temporal dummies included (not printed),semi_elasticity,0.7000000000000001,0.020398647861056066,100*b/1 (X per m2->m2),|b/t|,0.6671685489008392,0.01944190898999997,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.316,1468.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,Floor Area,living_area,A_structural,level,m2,0.007,,33.664,,***,,,high,,ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),semi_elasticity,0.7000000000000001,0.020793726235741442,100*b/1 (X per m2->m2),|b/t|,0.6600448214568297,0.019606844743845938,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.664,1468.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c1,6,Model 1,30,Terr,dwelling_type,A_structural,dummy,binary,-0.408,,-16.6,,***,,,high,Terraced =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.674,t,Parsimonious OLS with continuous EPC score; spatial and temporal dummies included (not printed),pct_premium,-33.52219455502006,1.634405919033373,100*(exp(b - se^2/2) - 1),|b/t|,-0.39754806094162787,0.02394867836997758,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.6,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,Terr,dwelling_type,A_structural,dummy,binary,-0.404,,-16.274,,***,,,high,Terraced =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,-33.25615730187623,1.6574181208839085,100*(exp(b - se^2/2) - 1),|b/t|,-0.39094412763243164,0.024022620599264573,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.274,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c1,6,Model 1,30,Detach,dwelling_type,A_structural,dummy,binary,0.102,,3.97,,***,,,high,Detached =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.674,t,Parsimonious OLS with continuous EPC score; spatial and temporal dummies included (not printed),pct_premium,10.701803204751958,2.845166602424413,100*(exp(b - se^2/2) - 1),|b/t|,0.10306436826049548,0.02596079805050264,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.97,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,Detach,dwelling_type,A_structural,dummy,binary,0.103,,3.973,,***,,,high,Detached =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,10.811896018590916,2.873763280514189,100*(exp(b - se^2/2) - 1),|b/t|,0.10314142243930326,0.025960589589555313,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.973,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c1,6,Model 1,30,Apt,dwelling_type,A_structural,dummy,binary,-0.092,,-2.453,,***,,,high,Apartment =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.674,t,Parsimonious OLS with continuous EPC score; spatial and temporal dummies included (not printed),pct_premium,-8.853612316137017,3.4208591014328706,100*(exp(b - se^2/2) - 1),|b/t|,-0.06389196885094872,0.026046461007317053,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.453,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,Apt,dwelling_type,A_structural,dummy,binary,-0.087,,-2.176,,***,,,high,Apartment =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,-8.405527945112734,3.6650233143421067,100*(exp(b - se^2/2) - 1),|b/t|,-0.05670176667077233,0.02605779718325934,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.176,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c1,6,Model 1,30,Pre1919,age,A_structural,dummy,construction period dummy,0.06,,1.732,,*,,,high,"Built pre-1919 =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.674,t,Parsimonious OLS with continuous EPC score; spatial and temporal dummies included (not printed),pct_premium,6.119959835337241,3.6784175977321922,100*(exp(b - se^2/2) - 1),|b/t|,0.045158715187530514,0.026073161193724315,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.732,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,Pre1919,age,A_structural,dummy,construction period dummy,0.064,,1.758,,*,,,high,"Built pre-1919 =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,6.538617362646337,3.8811099841146945,100*(exp(b - se^2/2) - 1),|b/t|,0.045835203706662296,0.026072357057259556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.758,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c1,6,Model 1,30,Early Modern,age,A_structural,dummy,construction period dummy,-0.029,,-1.279,,,,,high,"Early-modern construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.674,t,Parsimonious OLS with continuous EPC score; spatial and temporal dummies included (not printed),pct_premium,-2.883321024319363,2.2025861977741625,100*(exp(b - se^2/2) - 1),|b/t|,-0.03336304467768454,0.026085257762067666,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.279,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,Early Modern,age,A_structural,dummy,construction period dummy,-0.025,,-0.978,,,,,high,"Early-modern construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,-2.500868667666445,2.4931234970049405,100*(exp(b - se^2/2) - 1),|b/t|,-0.02551728060933998,0.026091288966605296,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.978,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c1,6,Model 1,30,Inter War,age,A_structural,dummy,construction period dummy,0.037,,1.442,,,,,high,"Inter-war construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.674,t,Parsimonious OLS with continuous EPC score; spatial and temporal dummies included (not printed),pct_premium,3.735148180284842,2.662596516713718,100*(exp(b - se^2/2) - 1),|b/t|,0.037609267050190014,0.02608132250359918,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.442,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,Inter War,age,A_structural,dummy,construction period dummy,0.041,,1.439,,,,,high,"Inter-war construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,4.142930643282083,2.9684458879336106,100*(exp(b - se^2/2) - 1),|b/t|,0.03753113341075769,0.02608139917356337,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.439,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c1,6,Model 1,30,No Garage,garage,A_structural,binary,binary,-0.019,,-0.971,,,,,high,Reverse-coded: no garage =1,ln(transaction price),log,OLS,1478.0,0.674,t,Parsimonious OLS with continuous EPC score; spatial and temporal dummies included (not printed),pct_premium,-1.9008459376579245,1.9199184225142443,100*(exp(b - se^2/2) - 1),|b/t|,-0.0253347592357099,0.02609141012946437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.971,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,No Garage,garage,A_structural,binary,binary,-0.028,,-1.134,,,,,high,Reverse-coded: no garage =1,ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,-2.790800270782734,2.4009589303734495,100*(exp(b - se^2/2) - 1),|b/t|,-0.029584204156082466,0.02608836345333551,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.134,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c1,6,Model 1,30,Gas Heat,heating,A_structural,binary,binary,0.132,,6.358,,***,,,high,Gas central heating =1,ln(transaction price),log,OLS,1478.0,0.674,t,Parsimonious OLS with continuous EPC score; spatial and temporal dummies included (not printed),pct_premium,14.08624201930424,2.369083015779727,100*(exp(b - se^2/2) - 1),|b/t|,0.16370380846815985,0.02574768928407673,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.358,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,Gas Heat,heating,A_structural,binary,binary,0.138,,6.048,,***,,,high,Gas central heating =1,ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,14.76767501838092,2.6193886563795745,100*(exp(b - se^2/2) - 1),|b/t|,0.15592091868937397,0.02578057518012136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.048,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,EPC Band G,energy_efficiency,A_structural,dummy,binary,-0.119,,-0.945,,,,,high,EPC band G dummy; reference band D,ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,-11.920350190981367,11.179801935520853,100*(exp(b - se^2/2) - 1),|b/t|,-0.02465680066675898,0.026091852557416913,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.945,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,EPC Band F,energy_efficiency,A_structural,dummy,binary,-0.035,,-0.956,,,,,high,EPC band F dummy; reference band D,ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,-3.5041494662738093,3.535166272909501,100*(exp(b - se^2/2) - 1),|b/t|,-0.024943633498107083,0.026091666839024145,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.956,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,EPC Band E,energy_efficiency,A_structural,dummy,binary,-0.003,,-0.114,,,,,high,EPC band E dummy; reference band D,ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,-0.3340667898234617,2.62369604079835,100*(exp(b - se^2/2) - 1),|b/t|,-0.002975362610333008,0.02609967202046498,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.114,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,EPC Band C,energy_efficiency,A_structural,dummy,binary,0.045,,1.145,,,,,high,EPC band C dummy; reference band D,ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,4.522032813580901,4.111026523658713,100*(exp(b - se^2/2) - 1),|b/t|,0.02987092132588901,0.026088140895972927,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.145,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T6-c2,6,Model 2,30,EPC Band B,energy_efficiency,A_structural,dummy,binary,0.088,,3.008,,***,,,high,EPC band B dummy; reference band D,ln(transaction price),log,OLS,1478.0,0.674,t,OLS with EPC band dummies (band D reference); spatial and temporal dummies included (not printed),pct_premium,9.1520920045437,3.194646101678237,100*(exp(b - se^2/2) - 1),|b/t|,0.07826732989837015,0.02601972403536242,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.008,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T7-c1,7,Model 3,31,Floor Area,living_area,A_structural,level,m2,0.007,,34.486,,***,,,high,,ln(transaction price),log,OLS,1478.0,0.673,t,OLS with property type x EPC interactions (interactions not extracted); main effects only,semi_elasticity,0.7000000000000001,0.020298091979353942,100*b/1 (X per m2->m2),|b/t|,0.6689964628689895,0.019399073910253133,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.486,1468.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T7-c1,7,Model 3,31,Terr,dwelling_type,A_structural,dummy,binary,-0.405,,-16.586,,***,,,high,Terraced =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.673,t,OLS with property type x EPC interactions (interactions not extracted); main effects only,pct_premium,-33.32220012029181,1.6286362498352958,100*(exp(b - se^2/2) - 1),|b/t|,-0.39726571239091635,0.02395186979325433,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.586,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T7-c1,7,Model 3,31,Detach,dwelling_type,A_structural,dummy,binary,0.103,,3.99,,***,,,high,Detached =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.673,t,OLS with property type x EPC interactions (interactions not extracted); main effects only,pct_premium,10.812212664714483,2.861519176311497,100*(exp(b - se^2/2) - 1),|b/t|,0.10357802767269904,0.02595940543175414,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.99,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T7-c1,7,Model 3,31,Apt,dwelling_type,A_structural,dummy,binary,-0.081,,-2.173,,**,,,high,Apartment =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.673,t,OLS with property type x EPC interactions (interactions not extracted); main effects only,pct_premium,-7.844676836936538,3.437537460055833,100*(exp(b - se^2/2) - 1),|b/t|,-0.05662384409588073,0.026057912607400237,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.173,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T7-c1,7,Model 3,31,Gas Heat,heating,A_structural,binary,binary,0.131,,6.277,,***,,,high,Gas central heating =1,ln(transaction price),log,OLS,1478.0,0.673,t,OLS with property type x EPC interactions (interactions not extracted); main effects only,pct_premium,13.97195516779217,2.3790947801795563,100*(exp(b - se^2/2) - 1),|b/t|,0.16167310089142775,0.025756428372061137,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.277,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T7-c1,7,Model 3,31,No Garage,garage,A_structural,binary,binary,-0.018,,-0.95,,,,,high,Reverse-coded: no garage =1,ln(transaction price),log,OLS,1478.0,0.673,t,OLS with property type x EPC interactions (interactions not extracted); main effects only,pct_premium,-1.8015251085306994,1.8609366928894118,100*(exp(b - se^2/2) - 1),|b/t|,-0.02478717998561971,0.026091768405915487,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.95,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T7-c2,7,Model 4,31,Floor Area,living_area,A_structural,level,m2,0.007,,34.61,,***,,,high,,ln(transaction price),log,OLS,1478.0,0.673,t,OLS with property age x EPC interactions (interactions not extracted); main effects only,semi_elasticity,0.7000000000000001,0.020225368390638543,100*b/1 (X per m2->m2),|b/t|,0.6703221550212739,0.01936787503673141,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.61,1468.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T7-c2,7,Model 4,31,Pre1919,age,A_structural,dummy,construction period dummy,0.058,,1.661,,,,,high,"Built pre-1919 =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.673,t,OLS with property age x EPC interactions (interactions not extracted); main effects only,pct_premium,5.906912821606425,3.7003895094037738,100*(exp(b - se^2/2) - 1),|b/t|,0.04331106737585808,0.026075296433388368,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.661,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T7-c2,7,Model 4,31,Early Modern,age,A_structural,dummy,construction period dummy,-0.029,,-1.285,,,,,high,"Early-modern construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.673,t,OLS with property age x EPC interactions (interactions not extracted); main effects only,pct_premium,-2.8830884390155354,2.1923017486016763,100*(exp(b - se^2/2) - 1),|b/t|,-0.033519380785964635,0.026085121234213724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.285,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T7-c2,7,Model 4,31,Inter War,age,A_structural,dummy,construction period dummy,0.039,,1.503,,,,,high,"Inter-war construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.673,t,OLS with property age x EPC interactions (interactions not extracted); main effects only,pct_premium,3.942050170466138,2.6980072430044015,100*(exp(b - se^2/2) - 1),|b/t|,0.039197832791135125,0.026079729069284848,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.503,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T7-c2,7,Model 4,31,Gas Heat,heating,A_structural,binary,binary,0.131,,6.276,,***,,,high,Gas central heating =1,ln(transaction price),log,OLS,1478.0,0.673,t,OLS with property age x EPC interactions (interactions not extracted); main effects only,pct_premium,13.971947257582752,2.379473858379075,100*(exp(b - se^2/2) - 1),|b/t|,0.16164801753284716,0.025756535617088457,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.276,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T7-c2,7,Model 4,31,No Garage,garage,A_structural,binary,binary,-0.018,,-0.947,,,,,high,Reverse-coded: no garage =1,ln(transaction price),log,OLS,1478.0,0.673,t,OLS with property age x EPC interactions (interactions not extracted); main effects only,pct_premium,-1.801636964953679,1.8668319516842042,100*(exp(b - se^2/2) - 1),|b/t|,-0.02470895254565685,0.026091818950007235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.947,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c1,8,Model 5,33,Floor Area,living_area,A_structural,level,m2,0.007,,33.83,,***,,,high,,ln(transaction price),log,OLS,1478.0,0.674,t,Partial regression model: predictor set A + EPC,semi_elasticity,0.7000000000000001,0.02069169376293231,100*b/1 (X per m2->m2),|b/t|,0.6618756946190412,0.019564755974550437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.83,1468.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c1,8,Model 5,33,Terr,dwelling_type,A_structural,dummy,binary,-0.407,,-16.47,,***,,,high,Terraced =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.674,t,Partial regression model: predictor set A + EPC,pct_premium,-33.45590208187753,1.6449130871446214,100*(exp(b - se^2/2) - 1),|b/t|,-0.39492191319528946,0.023978258238936827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.47,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c1,8,Model 5,33,Detach,dwelling_type,A_structural,dummy,binary,0.103,,3.987,,***,,,high,Detached =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.674,t,Partial regression model: predictor set A + EPC,pct_premium,10.81215708010539,2.863672313389233,100*(exp(b - se^2/2) - 1),|b/t|,0.10350098403369504,0.025959614756382005,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.987,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c1,8,Model 5,33,Apt,dwelling_type,A_structural,dummy,binary,-0.091,,-2.337,,**,,,high,Apartment =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.674,t,Partial regression model: predictor set A + EPC,pct_premium,-8.767419965302537,3.5551823573741195,100*(exp(b - se^2/2) - 1),|b/t|,-0.06088205539134681,0.026051371583802652,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.337,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c1,8,Model 5,33,Pre1919,age,A_structural,dummy,construction period dummy,0.063,,1.731,,*,,,high,"Built pre-1919 =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.674,t,Partial regression model: predictor set A + EPC,pct_premium,6.4321701895483585,3.8761808706858596,100*(exp(b - se^2/2) - 1),|b/t|,0.04513269515163727,0.026073191884250297,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.731,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c1,8,Model 5,33,Early Modern,age,A_structural,dummy,construction period dummy,-0.027,,-1.027,,,,,high,"Early-modern construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.674,t,Partial regression model: predictor set A + EPC,pct_premium,-2.6975080767235315,2.558982816081509,100*(exp(b - se^2/2) - 1),|b/t|,-0.026794857752785266,0.02609041650709374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.027,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c1,8,Model 5,33,Inter War,age,A_structural,dummy,construction period dummy,0.04,,1.385,,,,,high,"Inter-war construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.674,t,Partial regression model: predictor set A + EPC,pct_premium,4.037679224839819,3.00595169441845,100*(exp(b - se^2/2) - 1),|b/t|,0.03612461157532241,0.02608275203994398,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.385,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c1,8,Model 5,33,Gas Heat,heating,A_structural,binary,binary,0.129,,6.282,,***,,,high,Gas central heating =1,ln(transaction price),log,OLS,1478.0,0.674,t,Partial regression model: predictor set A + EPC,pct_premium,13.74502785598153,2.3362309139983983,100*(exp(b - se^2/2) - 1),|b/t|,0.16179851298323525,0.02575589191073468,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.282,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c2,8,Model 6,33,Floor Area,living_area,A_structural,level,m2,0.007,,35.798,,***,,,high,,ln(transaction price),log,OLS,1478.0,0.662,t,Partial regression model: floor area + type x EPC interactions (interactions not extracted),semi_elasticity,0.7000000000000001,0.01955416503715291,100*b/1 (X per m2->m2),|b/t|,0.6827035389247089,0.019070996673688723,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.798,1468.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c3,8,Model 7,33,Floor Area,living_area,A_structural,level,m2,0.007,,35.511,,***,,,high,,ln(transaction price),log,OLS,1478.0,0.671,t,Partial regression model: floor area + type x EPC interactions + gas heat (interactions not extracted),semi_elasticity,0.7000000000000001,0.019712201852946972,100*b/1 (X per m2->m2),|b/t|,0.6797647785253957,0.019142372181166278,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.511,1468.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c3,8,Model 7,33,Gas Heat,heating,A_structural,binary,binary,0.132,,6.428,,***,,,high,Gas central heating =1,ln(transaction price),log,OLS,1478.0,0.671,t,Partial regression model: floor area + type x EPC interactions + gas heat (interactions not extracted),pct_premium,14.08677460820571,2.343284040810128,100*(exp(b - se^2/2) - 1),|b/t|,0.16545706721258585,0.025740054015648082,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.428,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c4,8,Model 8,33,Floor Area,living_area,A_structural,level,m2,0.008,,45.47,,***,,,high,,ln(transaction price),log,OLS,1478.0,0.586,t,Partial regression model: floor area + age x EPC interactions + gas heat (interactions not extracted),semi_elasticity,0.8,0.017594018033868484,100*b/1 (X per m2->m2),|b/t|,0.764712606581649,0.01681795923865513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),45.47,1468.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c4,8,Model 8,33,Gas Heat,heating,A_structural,binary,binary,0.079,,3.698,,***,,,high,Gas central heating =1,ln(transaction price),log,OLS,1478.0,0.586,t,Partial regression model: floor area + age x EPC interactions + gas heat (interactions not extracted),pct_premium,8.195740558402886,2.3119021482843394,100*(exp(b - se^2/2) - 1),|b/t|,0.096070577277132,0.02597906362280476,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.698,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c5,8,Model 9,33,Floor Area,living_area,A_structural,level,m2,0.007,,34.19,,***,,,high,,ln(transaction price),log,OLS,1478.0,0.675,t,"Partial regression model: set A + EPC + coordinate polynomials (X*Y, Y*Y, X*X not extracted)",semi_elasticity,0.7000000000000001,0.02047382275519158,100*b/1 (X per m2->m2),|b/t|,0.6658059178151129,0.019473703358148957,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.19,1468.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c5,8,Model 9,33,Terr,dwelling_type,A_structural,dummy,binary,-0.408,,-16.597,,***,,,high,Terraced =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.675,t,"Partial regression model: set A + EPC + coordinate polynomials (X*Y, Y*Y, X*X not extracted)",pct_premium,-33.52220181460363,1.6347013469876481,100*(exp(b - se^2/2) - 1),|b/t|,-0.39748756718278133,0.023949362365655317,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.597,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c5,8,Model 9,33,Detach,dwelling_type,A_structural,dummy,binary,0.101,,3.916,,***,,,high,Detached =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.675,t,"Partial regression model: set A + EPC + coordinate polynomials (X*Y, Y*Y, X*X not extracted)",pct_premium,10.590875098129416,2.853267130186562,100*(exp(b - se^2/2) - 1),|b/t|,0.10167707703172993,0.025964524267551057,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.916,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c5,8,Model 9,33,Apt,dwelling_type,A_structural,dummy,binary,-0.094,,-2.513,,***,,,high,Apartment =1; reference semi-detached,ln(transaction price),log,OLS,1478.0,0.675,t,"Partial regression model: set A + EPC + coordinate polynomials (X*Y, Y*Y, X*X not extracted)",pct_premium,-9.035383558187638,3.404957407506252,100*(exp(b - se^2/2) - 1),|b/t|,-0.06544814195394888,0.026043828871448023,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.513,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c5,8,Model 9,33,Pre1919,age,A_structural,dummy,construction period dummy,0.134,,6.409,,***,,,high,"Built pre-1919 =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.675,t,"Partial regression model: set A + EPC + coordinate polynomials (X*Y, Y*Y, X*X not extracted)",pct_premium,14.3142930692155,2.390616911099746,100*(exp(b - se^2/2) - 1),|b/t|,0.1649813370540278,0.02574213403869992,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.409,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c5,8,Model 9,33,Early Modern,age,A_structural,dummy,construction period dummy,0.059,,1.699,,,,,high,"Early-modern construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.675,t,"Partial regression model: set A + EPC + coordinate polynomials (X*Y, Y*Y, X*X not extracted)",pct_premium,6.013583030426672,3.683680941946402,100*(exp(b - se^2/2) - 1),|b/t|,0.0443000057888295,0.02607416467853414,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.699,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c5,8,Model 9,33,Inter War,age,A_structural,dummy,construction period dummy,-0.029,,-1.288,,,,,high,"Inter-war construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,1478.0,0.675,t,"Partial regression model: set A + EPC + coordinate polynomials (X*Y, Y*Y, X*X not extracted)",pct_premium,-2.882973363168617,2.1871954557089706,100*(exp(b - se^2/2) - 1),|b/t|,-0.03359754791814423,0.02608505273147844,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.288,1468.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c5,8,Model 9,33,Gas Heat,heating,A_structural,binary,binary,0.036,,1.984,,**,,,high,Gas central heating =1,ln(transaction price),log,OLS,1478.0,0.675,t,"Partial regression model: set A + EPC + coordinate polynomials (X*Y, Y*Y, X*X not extracted)",pct_premium,3.648520268665467,1.8810287537133694,100*(exp(b - se^2/2) - 1),|b/t|,0.05171269439052915,0.02606486612425864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.984,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c6,8,Model 10,33,Floor Area,living_area,A_structural,level,m2,0.007,,34.573,,***,,,high,,ln(transaction price),log,OLS,1478.0,0.673,t,Partial regression model: floor area + type/age x EPC interactions + gas heat + coordinate polynomials (interactions not extracted),semi_elasticity,0.7000000000000001,0.020247013565499086,100*b/1 (X per m2->m2),|b/t|,0.669927255455896,0.019377180327304427,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.573,1468.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T8-c6,8,Model 10,33,Gas Heat,heating,A_structural,binary,binary,0.128,,6.249,,***,,,high,Gas central heating =1,ln(transaction price),log,OLS,1478.0,0.673,t,Partial regression model: floor area + type/age x EPC interactions + gas heat + coordinate polynomials (interactions not extracted),pct_premium,13.631459897301701,2.3280330348091494,100*(exp(b - se^2/2) - 1),|b/t|,0.16097064856407728,0.025759425278296895,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.249,1468.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c1,11,Model 13 (Base No lag),35,Floor Area,living_area,A_structural,level,m2,0.006611,,33.88551,,***,,,high,,ln(transaction price),log,OLS,961.0,0.614722,t,Base model on 961-observation subsample used for spatial lag models,semi_elasticity,0.6611,0.019509814076872387,100*b/1 (X per m2->m2),|b/t|,0.7395784415791967,0.021825802284787706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.88551,951.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c2,11,Model 14 (Base + Lag),35,Floor Area,living_area,A_structural,level,m2,0.006795,,28.6727,,***,,,high,,ln(transaction price),log,spatial_lag,961.0,0.673818,t,Spatial lag of price (inverse exponential distance weights) added; W*P coefficient 0.027939 (t 1.195744) not extracted,semi_elasticity,0.6795,0.023698500664395054,100*b/1 (X per m2->m2),|b/t|,0.6809246719881037,0.023748188066980223,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.6727,951.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c3,11,Model 15 (Base+Lag + EPC),35,Floor Area,living_area,A_structural,level,m2,0.006796,,28.72439,,***,,,high,,ln(transaction price),log,spatial_lag,961.0,0.675209,t,"Spatial lag of price and spatially lagged price x EPC term added (W*P 0.184266 t 2.273**, W*P*EPC -0.002952 t -2.0135** not extracted)",semi_elasticity,0.6796,0.023659336194780813,100*b/1 (X per m2->m2),|b/t|,0.6815822299801891,0.023728344796188502,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.72439,951.0,m2,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c1,11,Model 13 (Base No lag),35,Terr,dwelling_type,A_structural,dummy,binary,-0.398965,,-15.9981,,***,,,high,Terraced =1; reference semi-detached,ln(transaction price),log,OLS,961.0,0.614722,t,Base model on 961-observation subsample used for spatial lag models,pct_premium,-32.91944388571055,1.6733935585640018,100*(exp(b - se^2/2) - 1),|b/t|,-0.4604958387003762,0.02878440806723149,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.9981,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c2,11,Model 14 (Base + Lag),35,Terr,dwelling_type,A_structural,dummy,binary,-0.36092,,-11.5667,,***,,,high,Terraced =1; reference semi-detached,ln(transaction price),log,spatial_lag,961.0,0.673818,t,Spatial lag of price (inverse exponential distance weights) added; W*P coefficient 0.027939 (t 1.195744) not extracted,pct_premium,-30.330449241180023,2.1749832296546723,100*(exp(b - se^2/2) - 1),|b/t|,-0.3511857825749567,0.030361795721766505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.5667,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c3,11,Model 15 (Base+Lag + EPC),35,Terr,dwelling_type,A_structural,dummy,binary,-0.363045,,-11.64686,,***,,,high,Terraced =1; reference semi-detached,ln(transaction price),log,spatial_lag,961.0,0.675209,t,"Spatial lag of price and spatially lagged price x EPC term added (W*P 0.184266 t 2.273**, W*P*EPC -0.002952 t -2.0135** not extracted)",pct_premium,-30.47826980190932,2.168119245808803,100*(exp(b - se^2/2) - 1),|b/t|,-0.35331668194654064,0.03033578852553741,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.64686,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c1,11,Model 13 (Base No lag),35,Detach,dwelling_type,A_structural,dummy,binary,0.099087,,3.837041,,***,,,high,Detached =1; reference semi-detached,ln(transaction price),log,OLS,961.0,0.614722,t,Base model on 961-observation subsample used for spatial lag models,pct_premium,10.379425309650014,2.8513673822650816,100*(exp(b - se^2/2) - 1),|b/t|,0.12347248207864552,0.032179088542094156,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.837041,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c2,11,Model 14 (Base + Lag),35,Detach,dwelling_type,A_structural,dummy,binary,0.100533,,3.242625,,***,,,high,Detached =1; reference semi-detached,ln(transaction price),log,spatial_lag,961.0,0.673818,t,Spatial lag of price (inverse exponential distance weights) added; W*P coefficient 0.027939 (t 1.195744) not extracted,pct_premium,10.522881823322194,3.428252828142477,100*(exp(b - se^2/2) - 1),|b/t|,0.10457281075330473,0.03224943086336062,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.242625,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c3,11,Model 15 (Base+Lag + EPC),35,Detach,dwelling_type,A_structural,dummy,binary,0.102709,,3.316137,,***,,,high,Detached =1; reference semi-detached,ln(transaction price),log,spatial_lag,961.0,0.675209,t,"Spatial lag of price and spatially lagged price x EPC term added (W*P 0.184266 t 2.273**, W*P*EPC -0.002952 t -2.0135** not extracted)",pct_premium,10.763748215534608,3.4322743001881197,100*(exp(b - se^2/2) - 1),|b/t|,0.10691672778887205,0.032241348228035226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.316137,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c1,11,Model 13 (Base No lag),35,Apt,dwelling_type,A_structural,dummy,binary,-0.079251,,-1.934257,,*,,,high,Apartment =1; reference semi-detached,ln(transaction price),log,OLS,961.0,0.614722,t,Base model on 961-observation subsample used for spatial lag models,pct_premium,-7.696706778070849,3.785055933917746,100*(exp(b - se^2/2) - 1),|b/t|,-0.06259956437848929,0.032363623023460325,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.934257,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c2,11,Model 14 (Base + Lag),35,Apt,dwelling_type,A_structural,dummy,binary,-0.056519,,-1.173586,,,,,high,Apartment =1; reference semi-detached,ln(transaction price),log,spatial_lag,961.0,0.673818,t,Spatial lag of price (inverse exponential distance weights) added; W*P coefficient 0.027939 (t 1.195744) not extracted,pct_premium,-5.604676739429659,4.5512810971485935,100*(exp(b - se^2/2) - 1),|b/t|,-0.03802860560448492,0.032403765556580366,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.173586,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c3,11,Model 15 (Base+Lag + EPC),35,Apt,dwelling_type,A_structural,dummy,binary,-0.057789,,-1.201785,,,,,high,Apartment =1; reference semi-detached,ln(transaction price),log,spatial_lag,961.0,0.675209,t,"Spatial lag of price and spatially lagged price x EPC term added (W*P 0.184266 t 2.273**, W*P*EPC -0.002952 t -2.0135** not extracted)",pct_premium,-5.724150344008605,4.538590047491906,100*(exp(b - se^2/2) - 1),|b/t|,-0.03894099000469658,0.032402626097593645,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.201785,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c1,11,Model 13 (Base No lag),35,Pre1919,age,A_structural,dummy,construction period dummy,0.054449,,1.484746,,,,,high,"Built pre-1919 =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,961.0,0.614722,t,Base model on 961-observation subsample used for spatial lag models,pct_premium,5.524880416924471,3.872439525887735,100*(exp(b - se^2/2) - 1),|b/t|,0.048090481856863286,0.03238970292350563,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.484746,951.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c2,11,Model 14 (Base + Lag),35,Pre1919,age,A_structural,dummy,construction period dummy,0.030529,,0.710688,,,,,high,"Built pre-1919 =1 (construction-period dummy, not age in years)",ln(transaction price),log,spatial_lag,961.0,0.673818,t,Spatial lag of price (inverse exponential distance weights) added; W*P coefficient 0.027939 (t 1.195744) not extracted,pct_premium,3.004897489335745,4.428862249882903,100*(exp(b - se^2/2) - 1),|b/t|,0.023039520026955248,0.03241861411330323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.710688,951.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c3,11,Model 15 (Base+Lag + EPC),35,Pre1919,age,A_structural,dummy,construction period dummy,0.035264,,0.821004,,,,,high,"Built pre-1919 =1 (construction-period dummy, not age in years)",ln(transaction price),log,spatial_lag,961.0,0.675209,t,"Spatial lag of price and spatially lagged price x EPC term added (W*P 0.184266 t 2.273**, W*P*EPC -0.002952 t -2.0135** not extracted)",pct_premium,3.493802996127471,4.449398052693368,100*(exp(b - se^2/2) - 1),|b/t|,0.026613448932192252,0.03241573601613665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.821004,951.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c1,11,Model 13 (Base No lag),35,Early Modern,age,A_structural,dummy,construction period dummy,-0.020627,,-0.790323,,,,,high,"Early-modern construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,961.0,0.614722,t,Base model on 961-observation subsample used for spatial lag models,pct_premium,-2.074929920293511,2.5566616398398128,100*(exp(b - se^2/2) - 1),|b/t|,-0.02561956718084233,0.032416578007779515,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.790323,951.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c2,11,Model 14 (Base + Lag),35,Early Modern,age,A_structural,dummy,construction period dummy,0.007467,,0.226569,,,,,high,"Early-modern construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,spatial_lag,961.0,0.673818,t,Spatial lag of price (inverse exponential distance weights) added; W*P coefficient 0.027939 (t 1.195744) not extracted,pct_premium,0.6947948873100351,3.3203857427320207,100*(exp(b - se^2/2) - 1),|b/t|,0.0073468049241798405,0.032426346606022186,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.226569,951.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c3,11,Model 15 (Base+Lag + EPC),35,Early Modern,age,A_structural,dummy,construction period dummy,0.007792,,0.236813,,,,,high,"Early-modern construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,spatial_lag,961.0,0.675209,t,"Spatial lag of price and spatially lagged price x EPC term added (W*P 0.184266 t 2.273**, W*P*EPC -0.002952 t -2.0135** not extracted)",pct_premium,0.7277026386634189,3.316098536084502,100*(exp(b - se^2/2) - 1),|b/t|,0.007678961255229048,0.03242626568317216,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.236813,951.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c1,11,Model 13 (Base No lag),35,Inter War,age,A_structural,dummy,construction period dummy,0.04319,,1.496247,,,,,high,"Inter-war construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,OLS,961.0,0.614722,t,Base model on 961-observation subsample used for spatial lag models,pct_premium,4.370135474935544,3.013957264491826,100*(exp(b - se^2/2) - 1),|b/t|,0.04846212430681989,0.03238912045058061,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.496247,951.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c2,11,Model 14 (Base + Lag),35,Inter War,age,A_structural,dummy,construction period dummy,0.030309,,0.850356,,,,,high,"Inter-war construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,spatial_lag,961.0,0.673818,t,Spatial lag of price (inverse exponential distance weights) added; W*P coefficient 0.027939 (t 1.195744) not extracted,pct_premium,3.0118452739940293,3.6739552214770463,100*(exp(b - se^2/2) - 1),|b/t|,0.02756420517254363,0.032414900550526635,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.850356,951.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c3,11,Model 15 (Base+Lag + EPC),35,Inter War,age,A_structural,dummy,construction period dummy,0.024715,,0.6924,,,,,high,"Inter-war construction period =1 (construction-period dummy, not age in years)",ln(transaction price),log,spatial_lag,961.0,0.675209,t,"Spatial lag of price and spatially lagged price x EPC term added (W*P 0.184266 t 2.273**, W*P*EPC -0.002952 t -2.0135** not extracted)",pct_premium,2.4370159030260075,3.658787138041321,100*(exp(b - se^2/2) - 1),|b/t|,0.022446951082698563,0.03241905124595402,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6924,951.0,construction period dummy,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c1,11,Model 13 (Base No lag),36,Gas Heat,heating,A_structural,binary,binary,0.128549,,6.05882,,***,,,high,Gas central heating =1,ln(transaction price),log,OLS,961.0,0.614722,t,Base model on 961-observation subsample used for spatial lag models,pct_premium,13.6921217876375,2.4127302738207947,100*(exp(b - se^2/2) - 1),|b/t|,0.19278510614246533,0.03181891954909791,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.05882,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c2,11,Model 14 (Base + Lag),36,Gas Heat,heating,A_structural,binary,binary,0.108793,,4.202728,,,,,high,Gas central heating =1 printed without stars despite t=4.20,ln(transaction price),log,spatial_lag,961.0,0.673818,t,Spatial lag of price (inverse exponential distance weights) added; W*P coefficient 0.027939 (t 1.195744) not extracted,pct_premium,11.455804062755547,2.8861431564274143,100*(exp(b - se^2/2) - 1),|b/t|,0.13503456356415935,0.032130217221804355,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.202728,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c3,11,Model 15 (Base+Lag + EPC),36,Gas Heat,heating,A_structural,binary,binary,0.10717,,4.14469,,***,,,high,Gas central heating =1,ln(transaction price),log,spatial_lag,961.0,0.675209,t,"Spatial lag of price and spatially lagged price x EPC term added (W*P 0.184266 t 2.273**, W*P*EPC -0.002952 t -2.0135** not extracted)",pct_premium,11.275141784307197,2.8782235152456073,100*(exp(b - se^2/2) - 1),|b/t|,0.1332031043088718,0.03213825504654674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.14469,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c1,11,Model 13 (Base No lag),36,No Garage,garage,A_structural,binary,binary,-0.017509,,-0.907136,,,,,high,Reverse-coded: no garage =1,ln(transaction price),log,OLS,961.0,0.614722,t,Base model on 961-observation subsample used for spatial lag models,pct_premium,-1.7539630198191158,1.8966398806391354,100*(exp(b - se^2/2) - 1),|b/t|,-0.029403181769984247,0.03241320129504754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.907136,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,ols,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c2,11,Model 14 (Base + Lag),36,No Garage,garage,A_structural,binary,binary,0.000841,,0.035559,,,,,high,Reverse-coded: no garage =1,ln(transaction price),log,spatial_lag,961.0,0.673818,t,Spatial lag of price (inverse exponential distance weights) added; W*P coefficient 0.027939 (t 1.195744) not extracted,pct_premium,0.05614765986872161,2.367073254295825,100*(exp(b - se^2/2) - 1),|b/t|,0.0011530788118691976,0.03242720019880192,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.035559,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0,aa82db73a0ef7b24a4266aa846327f66030956a0:T11-c3,11,Model 15 (Base+Lag + EPC),36,No Garage,garage,A_structural,binary,binary,0.001888,,0.079952,,,,,high,Reverse-coded: no garage =1,ln(transaction price),log,spatial_lag,961.0,0.675209,t,"Spatial lag of price and spatially lagged price x EPC term added (W*P 0.184266 t 2.273**, W*P*EPC -0.002952 t -2.0135** not extracted)",pct_premium,0.16104809567958345,2.3658794164601242,100*(exp(b - se^2/2) - 1),|b/t|,0.0025926125205102605,0.032427112774042685,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.079952,951.0,binary,,2019.0,United Kingdom,Europe,High income,2013.0,2014.0,mixed,transaction,journal,True,True,OLS,,2013.5,spatial,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T3-c1,3,1,11,Age of house,age,A_structural,level,years,-0.005,0.002,-2.99,0.003,***,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes).",log monthly house rent (BDT/month),log,OLS,210.0,0.9543,se,Overall Rajshahi City Corporation area; robust SEs; coefficients on pp. 11-12,semi_elasticity,-0.5,0.2,100*b/1 (per year),reported,-0.20685226904721918,0.06918136088535758,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.99,200.0,years,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T4-c1,4,1,13,Age of house,age,A_structural,level,years,-0.0044,0.0016,-2.68,0.009,***,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes).",log monthly house rent (BDT/month),log,OLS,100.0,0.9531,se,Planned residential area; robust SEs; N/R2 note printed on p. 14,semi_elasticity,-0.44,0.16,100*b/1 (per year),reported,-0.2718572903961926,0.10143928746126589,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.68,90.0,years,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T5-c1,5,1,14,Age of house,age,A_structural,level,years,-8e-05,0.0019,-0.05,0.964,,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes).",log monthly house rent (BDT/month),log,OLS,110.0,0.8798,se,Unplanned residential area; conventional SEs; coefficients on pp. 14-15,semi_elasticity,-0.008,0.19,100*b/1 (per year),reported,-0.004999937501171852,0.099998750023437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.05,100.0,years,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T3-c1,3,1,12,Room Number,bedrooms,A_structural,level,count,0.0102,0.0032,3.13,0.002,***,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes). Defined in Table 1 as number of bedrooms",log monthly house rent (BDT/month),log,OLS,210.0,0.9543,se,Overall Rajshahi City Corporation area; robust SEs; coefficients on pp. 11-12,semi_elasticity,1.02,0.32,100*b/1 (per unit count),reported,0.2160950427408833,0.0690399497574707,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.13,200.0,count,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T4-c1,4,1,13,Room Number,bedrooms,A_structural,level,count,0.0039,0.0017,2.23,0.028,**,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes). Defined in Table 1 as number of bedrooms",log monthly house rent (BDT/month),log,OLS,100.0,0.9531,se,Planned residential area; robust SEs; N/R2 note printed on p. 14,semi_elasticity,0.38999999999999996,0.16999999999999998,100*b/1 (per unit count),reported,0.22882581262987028,0.10261247203133196,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.23,90.0,count,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T5-c1,5,1,14,Room Number,bedrooms,A_structural,level,count,0.0202,0.011,1.83,0.07,*,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes). Defined in Table 1 as number of bedrooms",log monthly house rent (BDT/month),log,OLS,110.0,0.8798,se,Unplanned residential area; conventional SEs; coefficients on pp. 14-15,semi_elasticity,2.02,1.0999999999999999,100*b/1 (per unit count),reported,0.18001063356783711,0.09836646643051208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.83,100.0,count,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T3-c1,3,1,12,Garage,garage,A_structural,binary,binary,0.011,0.0139,0.8,0.427,,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes).",log monthly house rent (BDT/month),log,OLS,210.0,0.9543,se,Overall Rajshahi City Corporation area; robust SEs; coefficients on pp. 11-12,pct_premium,1.0963053641351195,1.40537440419816,100*(exp(b - se^2/2) - 1),reported,0.056478249472490506,0.07059781184061313,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8,200.0,binary,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T4-c1,4,1,13,Garage,garage,A_structural,binary,binary,0.0137,0.0043,3.16,0.002,***,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes).",log monthly house rent (BDT/month),log,OLS,100.0,0.9531,se,Planned residential area; robust SEs; N/R2 note printed on p. 14,pct_premium,1.3784902545930011,0.4359315382631917,100*(exp(b - se^2/2) - 1),reported,0.31602275445751093,0.10000720077769333,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.16,90.0,binary,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T5-c1,5,1,14,Garage,garage,A_structural,binary,binary,0.0081,0.0079,1.02,0.309,,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes).",log monthly house rent (BDT/month),log,OLS,110.0,0.8798,se,Unplanned residential area; conventional SEs; coefficients on pp. 14-15,pct_premium,0.8101435457033457,0.7964249860649905,100*(exp(b - se^2/2) - 1),reported,0.10147350073033704,0.09948382424542847,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.02,100.0,binary,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T3-c1,3,1,12,School distance,school_distance,D_location,level,km,-0.0039,0.0099,-0.4,0.688,,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes).",log monthly house rent (BDT/month),log,OLS,210.0,0.9543,se,Overall Rajshahi City Corporation area; robust SEs; coefficients on pp. 11-12,semi_elasticity,-0.38999999999999996,0.9900000000000001,100*b/1 (X per km->km),reported,-0.0282729643226657,0.07068241080666425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4,200.0,km,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T4-c1,4,1,13,School distance,school_distance,D_location,level,km,-0.0217,0.0165,-1.32,0.192,,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes).",log monthly house rent (BDT/month),log,OLS,100.0,0.9531,se,Planned residential area; robust SEs; N/R2 note printed on p. 14,semi_elasticity,-2.17,1.6500000000000001,100*b/1 (X per km->km),reported,-0.13781258614401581,0.10440347435152711,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.32,90.0,km,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T5-c1,5,1,14,School distance,school_distance,D_location,level,km,-0.0035,0.0265,-0.14,0.893,,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes).",log monthly house rent (BDT/month),log,OLS,110.0,0.8798,se,Unplanned residential area; conventional SEs; coefficients on pp. 14-15,semi_elasticity,-0.35000000000000003,2.65,100*b/1 (X per km->km),reported,-0.013998628201651065,0.09999020144036475,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.14,100.0,km,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T3-c1,3,1,12,Waterlogging,flood_risk,E_environment,binary,binary,-0.0151,0.0083,-3.82,0.07,*,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes). Presence of waterlogging at the house (1/0); printed t-ratio inconsistent with beta/SE ratio",log monthly house rent (BDT/month),log,OLS,210.0,0.9543,se,Overall Rajshahi City Corporation area; robust SEs; coefficients on pp. 11-12,pct_premium,-1.5020494868881462,0.8175611496676332,100*(exp(b - se^2/2) - 1),reported,-0.2607691398300077,0.06826417273036853,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.82,200.0,binary,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T4-c1,4,1,13,Waterlogging,flood_risk,E_environment,binary,binary,-0.0118,0.0062,-2.91,0.059,*,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes). Presence of waterlogging at the house (1/0); printed t-ratio inconsistent with beta/SE ratio",log monthly house rent (BDT/month),log,OLS,100.0,0.9531,se,Planned residential area; robust SEs; N/R2 note printed on p. 14,pct_premium,-1.174964738705775,0.6127269951196979,100*(exp(b - se^2/2) - 1),reported,-0.2932548544137552,0.1007748640597097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.91,90.0,binary,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T5-c1,5,1,15,Waterlogging,flood_risk,E_environment,binary,binary,-0.0104,0.0062,-1.67,0.098,*,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes). Presence of waterlogging at the house (1/0)",log monthly house rent (BDT/month),log,OLS,110.0,0.8798,se,Unplanned residential area; conventional SEs; coefficients on pp. 14-15,pct_premium,-1.0365127955935916,0.6135854136656392,100*(exp(b - se^2/2) - 1),reported,-0.1647188728944956,0.09863405562544647,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.67,100.0,binary,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T3-c1,3,1,12,Landfill,hazard_site,E_environment,binary,binary,-0.0101,0.0075,-1.36,0.176,,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes). Presence of landfill by wastes nearby (1/0)",log monthly house rent (BDT/month),log,OLS,210.0,0.9543,se,Overall Rajshahi City Corporation area; robust SEs; coefficients on pp. 11-12,pct_premium,-1.0077008259791298,0.742463125286908,100*(exp(b - se^2/2) - 1),reported,-0.09572490892278161,0.07038596244322178,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.36,200.0,binary,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T4-c1,4,1,13,Landfill,hazard_site,E_environment,binary,binary,-0.0028,0.0041,-0.68,0.497,,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes). Presence of landfill by wastes nearby (1/0)",log monthly house rent (BDT/month),log,OLS,100.0,0.9531,se,Planned residential area; robust SEs; N/R2 note printed on p. 14,pct_premium,-0.2804465119800703,0.4088536057009961,100*(exp(b - se^2/2) - 1),reported,-0.07149486656219525,0.10513950965028712,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.68,90.0,binary,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6,b150aa7a491222e57926fd7829879b82c8d7c8d6:T5-c1,5,1,15,Landfill,hazard_site,E_environment,binary,binary,-0.0146,0.0075,-1.93,0.056,*,,,medium,"Log base of dependent variable uncertain (likely log10, see study notes). Presence of landfill by wastes nearby (1/0)",log monthly house rent (BDT/month),log,OLS,110.0,0.8798,se,Unplanned residential area; conventional SEs; coefficients on pp. 14-15,pct_premium,-1.4521653769887788,0.739129547398776,100*(exp(b - se^2/2) - 1),reported,-0.18950287214271566,0.09818801665425682,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.93,100.0,binary,,2025.0,Bangladesh,Asia,Lower middle income,,,rental,rent,journal,False,False,robust,,2022.0,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c1,3,1 (Pepperell),9,AGE,age,A_structural,level,years,-0.0021,0.005,,,,,,high,"age of the house in years (quadratic also included); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5506,se,"single-family sales in the town of Pepperell, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,-0.21,0.5,100*b/1 (per year),reported,-0.05989229072794672,0.14260069220939695,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.42,49.0,years,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c1,3,1 (Pepperell),9,BDRM,bedrooms,A_structural,level,count,0.065,0.0315,,,**,,,high,"number of bedrooms; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5506,se,"single-family sales in the town of Pepperell, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,6.5,3.15,100*b/1 (per unit count),reported,0.2827550552637739,0.1370274498585981,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0634920634920637,49.0,count,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c1,3,1 (Pepperell),9,BTHRM,bathrooms,A_structural,level,count,0.1236,0.0345,,,***,,,high,"number of bathrooms; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5506,se,"single-family sales in the town of Pepperell, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,12.36,3.45,100*b/1 (per unit count),reported,0.45559808965081044,0.12716936968408546,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5826086956521737,49.0,count,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c1,3,1 (Pepperell),9,LNLTSZ,lot_size,A_structural,log,sqft,0.1171,0.0316,,,***,,,high,"log of lot size, printed as 'in feet' (assumed square feet); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5506,se,"single-family sales in the town of Pepperell, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",elasticity,0.1171,0.0316,b (log-log),reported,0.4678693627600685,0.1262568049805138,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.705696202531645,49.0,sqft,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c1,3,1 (Pepperell),9,GRACE,garage,A_structural,dummy,binary,0.1107,0.0316,,,***,,,high,"garage dummy (printed GRACE in Table 3; GARAGE in Eq. 1 / Table 2); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5506,se,"single-family sales in the town of Pepperell, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,11.650215228127326,3.529908774166058,100*(exp(b - se^2/2) - 1),reported,0.4475369895613224,0.12775220298227447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5031645569620253,49.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c1,3,1 (Pepperell),9,FPLACE,fireplace,B_interior,dummy,binary,0.0896,0.0414,,,**,,,high,"fireplace dummy; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5506,se,"single-family sales in the town of Pepperell, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,9.279979254899985,4.528069944267964,100*(exp(b - se^2/2) - 1),reported,0.2953828675621677,0.13648270889591232,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1642512077294684,49.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c1,3,1 (Pepperell),9,POOL,pool,C_exterior,dummy,binary,0.0194,0.0661,,,,,,high,"swimming pool dummy; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5506,se,"single-family sales in the town of Pepperell, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,1.7364433938868773,6.7394859526551345,100*(exp(b - se^2/2) - 1),reported,0.04189101019077475,0.14273174090774282,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2934947049924357,49.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c2,3,2 (Hudson),9,AGE,age,A_structural,level,years,-0.0057,0.0015,,,***,,,high,"age of the house in years (quadratic also included); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,47.0,0.7335,se,"single-family sales in the town of Hudson, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,-0.5700000000000001,0.15,100*b/1 (per year),reported,-0.5298258172065025,0.1394278466332901,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.8000000000000003,37.0,years,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c2,3,2 (Hudson),9,BDRM,bedrooms,A_structural,level,count,0.1063,0.0403,,,**,,,high,"number of bedrooms; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,47.0,0.7335,se,"single-family sales in the town of Hudson, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,10.63,4.03,100*b/1 (per unit count),reported,0.3978427709129949,0.1508284446640987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6377171215880892,37.0,count,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c2,3,2 (Hudson),9,BTHRM,bathrooms,A_structural,level,count,0.0041,0.0471,,,,,,high,"number of bathrooms; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,47.0,0.7335,se,"single-family sales in the town of Hudson, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,0.41000000000000003,4.71,100*b/1 (per unit count),reported,0.014309274696366414,0.16438215565825806,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.08704883227176222,37.0,count,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c2,3,2 (Hudson),9,LNLTSZ,lot_size,A_structural,log,sqft,0.1639,0.037,,,***,,,high,"log of lot size, printed as 'in feet' (assumed square feet); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,47.0,0.7335,se,"single-family sales in the town of Hudson, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",elasticity,0.1639,0.037,b (log-log),reported,0.5886846182455134,0.1328940260834899,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.42972972972973,37.0,sqft,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c2,3,2 (Hudson),9,GRACE,garage,A_structural,dummy,binary,0.0397,0.0427,,,,,,high,"garage dummy (printed GRACE in Table 3; GARAGE in Eq. 1 / Table 2); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,47.0,0.7335,se,"single-family sales in the town of Hudson, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,3.9550444712037613,4.44292892717155,100*(exp(b - se^2/2) - 1),reported,0.1510939142249798,0.1625115903628876,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9297423887587821,37.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c2,3,2 (Hudson),9,FPLACE,fireplace,B_interior,dummy,binary,0.0624,0.0284,,,**,,,high,"fireplace dummy; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,47.0,0.7335,se,"single-family sales in the town of Hudson, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,6.395885493726627,3.022861962015706,100*(exp(b - se^2/2) - 1),reported,0.3397306312692407,0.1546209924366416,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.197183098591549,37.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c2,3,2 (Hudson),9,POOL,pool,C_exterior,dummy,binary,0.0901,0.0522,,,*,,,high,"swimming pool dummy; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,47.0,0.7335,se,"single-family sales in the town of Hudson, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,9.279384773429822,5.7121609484761935,100*(exp(b - se^2/2) - 1),reported,0.27298381952294376,0.15815488767034033,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7260536398467432,37.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c3,3,3 (Belchertown),9,AGE,age,A_structural,level,years,-0.0045,0.0014,,,***,,,high,"age of the house in years (quadratic also included); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,101.0,0.7034,se,"single-family sales in the town of Belchertown, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,-0.44999999999999996,0.13999999999999999,100*b/1 (per year),reported,-0.31930958700902373,0.0993407604028074,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.214285714285714,91.0,years,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c3,3,3 (Belchertown),9,BDRM,bedrooms,A_structural,level,count,0.073,0.0246,,,***,,,high,"number of bedrooms; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,101.0,0.7034,se,"single-family sales in the town of Belchertown, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,7.3,2.46,100*b/1 (per unit count),reported,0.2970363283029813,0.10009717364730605,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.967479674796748,91.0,count,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c3,3,3 (Belchertown),9,BTHRM,bathrooms,A_structural,level,count,0.1191,0.0381,,,***,,,high,"number of bathrooms; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,101.0,0.7034,se,"single-family sales in the town of Belchertown, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,11.91,3.81,100*b/1 (per unit count),reported,0.3113990807289997,0.09961633061104021,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1259842519685037,91.0,count,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c3,3,3 (Belchertown),9,LNLTSZ,lot_size,A_structural,log,sqft,0.0601,0.0265,,,**,,,high,"log of lot size, printed as 'in feet' (assumed square feet); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,101.0,0.7034,se,"single-family sales in the town of Belchertown, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",elasticity,0.0601,0.0265,b (log-log),reported,0.2312962946308943,0.1019858869836722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.267924528301887,91.0,sqft,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c3,3,3 (Belchertown),9,GRACE,garage,A_structural,dummy,binary,0.0183,0.0351,,,,,,high,"garage dummy (printed GRACE in Table 3; GARAGE in Eq. 1 / Table 2); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,101.0,0.7034,se,"single-family sales in the town of Belchertown, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,1.7841282629535105,3.57482433357724,100*(exp(b - se^2/2) - 1),reported,0.05457272099126674,0.1046722681307903,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5213675213675214,91.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c3,3,3 (Belchertown),9,FPLACE,fireplace,B_interior,dummy,binary,0.0008,0.033,,,,,,high,"fireplace dummy; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,101.0,0.7034,se,"single-family sales in the town of Belchertown, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,0.025553264290500977,3.3026410562816566,100*(exp(b - se^2/2) - 1),reported,0.002541288367825194,0.10482814517278927,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.024242424242424242,91.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c3,3,3 (Belchertown),9,POOL,pool,C_exterior,dummy,binary,0.066,0.0599,,,,,,high,"swimming pool dummy; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,101.0,0.7034,se,"single-family sales in the town of Belchertown, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,6.631203108599171,6.3986780358243,100*(exp(b - se^2/2) - 1),reported,0.11474098673985264,0.10413613796541173,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1018363939899833,91.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c4,3,4 (Clinton),9,AGE,age,A_structural,level,years,-0.0083,0.0047,,,***,,,high,"age of the house in years (quadratic also included); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5466,se,"single-family sales in the town of Clinton, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,-0.83,0.47000000000000003,100*b/1 (per year),reported,-0.24461542537618627,0.1385171685865151,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7659574468085106,49.0,years,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c4,3,4 (Clinton),9,BDRM,bedrooms,A_structural,level,count,0.0576,0.0323,,,***,,,high,"number of bedrooms; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5466,se,"single-family sales in the town of Clinton, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,5.76,3.2300000000000004,100*b/1 (per unit count),reported,0.24686955466197005,0.13843553152051447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7832817337461297,49.0,count,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c4,3,4 (Clinton),9,BTHRM,bathrooms,A_structural,level,count,-0.036,0.0611,,,,,,high,"number of bathrooms; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5466,se,"single-family sales in the town of Clinton, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,-3.5999999999999996,6.11,100*b/1 (per unit count),reported,-0.08387455591779644,0.14235376018270451,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5891980360065466,49.0,count,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c4,3,4 (Clinton),9,LNLTSZ,lot_size,A_structural,log,sqft,0.0255,0.05122,,,,,,high,"log of lot size, printed as 'in feet' (assumed square feet); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5466,se,"single-family sales in the town of Clinton, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",elasticity,0.0255,0.05122,b (log-log),reported,0.07094257331722399,0.14249720020816523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.49785240140570086,49.0,sqft,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c4,3,4 (Clinton),9,GRACE,garage,A_structural,dummy,binary,0.1298,0.0552,,,**,,,high,"garage dummy (printed GRACE in Table 3; GARAGE in Eq. 1 / Table 2); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5466,se,"single-family sales in the town of Clinton, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,13.686728031498197,6.285075535134994,100*(exp(b - se^2/2) - 1),reported,0.3184348553997904,0.13542067810530375,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.351449275362319,49.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c4,3,4 (Clinton),9,FPLACE,fireplace,B_interior,dummy,binary,0.0842,0.0625,,,,,,high,"fireplace dummy; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5466,se,"single-family sales in the town of Clinton, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,8.572381481310476,6.7990402583851,100*(exp(b - se^2/2) - 1),reported,0.1889889151666458,0.14028274581847222,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3472,49.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c4,3,4 (Clinton),9,POOL,pool,C_exterior,dummy,binary,-0.016,0.104,,,,,,high,"swimming pool dummy; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,59.0,0.5466,se,"single-family sales in the town of Clinton, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,-2.1180475276815103,10.234924128574965,100*(exp(b - se^2/2) - 1),reported,-0.021972715840335277,0.14282265296217928,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.15384615384615385,49.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c5,3,5 (Leicester),9,AGE,age,A_structural,level,years,-0.0086,0.0032,,,**,,,high,"age of the house in years (quadratic also included); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,46.0,0.4127,se,"single-family sales in the town of Leicester, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,-0.86,0.32,100*b/1 (per year),reported,-0.4087829245940621,0.152105274267558,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6875,36.0,years,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c5,3,5 (Leicester),9,BDRM,bedrooms,A_structural,level,count,-0.0178,0.0234,,,,,,high,"number of bedrooms; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,46.0,0.4127,se,"single-family sales in the town of Leicester, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,-1.78,2.34,100*b/1 (per unit count),reported,-0.12577385403802577,0.16534315643201142,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7606837606837606,36.0,count,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c5,3,5 (Leicester),9,BTHRM,bathrooms,A_structural,level,count,0.161,0.0819,,,,,,high,"number of bathrooms; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,46.0,0.4127,se,"single-family sales in the town of Leicester, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,16.1,8.19,100*b/1 (per unit count),reported,0.3113502848840519,0.15838253622362639,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.965811965811966,36.0,count,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c5,3,5 (Leicester),9,LNLTSZ,lot_size,A_structural,log,sqft,0.0056,0.0419,,,,,,high,"log of lot size, printed as 'in feet' (assumed square feet); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,46.0,0.4127,se,"single-family sales in the town of Leicester, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",elasticity,0.0056,0.0419,b (log-log),reported,0.02226973425937893,0.16662533311928165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.13365155131264916,36.0,sqft,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c5,3,5 (Leicester),9,GRACE,garage,A_structural,dummy,binary,0.0629,0.0679,,,,,,high,"garage dummy (printed GRACE in Table 3; GARAGE in Eq. 1 / Table 2); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,46.0,0.4127,se,"single-family sales in the town of Leicester, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,6.246830948015392,7.2308091213131815,100*(exp(b - se^2/2) - 1),reported,0.1525858009242068,0.16471503788161596,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.926362297496318,36.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c5,3,5 (Leicester),9,FPLACE,fireplace,B_interior,dummy,binary,0.0935,0.0534,,,*,,,high,"fireplace dummy; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,46.0,0.4127,se,"single-family sales in the town of Leicester, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,9.644619729770865,5.86337662184254,100*(exp(b - se^2/2) - 1),reported,0.28013805872740055,0.1599932870165047,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.750936329588015,36.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c5,3,5 (Leicester),9,POOL,pool,C_exterior,dummy,binary,0.2151,0.1118,,,*,,,high,"swimming pool dummy; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,46.0,0.4127,se,"single-family sales in the town of Leicester, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,23.226061390373264,13.86304224299197,100*(exp(b - se^2/2) - 1),reported,0.30534741089903433,0.1587068365342261,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9239713774597498,36.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c6,3,6 (Ware),9,AGE,age,A_structural,level,years,-0.0028,0.0018,,,,,,high,"age of the house in years (quadratic also included); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,67.0,0.6215,se,"single-family sales in the town of Ware, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,-0.27999999999999997,0.18,100*b/1 (per year),reported,-0.20179950882471162,0.1297282556730289,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5555555555555556,57.0,years,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c6,3,6 (Ware),9,BDRM,bedrooms,A_structural,level,count,0.092,0.0326,,,***,,,high,"number of bedrooms; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,67.0,0.6215,se,"single-family sales in the town of Ware, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,9.2,3.26,100*b/1 (per unit count),reported,0.35013319301668644,0.12406893578634758,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8220858895705523,57.0,count,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c6,3,6 (Ware),9,BTHRM,bathrooms,A_structural,level,count,0.0235,0.0406,,,,,,high,"number of bathrooms; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,67.0,0.6215,se,"single-family sales in the town of Ware, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",semi_elasticity,2.35,4.06,100*b/1 (per unit count),reported,0.07644195872792679,0.13206568188739692,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5788177339901478,57.0,count,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c6,3,6 (Ware),9,LNLTSZ,lot_size,A_structural,log,sqft,0.01066,0.0305,,,***,,,medium,"log of lot size, printed as 'in feet' (assumed square feet); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level; printed stars inconsistent with printed SE (|b/se|<1.65) - as printed",log of sale price (1995 dollars),log,OLS,67.0,0.6215,se,"single-family sales in the town of Ware, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",elasticity,0.01066,0.0305,b (log-log),reported,0.046243965652913194,0.13231153399754714,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.34950819672131145,57.0,sqft,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c6,3,6 (Ware),9,GRACE,garage,A_structural,dummy,binary,0.1602,0.0547,,,***,,,high,"garage dummy (printed GRACE in Table 3; GARAGE in Eq. 1 / Table 2); White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,67.0,0.6215,se,"single-family sales in the town of Ware, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,17.199093326162075,6.420388413608715,100*(exp(b - se^2/2) - 1),reported,0.36165829840749475,0.12348757130393236,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9287020109689217,57.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c6,3,6 (Ware),9,FPLACE,fireplace,B_interior,dummy,binary,0.0633,0.0477,,,,,,high,"fireplace dummy; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,67.0,0.6215,se,"single-family sales in the town of Ware, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,6.413509835784037,5.081702305171141,100*(exp(b - se^2/2) - 1),reported,0.17311734084788044,0.13045335163418478,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3270440251572326,57.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd,b4d90ac556c12775841d148b92b32c2089b062dd:T3-c6,3,6 (Ware),9,POOL,pool,C_exterior,dummy,binary,0.0564,0.0781,,,,,,high,"swimming pool dummy; White-corrected SE in parentheses; *** 99%, ** 95%, * 90% level",log of sale price (1995 dollars),log,OLS,67.0,0.6215,se,"single-family sales in the town of Ware, Massachusetts, Jan 1992-Aug 1995 (separate regression per town; Chow test rejected pooling); r2 = adjusted R2; year-of-sale dummies SOLD92-94 included, not extracted",pct_premium,5.479896577227716,8.263142506022074,100*(exp(b - se^2/2) - 1),reported,0.09521666377057163,0.131851443980171,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7221510883482714,57.0,binary,,2000.0,United States,North America,High income,1992.0,1995.0,single_family,transaction,journal,True,False,robust,,1993.5,ols,journal,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-OLS,2,OLS,14,lnarea_total,living_area,A_structural,log,m2,0.41,0.017,23.988,,***,,,high,Log total floor area excl. basement,"lnp (log purchase price, EUR)",log,OLS,3887.0,0.473,se,"Global model, stepwise AIC selection; HC (White) standard errors; federal state dummies",elasticity,0.41,0.017,b (log-log),reported,0.3594974180725158,0.01498655236253609,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.988,3877.0,m2,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,ols,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-SAR,2,SAR,14,lnarea_total,living_area,A_structural,log,m2,0.409,0.018,22.825,,***,,,high,Log total floor area excl. basement,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,0.486,se,"Spatial autoregressive (lag) model, k=5 nearest neighbours, ML; z-values",elasticity,0.409,0.018,b (log-log),reported,0.3441788113005924,0.015079027877353445,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.825,3877.0,m2,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-S2SLS,2,S2SLS,14,lnarea_total,living_area,A_structural,log,m2,0.411,0.017,23.864,,***,,,high,Log total floor area excl. basement,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,,se,Spatial two-stage least squares with SHAC standard errors,elasticity,0.411,0.017,b (log-log),reported,0.35787763291872227,0.01499654847966486,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.864,3877.0,m2,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-OLS,2,OLS,14,lnarea_plot,lot_size,A_structural,log,m2,0.111,0.012,8.945,,***,,,high,Log plot space,"lnp (log purchase price, EUR)",log,OLS,3887.0,0.473,se,"Global model, stepwise AIC selection; HC (White) standard errors; federal state dummies",elasticity,0.111,0.012,b (log-log),reported,0.14219902053917793,0.015897039747252983,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.945,3877.0,m2,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,ols,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-SAR,2,SAR,14,lnarea_plot,lot_size,A_structural,log,m2,0.111,0.013,8.855,,***,,,high,Log plot space,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,0.486,se,"Spatial autoregressive (lag) model, k=5 nearest neighbours, ML; z-values",elasticity,0.111,0.013,b (log-log),reported,0.14079679069581127,0.01590025868953261,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.855,3877.0,m2,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-S2SLS,2,S2SLS,14,lnarea_plot,lot_size,A_structural,log,m2,0.111,0.012,8.891,,***,,,high,Log plot space,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,,se,Spatial two-stage least squares with SHAC standard errors,elasticity,0.111,0.012,b (log-log),reported,0.14135778480775987,0.0158989747843617,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.891,3877.0,m2,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-OLS,2,OLS,14,cond_house_1,condition,A_structural,binary,binary,-0.052,0.014,-3.742,,***,,,high,1 = poor condition,"lnp (log purchase price, EUR)",log,OLS,3887.0,0.473,se,"Global model, stepwise AIC selection; HC (White) standard errors; federal state dummies",pct_premium,-5.0764162827532715,1.3290604135800455,100*(exp(b - se^2/2) - 1),reported,-0.059989193691741646,0.016031318463853993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.742,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,ols,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-SAR,2,SAR,14,cond_house_1,condition,A_structural,binary,binary,-0.045,0.014,-3.33,,**,,,high,1 = poor condition,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,0.486,se,"Spatial autoregressive (lag) model, k=5 nearest neighbours, ML; z-values",pct_premium,-4.409620132956982,1.33839647456634,100*(exp(b - se^2/2) - 1),reported,-0.05340428935294871,0.01603732413001463,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.33,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-S2SLS,2,S2SLS,14,cond_house_1,condition,A_structural,binary,binary,-0.044,0.014,-3.229,,**,,,high,1 = poor condition,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,,se,Spatial two-stage least squares with SHAC standard errors,pct_premium,-4.313981941964284,1.3397355404622655,100*(exp(b - se^2/2) - 1),reported,-0.051788931745568825,0.016038690537494217,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.229,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-OLS,2,OLS,14,heat_1,heating,A_structural,binary,binary,-0.102,0.02,-5.018,,***,,,high,1 = poor quality heating system,"lnp (log purchase price, EUR)",log,OLS,3887.0,0.473,se,"Global model, stepwise AIC selection; HC (White) standard errors; federal state dummies",pct_premium,-9.715103618206989,1.8060591033377535,100*(exp(b - se^2/2) - 1),reported,-0.08032985621513399,0.016008341214654043,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.018,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,ols,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-SAR,2,SAR,14,heat_1,heating,A_structural,binary,binary,-0.107,0.023,-4.602,,***,,,high,1 = poor quality heating system,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,0.486,se,"Spatial autoregressive (lag) model, k=5 nearest neighbours, ML; z-values",pct_premium,-10.171195562243096,2.066609047877703,100*(exp(b - se^2/2) - 1),reported,-0.0737081920515675,0.01601655629108377,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.602,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-S2SLS,2,S2SLS,14,heat_1,heating,A_structural,binary,binary,-0.105,0.021,-5.005,,***,,,high,1 = poor quality heating system,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,,se,Spatial two-stage least squares with SHAC standard errors,pct_premium,-9.987397708557156,1.8906814974311579,100*(exp(b - se^2/2) - 1),reported,-0.08012308549879814,0.01600860849126836,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.005,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-OLS,2,OLS,14,bath_1,bathroom_quality,B_interior,binary,binary,-0.076,0.019,-3.91,,***,,,high,1 = poor quality bathroom/toilet,"lnp (log purchase price, EUR)",log,OLS,3887.0,0.473,se,"Global model, stepwise AIC selection; HC (White) standard errors; federal state dummies",pct_premium,-7.3351068668858215,1.760950792462826,100*(exp(b - se^2/2) - 1),reported,-0.06267210302994967,0.01602867085164953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.91,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,ols,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-SAR,2,SAR,14,bath_1,bathroom_quality,B_interior,binary,binary,-0.074,0.022,-3.339,,***,,,high,1 = poor quality bathroom/toilet,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,0.486,se,"Spatial autoregressive (lag) model, k=5 nearest neighbours, ML; z-values",pct_premium,-7.155301751745135,2.0430777264508317,100*(exp(b - se^2/2) - 1),reported,-0.053548211955903466,0.01603720034618253,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.339,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-S2SLS,2,S2SLS,14,bath_1,bathroom_quality,B_interior,binary,binary,-0.075,0.019,-3.985,,***,,,high,1 = poor quality bathroom/toilet,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,,se,Spatial two-stage least squares with SHAC standard errors,pct_premium,-7.2423956258581335,1.7627126240242503,100*(exp(b - se^2/2) - 1),reported,-0.06386939537512255,0.016027451787985585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.985,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-OLS,2,OLS,14,attic_1,storage,B_interior,binary,binary,-0.024,0.012,-2.018,,*,,,high,1 = traditional attic exists,"lnp (log purchase price, EUR)",log,OLS,3887.0,0.473,se,"Global model, stepwise AIC selection; HC (White) standard errors; federal state dummies",pct_premium,-2.3784580282721457,1.1715428517094912,100*(exp(b - se^2/2) - 1),reported,-0.032392561646013805,0.01605181449257374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.018,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,ols,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-SAR,2,SAR,14,attic_1,storage,B_interior,binary,binary,-0.024,0.011,-2.077,,*,,,high,1 = traditional attic exists,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,0.486,se,"Spatial autoregressive (lag) model, k=5 nearest neighbours, ML; z-values",pct_premium,-2.377335374084222,1.0739142807337003,100*(exp(b - se^2/2) - 1),reported,-0.033338581018466075,0.016051314886117513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.077,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-S2SLS,2,S2SLS,14,attic_1,storage,B_interior,binary,binary,-0.024,0.012,-2.02,,*,,,high,1 = traditional attic exists,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,,se,Spatial two-stage least squares with SHAC standard errors,pct_premium,-2.3784580282721457,1.1715428517094912,100*(exp(b - se^2/2) - 1),reported,-0.03242463153932409,0.0160517977917446,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.02,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-OLS,2,OLS,14,basement_1,basement,A_structural,binary,binary,0.132,0.013,9.936,,***,,,high,,"lnp (log purchase price, EUR)",log,OLS,3887.0,0.473,se,"Global model, stepwise AIC selection; HC (White) standard errors; federal state dummies",pct_premium,14.101189968804162,1.4834408150474054,100*(exp(b - se^2/2) - 1),reported,0.1575808591046172,0.015859587268983212,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.936,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,ols,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-SAR,2,SAR,14,basement_1,basement,A_structural,binary,binary,0.126,0.013,9.597,,***,,,high,,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,0.486,se,"Spatial autoregressive (lag) model, k=5 nearest neighbours, ML; z-values",pct_premium,13.418632548922016,1.4745668187679326,100*(exp(b - se^2/2) - 1),reported,0.1523313681024883,0.01587281109747716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.597,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-S2SLS,2,S2SLS,14,basement_1,basement,A_structural,binary,binary,0.124,0.014,9.069,,***,,,high,,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,,se,Spatial two-stage least squares with SHAC standard errors,pct_premium,13.190493887957988,1.5848222193988453,100*(exp(b - se^2/2) - 1),reported,0.1441295785946081,0.015892554702239284,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.069,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-OLS,2,OLS,14,garage_1,garage,A_structural,binary,binary,-0.082,0.012,-6.899,,***,,,high,1 = poor quality garage,"lnp (log purchase price, EUR)",log,OLS,3887.0,0.473,se,"Global model, stepwise AIC selection; HC (White) standard errors; federal state dummies",pct_premium,-7.879437049679783,1.1055263504356185,100*(exp(b - se^2/2) - 1),reported,-0.11012569326006429,0.015962558814330233,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.899,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,ols,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-SAR,2,SAR,14,garage_1,garage,A_structural,binary,binary,-0.084,0.012,-7.162,,***,,,high,1 = poor quality garage,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,0.486,se,"Spatial autoregressive (lag) model, k=5 nearest neighbours, ML; z-values",pct_premium,-8.063494057220556,1.1033175073141497,100*(exp(b - se^2/2) - 1),reported,-0.11427002209765391,0.015955043576885496,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.162,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,True
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-S2SLS,2,S2SLS,14,garage_1,garage,A_structural,binary,binary,-0.084,0.012,-7.064,,***,,,high,1 = poor quality garage,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,,se,Spatial two-stage least squares with SHAC standard errors,pct_premium,-8.063494057220556,1.1033175073141497,100*(exp(b - se^2/2) - 1),reported,-0.11272643285568539,0.015957875545821825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.064,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,True
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-OLS,2,OLS,14,terr_1,terrace_balcony,C_exterior,binary,binary,0.07,0.012,5.893,,***,,,high,,"lnp (log purchase price, EUR)",log,OLS,3887.0,0.473,se,"Global model, stepwise AIC selection; HC (White) standard errors; federal state dummies",pct_premium,7.243096344504063,1.28700981750506,100*(exp(b - se^2/2) - 1),reported,0.09422196285414136,0.015988793968121733,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.893,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,ols,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-SAR,2,SAR,14,terr_1,terrace_balcony,C_exterior,binary,binary,0.066,0.012,5.673,,***,,,high,,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,0.486,se,"Spatial autoregressive (lag) model, k=5 nearest neighbours, ML; z-values",pct_premium,6.814980761113465,1.281872060599192,100*(exp(b - se^2/2) - 1),reported,0.09073394351603599,0.01599399674176555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.673,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-S2SLS,2,S2SLS,14,terr_1,terrace_balcony,C_exterior,binary,binary,0.066,0.012,5.574,,***,,,high,,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,,se,Spatial two-stage least squares with SHAC standard errors,pct_premium,6.814980761113465,1.281872060599192,100*(exp(b - se^2/2) - 1),reported,0.08916323693018595,0.015996275014385712,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.574,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-OLS,2,OLS,14,age,age,A_structural,level,years,-0.006,0.0,-16.976,,***,,,high,SE printed as 0.000 (rounded); S2SLS t printed without stars,"lnp (log purchase price, EUR)",log,OLS,3887.0,0.473,se,"Global model, stepwise AIC selection; HC (White) standard errors; federal state dummies",semi_elasticity,-0.6,0.0353440150801131,100*b/1 (per year),|b/t|,-0.2630378468142042,0.015494689374069526,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.976,3877.0,years,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,ols,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-SAR,2,SAR,14,age,age,A_structural,level,years,-0.006,0.0,-17.617,,***,,,high,SE printed as 0.000 (rounded); S2SLS t printed without stars,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,0.486,se,"Spatial autoregressive (lag) model, k=5 nearest neighbours, ML; z-values",semi_elasticity,-0.6,0.034058012147357666,100*b/1 (per year),|b/t|,-0.2722462286250993,0.015453608935976573,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.617,3877.0,years,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-S2SLS,2,S2SLS,14,age,age,A_structural,level,years,-0.006,0.0,-16.434,,,,,high,SE printed as 0.000 (rounded); S2SLS t printed without stars,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,,se,Spatial two-stage least squares with SHAC standard errors,semi_elasticity,-0.6,0.03650967506389193,100*b/1 (per year),|b/t|,-0.25519506213420917,0.015528481327382816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.434,3877.0,years,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-OLS,2,OLS,14,ln_muni_popd,density,F_neighbourhood,log,per_km2,0.033,0.007,4.518,,***,,,high,Log municipal population density,"lnp (log purchase price, EUR)",log,OLS,3887.0,0.473,se,"Global model, stepwise AIC selection; HC (White) standard errors; federal state dummies",elasticity,0.033,0.007,b (log-log),reported,0.07236991283280168,0.016018130330412057,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.518,3877.0,per_km2,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,ols,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-SAR,2,SAR,14,ln_muni_popd,density,F_neighbourhood,log,per_km2,0.02,0.006,3.153,,**,,,high,Log municipal population density,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,0.486,se,"Spatial autoregressive (lag) model, k=5 nearest neighbours, ML; z-values",elasticity,0.02,0.006,b (log-log),reported,0.05057314635458123,0.016039691200311207,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.153,3877.0,per_km2,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T2-S2SLS,2,S2SLS,14,ln_muni_popd,density,F_neighbourhood,log,per_km2,0.02,0.006,3.245,,,,,high,Log municipal population density,"lnp (log purchase price, EUR)",log,spatial_lag,3887.0,,se,Spatial two-stage least squares with SHAC standard errors,elasticity,0.02,0.006,b (log-log),reported,0.052044857407595395,0.016038476859043267,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.245,3877.0,per_km2,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T3-global,3,Global coeff.,16,lnarea_total,living_area,A_structural,log,m2,0.422,0.024,17.453,,***,,,medium,Global column of the semi-local (MGWR) table; exact estimator of the global counterparts for locally varying covariates is not stated,"lnp (log purchase price, EUR)",log,GWR,3887.0,,se,"Mixed GWR on 50% random subsample; 'global' column = spatially stationary estimates for cond_house_1, bath_1, attic_1, basement_1, garage_1, terr_1 and global counterparts for the locally varying covariates (local quantiles not extracted)",elasticity,0.422,0.024,b (log-log),reported,0.2698972569963901,0.015464232911040513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.453,3877.0,m2,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T3-global,3,Global coeff.,16,lnarea_plot,lot_size,A_structural,log,m2,0.077,0.018,4.268,,***,,,medium,Global column of the semi-local (MGWR) table; exact estimator of the global counterparts for locally varying covariates is not stated,"lnp (log purchase price, EUR)",log,GWR,3887.0,,se,"Mixed GWR on 50% random subsample; 'global' column = spatially stationary estimates for cond_house_1, bath_1, attic_1, basement_1, garage_1, terr_1 and global counterparts for the locally varying covariates (local quantiles not extracted)",elasticity,0.077,0.018,b (log-log),reported,0.06838465304548642,0.01602264598066692,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.268,3877.0,m2,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T3-global,3,Global coeff.,16,heat_1,heating,A_structural,binary,binary,-0.111,0.031,-3.544,,***,,,medium,1 = poor heating; Global column of the semi-local (MGWR) table; exact estimator of the global counterparts for locally varying covariates is not stated,"lnp (log purchase price, EUR)",log,GWR,3887.0,,se,"Mixed GWR on 50% random subsample; 'global' column = spatially stationary estimates for cond_house_1, bath_1, attic_1, basement_1, garage_1, terr_1 and global counterparts for the locally varying covariates (local quantiles not extracted)",pct_premium,-10.549116584453344,2.774310121679996,100*(exp(b - se^2/2) - 1),reported,-0.056825527928064716,0.016034291176090495,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.544,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T3-global,3,Global coeff.,16,Age,age,A_structural,level,years,-0.005,0.0,-11.441,,***,,,medium,SE printed 0.000; Global column of the semi-local (MGWR) table; exact estimator of the global counterparts for locally varying covariates is not stated,"lnp (log purchase price, EUR)",log,GWR,3887.0,,se,"Mixed GWR on 50% random subsample; 'global' column = spatially stationary estimates for cond_house_1, bath_1, attic_1, basement_1, garage_1, terr_1 and global counterparts for the locally varying covariates (local quantiles not extracted)",semi_elasticity,-0.5,0.043702473560003494,100*b/1 (per year),|b/t|,-0.1807198001911136,0.015795804579242515,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.441,3877.0,years,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T3-global,3,Global coeff.,16,ln_muni_popd,density,F_neighbourhood,log,per_km2,0.067,0.008,8.623,,***,,,medium,Global column of the semi-local (MGWR) table; exact estimator of the global counterparts for locally varying covariates is not stated,"lnp (log purchase price, EUR)",log,GWR,3887.0,,se,"Mixed GWR on 50% random subsample; 'global' column = spatially stationary estimates for cond_house_1, bath_1, attic_1, basement_1, garage_1, terr_1 and global counterparts for the locally varying covariates (local quantiles not extracted)",elasticity,0.067,0.008,b (log-log),reported,0.13717826296868457,0.015908415049134244,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.623,3877.0,per_km2,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T3-global,3,Global coeff.,16,cond_house_1,condition,A_structural,binary,binary,-0.038,0.02,-1.953,,.,,,medium,Spatially stationary in MGWR; '.' = p<0.10; Global column of the semi-local (MGWR) table; exact estimator of the global counterparts for locally varying covariates is not stated,"lnp (log purchase price, EUR)",log,GWR,3887.0,,se,"Mixed GWR on 50% random subsample; 'global' column = spatially stationary estimates for cond_house_1, bath_1, attic_1, basement_1, garage_1, terr_1 and global counterparts for the locally varying covariates (local quantiles not extracted)",pct_premium,-3.74795824440034,1.925425881782399,100*(exp(b - se^2/2) - 1),reported,-0.03135023621236665,0.016052348291022346,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.953,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T3-global,3,Global coeff.,16,bath_1,bathroom_quality,B_interior,binary,binary,-0.064,0.031,-2.029,,*,,,medium,Spatially stationary in MGWR; Global column of the semi-local (MGWR) table; exact estimator of the global counterparts for locally varying covariates is not stated,"lnp (log purchase price, EUR)",log,GWR,3887.0,,se,"Mixed GWR on 50% random subsample; 'global' column = spatially stationary estimates for cond_house_1, bath_1, attic_1, basement_1, garage_1, terr_1 and global counterparts for the locally varying covariates (local quantiles not extracted)",pct_premium,-6.244560360547191,2.9078154985452613,100*(exp(b - se^2/2) - 1),reported,-0.032568944818451885,0.0160517224339339,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.029,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T3-global,3,Global coeff.,16,attic_1,storage,B_interior,binary,binary,-0.028,0.016,-1.674,,.,,,medium,Spatially stationary in MGWR; '.' = p<0.10; Global column of the semi-local (MGWR) table; exact estimator of the global counterparts for locally varying covariates is not stated,"lnp (log purchase price, EUR)",log,GWR,3887.0,,se,"Mixed GWR on 50% random subsample; 'global' column = spatially stationary estimates for cond_house_1, bath_1, attic_1, basement_1, garage_1, terr_1 and global counterparts for the locally varying covariates (local quantiles not extracted)",pct_premium,-2.773609094423801,1.555821386881995,100*(exp(b - se^2/2) - 1),reported,-0.02687513515039033,0.016054441547425528,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.674,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T3-global,3,Global coeff.,16,basement_1,basement,A_structural,binary,binary,0.144,0.019,7.665,,***,,,medium,Spatially stationary in MGWR; Global column of the semi-local (MGWR) table; exact estimator of the global counterparts for locally varying covariates is not stated,"lnp (log purchase price, EUR)",log,GWR,3887.0,,se,"Mixed GWR on 50% random subsample; 'global' column = spatially stationary estimates for cond_house_1, bath_1, attic_1, basement_1, garage_1, terr_1 and global counterparts for the locally varying covariates (local quantiles not extracted)",pct_premium,15.467567075539957,2.194279806197336,100*(exp(b - se^2/2) - 1),reported,0.12217948335950372,0.01593991955114204,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.665,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T3-global,3,Global coeff.,16,garage_1,garage,A_structural,binary,binary,-0.068,0.017,-4.06,,***,,,medium,Spatially stationary in MGWR; Global column of the semi-local (MGWR) table; exact estimator of the global counterparts for locally varying covariates is not stated,"lnp (log purchase price, EUR)",log,GWR,3887.0,,se,"Mixed GWR on 50% random subsample; 'global' column = spatially stationary estimates for cond_house_1, bath_1, attic_1, basement_1, garage_1, terr_1 and global counterparts for the locally varying covariates (local quantiles not extracted)",pct_premium,-6.587451730789207,1.5882428050812631,100*(exp(b - se^2/2) - 1),reported,-0.06506641198679952,0.0160262098489654,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.06,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6:T3-global,3,Global coeff.,16,terr_1,terrace_balcony,C_exterior,binary,binary,0.076,0.017,4.587,,***,,,medium,Spatially stationary in MGWR; Global column of the semi-local (MGWR) table; exact estimator of the global counterparts for locally varying covariates is not stated,"lnp (log purchase price, EUR)",log,GWR,3887.0,,se,"Mixed GWR on 50% random subsample; 'global' column = spatially stationary estimates for cond_house_1, bath_1, attic_1, basement_1, garage_1, terr_1 and global counterparts for the locally varying covariates (local quantiles not extracted)",pct_premium,7.880667532927976,1.8342363760673828,100*(exp(b - se^2/2) - 1),reported,0.07346924261165404,0.016016839461882284,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.587,3877.0,binary,,2014.0,Austria,Europe,High income,1998.0,2009.0,single_family,transaction,working_paper,False,True,robust,,2003.5,spatial,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c1,2,1,16,Log(living area sqft),living_area,A_structural,log,sqft,0.458,0.032,,,***,,,high,,"logprice (log sale price, USD)",log,FE_panel,258473.0,0.844,se,"Connecticut, 50 municipalities, 1994-2013; town FE + year dummies; clustered SE",elasticity,0.458,0.032,b (log-log),reported,0.028141307710993487,0.0019662049055715974,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.3125,258463.0,sqft,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,Log(living area sqft),living_area,A_structural,log,sqft,0.323,0.01,,,***,,,high,,"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",elasticity,0.323,0.01,b (log-log),reported,0.041350615272622404,0.0012802048072019323,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.3,609113.0,sqft,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c1,2,1,16,Log(lotsize),lot_size,A_structural,log,acres,0.0921,0.011,,,***,,,high,Lot size in acres (Table 1),"logprice (log sale price, USD)",log,FE_panel,258473.0,0.844,se,"Connecticut, 50 municipalities, 1994-2013; town FE + year dummies; clustered SE",elasticity,0.0921,0.011,b (log-log),reported,0.01646678692954335,0.0019667172228553403,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.372727272727273,258463.0,acre,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,Log(lotsize),lot_size,A_structural,log,acres,0.063,0.005,,,***,,,high,Lot size in acres (Table 1),"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",elasticity,0.063,0.005,b (log-log),reported,0.016142285370328788,0.001281133759549904,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.6,609113.0,acre,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c1,2,1,16,2 bathrooms+,bathrooms,A_structural,dummy,binary,0.0436,0.007,,,***,,,high,2 (or 2.5 in CT) bathrooms; ref. 1 bathroom,"logprice (log sale price, USD)",log,FE_panel,258473.0,0.844,se,"Connecticut, 50 municipalities, 1994-2013; town FE + year dummies; clustered SE",pct_premium,4.453885401851321,0.731195111873752,100*(exp(b - se^2/2) - 1),reported,0.012250580476166919,0.001966836314980927,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.228571428571429,258463.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,2 bathrooms+,bathrooms,A_structural,dummy,binary,0.051,0.003,,,***,,,high,2 (or 2.5 in CT) bathrooms; ref. 1 bathroom,"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",pct_premium,5.231815784083893,0.31569686798496116,100*(exp(b - se^2/2) - 1),reported,0.021776946479713705,0.001280996851747865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.0,609113.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c1,2,1,16,3 bathrooms+,bathrooms,A_structural,dummy,binary,0.122,0.009,,,***,,,high,3 (or 3.5 in CT) bathrooms; ref. 1 bathroom,"logprice (log sale price, USD)",log,FE_panel,258473.0,0.844,se,"Connecticut, 50 municipalities, 1994-2013; town FE + year dummies; clustered SE",pct_premium,12.97083476657237,1.0167786916022867,100*(exp(b - se^2/2) - 1),reported,0.026654086684282586,0.001966285083266748,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.555555555555557,258463.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,3 bathrooms+,bathrooms,A_structural,dummy,binary,0.117,0.008,,,***,,,high,3 (or 3.5 in CT) bathrooms; ref. 1 bathroom,"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",pct_premium,12.408345844432978,0.8992955437524295,100*(exp(b - se^2/2) - 1),reported,0.01873573359086643,0.001281075801084884,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.625,609113.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c1,2,1,16,4 or more bathrooms,bathrooms,A_structural,dummy,binary,0.282,0.018,,,***,,,high,ref. 1 bathroom,"logprice (log sale price, USD)",log,FE_panel,258473.0,0.844,se,"Connecticut, 50 municipalities, 1994-2013; town FE + year dummies; clustered SE",pct_premium,32.55639612300831,2.3864016959762253,100*(exp(b - se^2/2) - 1),reported,0.03080145987152973,0.0019660506300976425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.666666666666666,258463.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,4 or more bathrooms,bathrooms,A_structural,dummy,binary,0.07,0.012,,,***,,,high,ref. 1 bathroom,"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",pct_premium,7.243096344504063,1.28700981750506,100*(exp(b - se^2/2) - 1),reported,0.007474045359410974,0.001281264918756167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.833333333333334,609113.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c1,2,1,16,Age>=10 and < 30,age,A_structural,dummy,years,0.166,0.012,,,***,,,high,Age category 10-29 years; ref. age < 10,"logprice (log sale price, USD)",log,FE_panel,258473.0,0.844,se,"Connecticut, 50 municipalities, 1994-2013; town FE + year dummies; clustered SE",pct_premium,18.048810351992394,1.4166877220679315,100*(exp(b - se^2/2) - 1),reported,0.027199876949598543,0.00196625616503122,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.833333333333334,258463.0,years,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,Age>=10 and < 30,age,A_structural,dummy,years,-0.033,0.006,,,***,,,high,Age category 10-29 years; ref. age < 10,"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",pct_premium,-3.2478855948300245,0.5805231357534192,100*(exp(b - se^2/2) - 1),reported,-0.007046978904994657,0.0012812688918172103,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.5,609113.0,years,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c1,2,1,16,Age>=30 and <=50,age,A_structural,dummy,years,0.0588,0.008,,,***,,,high,Age category 30-50 years; ref. age < 10,"logprice (log sale price, USD)",log,FE_panel,258473.0,0.844,se,"Connecticut, 50 municipalities, 1994-2013; town FE + year dummies; clustered SE",pct_premium,6.0529169429683005,0.8484504855248812,100*(exp(b - se^2/2) - 1),reported,0.014455821151528898,0.0019667783879631154,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.35,258463.0,years,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,Age>=30 and <=50,age,A_structural,dummy,years,-0.127,0.007,,,***,,,high,Age category 30-50 years; ref. age < 10,"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",pct_premium,-11.928790511349362,0.6165135708180098,100*(exp(b - se^2/2) - 1),reported,-0.02324017706044849,0.0012809546411270824,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-18.142857142857142,609113.0,years,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c1,2,1,16,Age>=50,age,A_structural,dummy,years,-0.0248,0.013,,,,,,high,Age category > 50 years; ref. age < 10,"logprice (log sale price, USD)",log,FE_panel,258473.0,0.844,se,"Connecticut, 50 municipalities, 1994-2013; town FE + year dummies; clustered SE",pct_premium,-2.4577433171138585,1.268156491573708,100*(exp(b - se^2/2) - 1),reported,-0.0037523736755291307,0.001966970071849947,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9076923076923078,258463.0,years,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,Age>=50,age,A_structural,dummy,years,-0.177,0.011,,,***,,,high,Age category > 50 years; ref. age < 10,"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",pct_premium,-16.22708996207589,0.9215577629752931,100*(exp(b - se^2/2) - 1),reported,-0.020612912663507132,0.0012810284706134376,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.09090909090909,609113.0,years,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,True
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c1,2,1,16,2 bedrooms,bedrooms,A_structural,dummy,binary,0.0357,0.03,,,**,,,medium,Bedroom-count dummy (reference not stated); printed stars inconsistent with printed SE (as printed),"logprice (log sale price, USD)",log,FE_panel,258473.0,0.844,se,"Connecticut, 50 municipalities, 1994-2013; town FE + year dummies; clustered SE",pct_premium,3.5878646092636135,3.1090346891454743,100*(exp(b - se^2/2) - 1),reported,0.0023407044522585968,0.0019669785313097448,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1900000000000002,258463.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,2 bedrooms,bedrooms,A_structural,dummy,binary,0.01,0.013,,,,,,high,Bedroom-count dummy (reference not stated),"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",pct_premium,0.9964821450953343,1.3130652172094182,100*(exp(b - se^2/2) - 1),reported,0.0009856154496154165,0.0012813000845000415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7692307692307693,609113.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c1,2,1,16,3 bedrooms,bedrooms,A_structural,dummy,binary,0.05,0.03,,,***,,,medium,Bedroom-count dummy (reference not stated); printed stars inconsistent with printed SE (as printed),"logprice (log sale price, USD)",log,FE_panel,258473.0,0.844,se,"Connecticut, 50 municipalities, 1994-2013; town FE + year dummies; clustered SE",pct_premium,5.079813080788886,3.1538132891280726,100*(exp(b - se^2/2) - 1),reported,0.0032782889166280515,0.001966973349976831,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6666666666666667,258463.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,3 bedrooms,bedrooms,A_structural,dummy,binary,0.019,0.014,,,,,,high,Bedroom-count dummy (reference not stated),"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",pct_premium,1.9081773709793914,1.4268543080643714,100*(exp(b - se^2/2) - 1),reported,0.0017389054731061148,0.0012812987696571374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.357142857142857,609113.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c1,2,1,16,4 bedrooms,bedrooms,A_structural,dummy,binary,0.0356,0.028,,,**,,,medium,Bedroom-count dummy (reference not stated); printed stars inconsistent with printed SE (as printed),"logprice (log sale price, USD)",log,FE_panel,258473.0,0.844,se,"Connecticut, 50 municipalities, 1994-2013; town FE + year dummies; clustered SE",pct_premium,3.583514010313249,2.9014755478064678,100*(exp(b - se^2/2) - 1),reported,0.0025008717344223194,0.001966977768646768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2714285714285714,258463.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,4 bedrooms,bedrooms,A_structural,dummy,binary,0.032,0.014,,,**,,,high,Bedroom-count dummy (reference not stated),"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",pct_premium,3.2416323547585613,1.4455245074271657,100*(exp(b - se^2/2) - 1),reported,0.0029286747700462577,0.0012812952118952377,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.2857142857142856,609113.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c1,2,1,16,5 or more bedrooms,bedrooms,A_structural,dummy,binary,0.0566,0.026,,,***,,,medium,Bedroom-count dummy (reference not stated); printed stars inconsistent with printed SE (as printed),"logprice (log sale price, USD)",log,FE_panel,258473.0,0.844,se,"Connecticut, 50 municipalities, 1994-2013; town FE + year dummies; clustered SE",pct_premium,5.787481063178834,2.75140432515654,100*(exp(b - se^2/2) - 1),reported,0.004281933431815004,0.0019669658874061856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1769230769230767,258463.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,5 or more bedrooms,bedrooms,A_structural,dummy,binary,0.006,0.014,,,,,,high,Bedroom-count dummy (reference not stated),"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",pct_premium,0.5919451117272434,1.408425250475691,100*(exp(b - se^2/2) - 1),reported,0.0005491287915723828,0.0012813005136688932,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.42857142857142855,609113.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,1 half bathroom,bathrooms,A_structural,dummy,binary,0.073,0.002,,,***,,,high,Half bathrooms (MA only),"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",pct_premium,7.572838545578109,0.2151461073829407,100*(exp(b - se^2/2) - 1),reported,0.04671641470880892,0.00127990177284408,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),36.5,609113.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d,b633c49b2f5879640f919bdc54ae4390ee31d91d:T2-c2,2,2,16,2 or more half bathrooms,bathrooms,A_structural,dummy,binary,0.112,0.007,,,***,,,high,Half bathrooms (MA only),"logprice (log sale price, USD)",log,FE_panel,609123.0,0.7,se,"Massachusetts (Greater Boston, 145 towns), 1987-2012; town FE + year dummies; clustered SE",pct_premium,11.848545741565042,0.7829590024515317,100*(exp(b - se^2/2) - 1),reported,0.020496504593168305,0.001281031537073019,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.0,609113.0,binary,,2019.0,United States,North America,High income,1987.0,2013.0,single_family,transaction,working_paper,True,True,clustered,,2000.0,panel,other,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c1,3,1,14,Age,age,A_structural,level,years,-0.005,0.001,,,***,,,high,"building age in years; age-category dummies (construction periods, ref post-2000) also included","log(asking rent, EUR per m2)",log,SAC,16004.0,,se,"Rental apartments, Dortmund 2007-2016 (30% random sample); lambda 1.271***, rho 1.176***",semi_elasticity,-0.5,0.1,100*b/1 (per year),reported,-0.03950502160492692,0.007901004320985386,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,15994.0,years,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c2,3,2,14,Age,age,A_structural,level,years,-0.008,0.001,,,***,,,high,"building age in years; age-category dummies (construction periods, ref post-2000) also included","log(asking price, EUR per m2)",log,SAC,15786.0,,se,"Apartments for sale, Dortmund 2007-2016; lambda 0.743***, rho 1.392***",semi_elasticity,-0.8,0.1,100*b/1 (per year),reported,-0.06356417261637282,0.007945521577046602,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.0,15776.0,years,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c3,3,3,14,Age,age,A_structural,level,years,-0.005,0.001,,,***,,,high,"building age in years; age-category dummies (construction periods, ref post-2000) also included","log(asking price, EUR per m2)",log,SAC,25347.0,,se,"1-/2-family homes for sale, Dortmund 2008-2015; lambda 0.244***, rho 1.447***",semi_elasticity,-0.5,0.1,100*b/1 (per year),reported,-0.031396284457030986,0.0062792568914061975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,25337.0,years,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c1,3,1,14,Floor space (log),living_area,A_structural,log,m2,-0.106,0.008,,,***,,,high,"dependent variable is per m2, so this is a size (dis)count on price/rent per m2","log(asking rent, EUR per m2)",log,SAC,16004.0,,se,"Rental apartments, Dortmund 2007-2016 (30% random sample); lambda 1.271***, rho 1.176***",elasticity,-0.106,0.008,b (log-log),reported,-0.10419976598072,0.007864133281563775,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.25,15994.0,m2,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,True
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c2,3,2,14,Floor space (log),living_area,A_structural,log,m2,0.097,0.014,,,***,,,high,"dependent variable is per m2, so this is a size (dis)count on price/rent per m2","log(asking price, EUR per m2)",log,SAC,15786.0,,se,"Apartments for sale, Dortmund 2007-2016; lambda 0.743***, rho 1.392***",elasticity,0.097,0.014,b (log-log),reported,0.055078929578326996,0.007949536227799772,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.928571428571429,15776.0,m2,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c3,3,3,14,Floor space (log),living_area,A_structural,log,m2,0.671,0.013,,,***,,,high,"dependent variable is per m2, so this is a size (dis)count on price/rent per m2","log(asking price, EUR per m2)",log,SAC,25347.0,,se,"1-/2-family homes for sale, Dortmund 2008-2015; lambda 0.244***, rho 1.447***",elasticity,0.671,0.013,b (log-log),reported,0.3084545990071641,0.005976020547083655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),51.61538461538462,25337.0,m2,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c1,3,1,14,No of rooms,bedrooms,A_structural,level,count,0.014,0.003,,,***,,,high,number of rooms (not bedrooms),"log(asking rent, EUR per m2)",log,SAC,16004.0,,se,"Rental apartments, Dortmund 2007-2016 (30% random sample); lambda 1.271***, rho 1.176***",semi_elasticity,1.4000000000000001,0.3,100*b/1 (per unit count),reported,0.03687506239428105,0.007901799084488797,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.666666666666667,15994.0,count,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c2,3,2,14,No of rooms,bedrooms,A_structural,level,count,0.007,0.004,,,,,,high,number of rooms (not bedrooms),"log(asking price, EUR per m2)",log,SAC,15786.0,,se,"Apartments for sale, Dortmund 2007-2016; lambda 0.743***, rho 1.392***",semi_elasticity,0.7000000000000001,0.4,100*b/1 (per unit count),reported,0.013931486244953401,0.007960849282830515,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.75,15776.0,count,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c3,3,3,14,No of rooms,bedrooms,A_structural,level,count,-0.014,0.002,,,***,,,high,number of rooms (not bedrooms),"log(asking price, EUR per m2)",log,SAC,25347.0,,se,"1-/2-family homes for sale, Dortmund 2008-2015; lambda 0.244***, rho 1.447***",semi_elasticity,-1.4000000000000001,0.2,100*b/1 (per unit count),reported,-0.04393401582816633,0.006276287975452332,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,25337.0,count,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c1,3,1,14,Multi-family housing: Floor level,floor_level,A_structural,level,count,-0.008,0.001,,,***,,,high,floor level of apartment in multi-family building,"log(asking rent, EUR per m2)",log,SAC,16004.0,,se,"Rental apartments, Dortmund 2007-2016 (30% random sample); lambda 1.271***, rho 1.176***",semi_elasticity,-0.8,0.1,100*b/1 (per unit count),reported,-0.06313123135698485,0.007891403919623105,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.0,15994.0,count,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c2,3,2,14,Multi-family housing: Floor level,floor_level,A_structural,level,count,-0.018,0.002,,,***,,,high,floor level of apartment in multi-family building,"log(asking price, EUR per m2)",log,SAC,15786.0,,se,"Apartments for sale, Dortmund 2007-2016; lambda 0.743***, rho 1.392***",semi_elasticity,-1.7999999999999998,0.2,100*b/1 (per unit count),reported,-0.07147135179576962,0.00794126131064107,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.0,15776.0,count,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c1,3,1,14,Good state of house,condition,A_structural,binary,binary,0.071,0.004,,,***,,,high,,"log(asking rent, EUR per m2)",log,SAC,16004.0,,se,"Rental apartments, Dortmund 2007-2016 (30% random sample); lambda 1.271***, rho 1.176***",pct_premium,7.357263725290486,0.429432490347343,100*(exp(b - se^2/2) - 1),reported,0.13899009727387757,0.007830428015429724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.749999999999996,15994.0,binary,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c2,3,2,14,Good state of house,condition,A_structural,binary,binary,0.083,0.006,,,***,,,high,,"log(asking price, EUR per m2)",log,SAC,15786.0,,se,"Apartments for sale, Dortmund 2007-2016; lambda 0.743***, rho 1.392***",pct_premium,8.652225097170296,0.6519250851289429,100*(exp(b - se^2/2) - 1),reported,0.10947381891083018,0.00791377004174676,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.833333333333334,15776.0,binary,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c3,3,3,14,Good state of house,condition,A_structural,binary,binary,0.038,0.006,,,***,,,high,,"log(asking price, EUR per m2)",log,SAC,25347.0,,se,"1-/2-family homes for sale, Dortmund 2008-2015; lambda 0.244***, rho 1.447***",pct_premium,3.8712535884579458,0.6232387397270986,100*(exp(b - se^2/2) - 1),reported,0.03975678485815569,0.006277387082866688,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.333333333333333,25337.0,binary,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c1,3,1,14,Bad state of house,condition,A_structural,binary,binary,-0.023,0.004,,,***,,,high,,"log(asking rent, EUR per m2)",log,SAC,16004.0,,se,"Rental apartments, Dortmund 2007-2016 (30% random sample); lambda 1.271***, rho 1.176***",pct_premium,-2.2745334295320774,0.39090499350931085,100*(exp(b - se^2/2) - 1),reported,-0.04541934631035977,0.007899016749627785,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.75,15994.0,binary,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c2,3,2,14,Bad state of house,condition,A_structural,binary,binary,-0.105,0.006,,,***,,,high,,"log(asking price, EUR per m2)",log,SAC,15786.0,,se,"Apartments for sale, Dortmund 2007-2016; lambda 0.743***, rho 1.392***",pct_premium,-9.969168310928922,0.5401947135517594,100*(exp(b - se^2/2) - 1),reported,-0.13799541096850645,0.007885452055343226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.5,15776.0,binary,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c3,3,3,14,Bad state of house,condition,A_structural,binary,binary,-0.085,0.005,,,***,,,high,,"log(asking price, EUR per m2)",log,SAC,25347.0,,se,"1-/2-family homes for sale, Dortmund 2008-2015; lambda 0.244***, rho 1.447***",pct_premium,-8.149919693033924,0.4592561422007287,100*(exp(b - se^2/2) - 1),reported,-0.10619608598571659,0.006246828587395093,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.0,25337.0,binary,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c1,3,1,14,Population (log),density,F_neighbourhood,log,count,0.009,0.007,,,,,,high,"annual population of the 5-digit postcode district (log), not density per km2","log(asking rent, EUR per m2)",log,SAC,16004.0,,se,"Rental apartments, Dortmund 2007-2016 (30% random sample); lambda 1.271***, rho 1.176***",elasticity,0.009,0.007,b (log-log),reported,0.010165844948541782,0.007906768293310275,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2857142857142856,15994.0,count,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c2,3,2,14,Population (log),density,F_neighbourhood,log,count,0.033,0.017,,,**,,,high,"annual population of the 5-digit postcode district (log), not density per km2","log(asking price, EUR per m2)",log,SAC,15786.0,,se,"Apartments for sale, Dortmund 2007-2016; lambda 0.743***, rho 1.392***",elasticity,0.033,0.017,b (log-log),reported,0.015453067774063012,0.007960671277547612,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9411764705882353,15776.0,count,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf,b79aa4750ced5d8cf3b4aca71bb4a545f71e34bf:T3-c3,3,3,14,Population (log),density,F_neighbourhood,log,count,0.059,0.014,,,***,,,high,"annual population of the 5-digit postcode district (log), not density per km2","log(asking price, EUR per m2)",log,SAC,25347.0,,se,"1-/2-family homes for sale, Dortmund 2008-2015; lambda 0.244***, rho 1.447***",elasticity,0.059,0.014,b (log-log),reported,0.026466360405839055,0.006280153316639775,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.214285714285714,25337.0,count,,2021.0,Germany,Europe,High income,2007.0,2016.0,mixed,listing,journal,True,True,robust,,2011.5,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M0,2,M0,13,LotSize,lot_size,A_structural,log,m2,-0.173,,-3.0,,,,,medium,ln(LotSize); lot size in m2,ln real selling price (1998 NOK),log,OLS,4392.0,0.822,t,M0 base; year dummies 2004-2007 included (not extracted),elasticity,-0.173,0.057666666666666665,b (log-log),|b/t|,-0.045273027347836885,0.015091009115945629,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M0,2,M0,13,Age,age,A_structural,log,years,-0.2017,,-11.75,,,,,medium,ln(Age) of building (all continuous variables in logarithmic form),ln real selling price (1998 NOK),log,OLS,4392.0,0.822,t,M0 base; year dummies 2004-2007 included (not extracted),elasticity,-0.2017,0.01716595744680851,b (log-log),|b/t|,-0.17476950115677747,0.014874000098449148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.75,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M0,2,M0,13,Garage,garage,A_structural,binary,binary,0.042,,7.21,,,,,medium,Garage dummy,ln real selling price (1998 NOK),log,OLS,4392.0,0.822,t,M0 base; year dummies 2004-2007 included (not extracted),pct_premium,4.287678439562348,0.6075113468451048,100*(exp(b - se^2/2) - 1),|b/t|,0.10827749479917226,0.01501768305120281,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.21,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M0,2,M0,13,LivingArea,living_area,A_structural,log,m2,0.51,,42.77,,,,,medium,ln(LivingArea); printed as 'Size of house' in Table A.1,ln real selling price (1998 NOK),log,OLS,4392.0,0.822,t,M0 base; year dummies 2004-2007 included (not extracted),elasticity,0.51,0.011924245966799158,b (log-log),|b/t|,0.5426864083938541,0.012688482777504185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.77,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M0,2,M0,13,DistCBD,cbd_distance,D_location,log,minutes,-0.056,,-3.14,,,,,medium,"ln(travel time by car to CBD, minutes)",ln real selling price (1998 NOK),log,OLS,4392.0,0.822,t,M0 base; year dummies 2004-2007 included (not extracted),elasticity,-0.056,0.017834394904458598,b (log-log),|b/t|,-0.04738113108966141,0.015089532194159684,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.14,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M1,2,M1,13,LotSize,lot_size,A_structural,log,m2,-0.204,,-3.62,,,,,medium,ln(LotSize); lot size in m2,ln real selling price (1998 NOK),log,OLS,4392.0,0.824,t,M1 = M0 + gravity accessibility; year dummies 2004-2007 included (not extracted),elasticity,-0.204,0.05635359116022099,b (log-log),|b/t|,-0.05460393898702091,0.015083961046138373,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.62,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M1,2,M1,13,Age,age,A_structural,log,years,-0.192,,-11.38,,,,,medium,ln(Age) of building (all continuous variables in logarithmic form),ln real selling price (1998 NOK),log,OLS,4392.0,0.824,t,M1 = M0 + gravity accessibility; year dummies 2004-2007 included (not extracted),elasticity,-0.192,0.016871704745166957,b (log-log),|b/t|,-0.1694265897727925,0.014888101034516037,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.38,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M1,2,M1,13,Garage,garage,A_structural,binary,binary,0.043,,7.44,,,,,medium,Garage dummy,ln real selling price (1998 NOK),log,OLS,4392.0,0.824,t,M1 = M0 + gravity accessibility; year dummies 2004-2007 included (not extracted),pct_premium,4.392045944398593,0.6033512026690367,100*(exp(b - se^2/2) - 1),|b/t|,0.11168913222002314,0.015011980137099885,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.44,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M1,2,M1,13,LivingArea,living_area,A_structural,log,m2,0.505,,42.69,,,,,medium,ln(LivingArea); printed as 'Size of house' in Table A.1,ln real selling price (1998 NOK),log,OLS,4392.0,0.824,t,M1 = M0 + gravity accessibility; year dummies 2004-2007 included (not extracted),elasticity,0.505,0.011829468259545561,b (log-log),|b/t|,0.5419696871778356,0.01269547170714068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.69,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M1,2,M1,13,DistCBD,cbd_distance,D_location,log,minutes,-0.104,,-5.36,,,,,medium,"ln(travel time by car to CBD, minutes)",ln real selling price (1998 NOK),log,OLS,4392.0,0.824,t,M1 = M0 + gravity accessibility; year dummies 2004-2007 included (not extracted),elasticity,-0.104,0.019402985074626865,b (log-log),|b/t|,-0.0807066967898395,0.015057219550343188,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.36,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M1,2,M1,13,ACCESS,employment_access,D_location,log,index,0.064,,6.48,,,,,medium,ln of gravity-based labour market accessibility measure (eq. 2),ln real selling price (1998 NOK),log,OLS,4392.0,0.824,t,M1 = M0 + gravity accessibility; year dummies 2004-2007 included (not extracted),elasticity,0.064,0.009876543209876543,b (log-log),|b/t|,0.09742443995522455,0.015034635795559342,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.48,4382.0,index,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M2,2,M2,13,LotSize,lot_size,A_structural,log,m2,-0.167,,-2.91,,,,,medium,ln(LotSize); lot size in m2,ln real selling price (1998 NOK),log,OLS,4392.0,0.823,t,"M2 = M0 + IN-COM, OUT-COM; year dummies 2004-2007 included (not extracted)",elasticity,-0.167,0.057388316151202746,b (log-log),|b/t|,-0.043917496562004256,0.015091923217183594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.91,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M2,2,M2,13,Age,age,A_structural,log,years,-0.205,,-11.84,,,,,medium,ln(Age) of building (all continuous variables in logarithmic form),ln real selling price (1998 NOK),log,OLS,4392.0,0.823,t,"M2 = M0 + IN-COM, OUT-COM; year dummies 2004-2007 included (not extracted)",elasticity,-0.205,0.01731418918918919,b (log-log),|b/t|,-0.176066816209356,0.014870508125790199,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.84,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M2,2,M2,13,Garage,garage,A_structural,binary,binary,0.04,,6.93,,,,,medium,Garage dummy,ln real selling price (1998 NOK),log,OLS,4392.0,0.823,t,"M2 = M0 + IN-COM, OUT-COM; year dummies 2004-2007 included (not extracted)",pct_premium,4.079343648456901,0.6007565796204261,100*(exp(b - se^2/2) - 1),|b/t|,0.10411903899371747,0.015024392351185783,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.93,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M2,2,M2,13,LivingArea,living_area,A_structural,log,m2,0.51,,42.8,,,,,medium,ln(LivingArea); printed as 'Size of house' in Table A.1,ln real selling price (1998 NOK),log,OLS,4392.0,0.823,t,"M2 = M0 + IN-COM, OUT-COM; year dummies 2004-2007 included (not extracted)",elasticity,0.51,0.01191588785046729,b (log-log),|b/t|,0.5429548736775509,0.01268586153452222,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.8,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M2,2,M2,13,DistCBD,cbd_distance,D_location,log,minutes,-0.043,,-2.28,,,,,medium,"ln(travel time by car to CBD, minutes)",ln real selling price (1998 NOK),log,OLS,4392.0,0.823,t,"M2 = M0 + IN-COM, OUT-COM; year dummies 2004-2007 included (not extracted)",elasticity,-0.043,0.018859649122807017,b (log-log),|b/t|,-0.03442240496913621,0.015097546039094831,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.28,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M2,2,M2,13,IN-COM,employment_access,D_location,log,share,-0.03,,-2.06,,,,,medium,"ln of share of jobs in zone held by in-commuters (observed in-commuting), zone level",ln real selling price (1998 NOK),log,OLS,4392.0,0.823,t,"M2 = M0 + IN-COM, OUT-COM; year dummies 2004-2007 included (not extracted)",elasticity,-0.03,0.014563106796116504,b (log-log),|b/t|,-0.031104329692016652,0.015099189170881868,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.06,4382.0,share,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M3,2,M3,13,LotSize,lot_size,A_structural,log,m2,-0.203,,-3.55,,,,,medium,ln(LotSize); lot size in m2,ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M3 = M2 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,-0.203,0.057183098591549304,b (log-log),|b/t|,-0.053551119442545876,0.015084822378181937,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.55,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M3,2,M3,13,Age,age,A_structural,log,years,-0.199,,-11.72,,,,,medium,ln(Age) of building (all continuous variables in logarithmic form),ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M3 = M2 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,-0.199,0.016979522184300343,b (log-log),|b/t|,-0.1743368600992313,0.014875158711538505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.72,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M3,2,M3,13,Garage,garage,A_structural,binary,binary,0.042,,7.16,,,,,medium,Garage dummy,ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M3 = M2 + ACCESS; year dummies 2004-2007 included (not extracted),pct_premium,4.287653640701494,0.6117537445186041,100*(exp(b - se^2/2) - 1),|b/t|,0.10753532372030038,0.015018899960935804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.16,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M3,2,M3,13,LivingArea,living_area,A_structural,log,m2,0.503,,42.66,,,,,medium,ln(LivingArea); printed as 'Size of house' in Table A.1,ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M3 = M2 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,0.503,0.011790904828879513,b (log-log),|b/t|,0.5417006113926338,0.012698092156414294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.66,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M3,2,M3,13,DistCBD,cbd_distance,D_location,log,minutes,-0.114,,-5.57,,,,,medium,"ln(travel time by car to CBD, minutes)",ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M3 = M2 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,-0.114,0.020466786355475764,b (log-log),|b/t|,-0.08384689918499381,0.01505330326481038,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.57,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M3,2,M3,13,ACCESS,employment_access,D_location,log,index,0.096,,7.79,,,,,medium,ln of gravity-based labour market accessibility measure (eq. 2),ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M3 = M2 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,0.096,0.012323491655969191,b (log-log),|b/t|,0.11687314770437816,0.015002971463976658,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.79,4382.0,index,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M3,2,M3,13,IN-COM,employment_access,D_location,log,share,-0.083,,-4.9,,,,,medium,"ln of share of jobs in zone held by in-commuters (observed in-commuting), zone level",ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M3 = M2 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,-0.083,0.01693877551020408,b (log-log),|b/t|,-0.07381988100231861,0.01506528183720788,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.9,4382.0,share,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M3,2,M3,13,OUT-COM,employment_access,D_location,log,share,0.001,,2.31,,,,,medium,"ln of share of working population in zone commuting out (observed out-commuting), zone level",ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M3 = M2 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,0.001,0.0004329004329004329,b (log-log),|b/t|,0.03487478405113943,0.015097309113047375,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.31,4382.0,share,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M4,2,M4,13,LotSize,lot_size,A_structural,log,m2,-0.177,,-3.1,,,,,medium,ln(LotSize); lot size in m2,ln real selling price (1998 NOK),log,OLS,4392.0,0.823,t,"M4 = M0 + MCT, MCT2; year dummies 2004-2007 included (not extracted)",elasticity,-0.177,0.05709677419354838,b (log-log),|b/t|,-0.046778879099184247,0.01508996099973685,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.1,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M4,2,M4,13,Age,age,A_structural,log,years,-0.204,,-11.75,,,,,medium,ln(Age) of building (all continuous variables in logarithmic form),ln real selling price (1998 NOK),log,OLS,4392.0,0.823,t,"M4 = M0 + MCT, MCT2; year dummies 2004-2007 included (not extracted)",elasticity,-0.204,0.017361702127659574,b (log-log),|b/t|,-0.17476950115677747,0.014874000098449148,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.75,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M4,2,M4,13,Garage,garage,A_structural,binary,binary,0.042,,7.19,,,,,medium,Garage dummy,ln real selling price (1998 NOK),log,OLS,4392.0,0.823,t,"M4 = M0 + MCT, MCT2; year dummies 2004-2007 included (not extracted)",pct_premium,4.287668582086024,0.609201225417692,100*(exp(b - se^2/2) - 1),|b/t|,0.10798064802167871,0.015018170795782852,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.19,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M4,2,M4,13,LivingArea,living_area,A_structural,log,m2,0.511,,42.99,,,,,medium,ln(LivingArea); printed as 'Size of house' in Table A.1,ln real selling price (1998 NOK),log,OLS,4392.0,0.823,t,"M4 = M0 + MCT, MCT2; year dummies 2004-2007 included (not extracted)",elasticity,0.511,0.01188648522912305,b (log-log),|b/t|,0.5446512925740695,0.012669255468110477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.99,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M4,2,M4,13,DistCBD,cbd_distance,D_location,log,minutes,-0.076,,-3.9,,,,,medium,"ln(travel time by car to CBD, minutes)",ln real selling price (1998 NOK),log,OLS,4392.0,0.823,t,"M4 = M0 + MCT, MCT2; year dummies 2004-2007 included (not extracted)",elasticity,-0.076,0.019487179487179488,b (log-log),|b/t|,-0.058813361658477246,0.015080349143199294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.9,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M4,2,M4,13,MCT,employment_access,D_location,log,minutes,0.393,,2.45,,,,,medium,ln of mean commuting time of residents of the zone (minutes),ln real selling price (1998 NOK),log,OLS,4392.0,0.823,t,"M4 = M0 + MCT, MCT2; year dummies 2004-2007 included (not extracted)",elasticity,0.393,0.16040816326530613,b (log-log),|b/t|,0.0369855985306437,0.015096162665568855,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.45,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M5,2,M5,13,LotSize,lot_size,A_structural,log,m2,-0.221,,-3.92,,,,,medium,ln(LotSize); lot size in m2,ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M5 = M4 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,-0.221,0.056377551020408166,b (log-log),|b/t|,-0.05911391736854921,0.015080080961364593,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.92,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,True
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M5,2,M5,13,Age,age,A_structural,log,years,-0.196,,-11.47,,,,,medium,ln(Age) of building (all continuous variables in logarithmic form),ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M5 = M4 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,-0.196,0.017088055797733218,b (log-log),|b/t|,-0.17072761151925334,0.01488470893803429,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.47,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M5,2,M5,13,Garage,garage,A_structural,binary,binary,0.04,,7.06,,,,,medium,Garage dummy,ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M5 = M4 + ACCESS; year dummies 2004-2007 included (not extracted),pct_premium,4.079406910011363,0.5896944896274154,100*(exp(b - se^2/2) - 1),|b/t|,0.10605044328766768,0.015021309247545,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.06,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M5,2,M5,13,LivingArea,living_area,A_structural,log,m2,0.504,,42.88,,,,,medium,ln(LivingArea); printed as 'Size of house' in Table A.1,ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M5 = M4 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,0.504,0.011753731343283582,b (log-log),|b/t|,0.5436699678778335,0.012678870519539028,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.88,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M5,2,M5,13,DistCBD,cbd_distance,D_location,log,minutes,-0.171,,-7.4,,,,,medium,"ln(travel time by car to CBD, minutes)",ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M5 = M4 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,-0.171,0.023108108108108108,b (log-log),|b/t|,-0.11109608411504408,0.015012984339870823,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.4,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M5,2,M5,13,ACCESS,employment_access,D_location,log,index,0.114,,7.06,,,,,medium,ln of gravity-based labour market accessibility measure (eq. 2),ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M5 = M4 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,0.114,0.01614730878186969,b (log-log),|b/t|,0.10605044328766768,0.015021309247545,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.06,4382.0,index,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T2-M5,2,M5,13,MCT,employment_access,D_location,log,minutes,0.399,,2.29,,,,,medium,ln of mean commuting time of residents of the zone (minutes),ln real selling price (1998 NOK),log,OLS,4392.0,0.826,t,M5 = M4 + ACCESS; year dummies 2004-2007 included (not extracted),elasticity,0.399,0.17423580786026202,b (log-log),|b/t|,0.034573200361178544,0.015097467406628184,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.29,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,ols,journal,True,True,True
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-direct,3,M3 direct,17,Lotsize,lot_size,A_structural,log,m2,-0.201,,-6.47,,,,,high,"ln(LotSize); lot size in m2; SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.201,0.031066460587326122,b (log-log),|b/t|,-0.0972755173426374,0.015034855848939318,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.47,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-direct,3,M3 direct,17,Age,age,A_structural,log,years,-0.196,,-11.93,,,,,high,"ln(Age) of building (all continuous variables in logarithmic form); SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.196,0.016429170159262364,b (log-log),|b/t|,-0.17736321449595122,0.014866991994631283,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.93,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-direct,3,M3 direct,17,Garage,garage,A_structural,binary,binary,0.04,,6.48,,,,,high,"Garage dummy; SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,pct_premium,4.07909448816981,0.6424757865385112,100*(exp(b - se^2/2) - 1),|b/t|,0.09742443995522455,0.015034635795559342,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.48,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-direct,3,M3 direct,17,LivingArea,living_area,A_structural,log,m2,0.503,,52.91,,,,,high,"ln(LivingArea); printed as 'Size of house' in Table A.1; SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,0.503,0.009506709506709508,b (log-log),|b/t|,0.624354352602825,0.01180030906450246,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),52.91,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-direct,3,M3 direct,17,DistCBD,cbd_distance,D_location,log,minutes,-0.081,,-3.45,,,,,high,"ln(travel time by car to CBD, minutes); SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.081,0.023478260869565216,b (log-log),|b/t|,-0.05204678253968151,0.015086023924545363,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.45,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-direct,3,M3 direct,17,ACCESS,employment_access,D_location,log,index,0.084,,7.23,,,,,high,"ln of gravity-based labour market accessibility measure (eq. 2); SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,0.084,0.011618257261410789,b (log-log),|b/t|,0.10857431261633571,0.01501719399949318,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.23,4382.0,index,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-direct,3,M3 direct,17,IN-COM,employment_access,D_location,log,share,-0.073,,-4.67,,,,,high,"ln of share of jobs in zone held by in-commuters (observed in-commuting), zone level; SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.073,0.01563169164882227,b (log-log),|b/t|,-0.07037244627395978,0.015069046311340423,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.67,4382.0,share,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-direct,3,M3 direct,17,OUT-COM,employment_access,D_location,log,share,0.04,,2.36,,,,,high,"ln of share of working population in zone commuting out (observed out-commuting), zone level; SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,0.04,0.01694915254237288,b (log-log),|b/t|,0.035628701415409844,0.015096907379410954,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.36,4382.0,share,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-total,3,M3 total,17,Lotsize,lot_size,A_structural,log,m2,-0.051,,-0.7,,,,,high,"ln(LotSize); lot size in m2; SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.051,0.07285714285714286,b (log-log),|b/t|,-0.01057395780702276,0.015105654010032513,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-total,3,M3 total,17,Age,age,A_structural,log,years,-0.158,,-4.13,,,,,high,"ln(Age) of building (all continuous variables in logarithmic form); SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.158,0.038256658595641646,b (log-log),|b/t|,-0.062268766384938126,0.015077183144052816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.13,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-total,3,M3 total,17,Garage,garage,A_structural,binary,binary,0.066,,4.7,,,,,high,"Garage dummy; SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,pct_premium,6.812139878227286,1.5000630496373524,100*(exp(b - se^2/2) - 1),|b/t|,0.07082225736780139,0.015068565397404553,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.7,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-total,3,M3 total,17,LivingArea,living_area,A_structural,log,m2,0.466,,21.11,,,,,high,"ln(LivingArea); printed as 'Size of house' in Table A.1; SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,0.466,0.02207484604452866,b (log-log),|b/t|,0.30382335147776945,0.014392389932627639,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.11,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-total,3,M3 total,17,DistCBD,cbd_distance,D_location,log,minutes,-0.153,,-4.86,,,,,high,"ln(travel time by car to CBD, minutes); SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.153,0.03148148148148148,b (log-log),|b/t|,-0.07322051369806601,0.015065949320589715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.86,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-total,3,M3 total,17,ACCESS,employment_access,D_location,log,index,0.12,,6.99,,,,,high,"ln of gravity-based labour market accessibility measure (eq. 2); SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,0.12,0.017167381974248927,b (log-log),|b/t|,0.10501060408894254,0.015022976264512523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.99,4382.0,index,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-total,3,M3 total,17,IN-COM,employment_access,D_location,log,share,-0.136,,-6.18,,,,,high,"ln of share of jobs in zone held by in-commuters (observed in-commuting), zone level; SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.136,0.022006472491909387,b (log-log),|b/t|,-0.09295395831506333,0.01504109357848921,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.18,4382.0,share,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,True
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M3-total,3,M3 total,17,OUT-COM,employment_access,D_location,log,share,0.073,,2.72,,,,,high,"ln of share of working population in zone commuting out (observed out-commuting), zone level; SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M3; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,0.073,0.026838235294117642,b (log-log),|b/t|,0.04105503280920673,0.015093762062208357,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.72,4382.0,share,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-direct,3,M5 direct,17,Lotsize,lot_size,A_structural,log,m2,-0.173,,-4.92,,,,,high,"ln(LotSize); lot size in m2; SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.173,0.03516260162601626,b (log-log),|b/t|,-0.07411953470064267,0.015064946077366395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.92,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-direct,3,M5 direct,17,Age,age,A_structural,log,years,-0.161,,-9.39,,,,,high,"ln(Age) of building (all continuous variables in logarithmic form); SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.161,0.01714589989350373,b (log-log),|b/t|,-0.14044409064275226,0.014956772166427289,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.39,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-direct,3,M5 direct,17,Garage,garage,A_structural,binary,binary,0.039,,6.78,,,,,high,"Garage dummy; SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,pct_premium,3.9753281856929945,0.5980980658164624,100*(exp(b - se^2/2) - 1),|b/t|,0.10188903227875278,0.015027880867072678,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.78,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-direct,3,M5 direct,17,LivingArea,living_area,A_structural,log,m2,0.487,,53.64,,,,,high,"ln(LivingArea); printed as 'Size of house' in Table A.1; SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,0.487,0.009079045488441462,b (log-log),|b/t|,0.6295683756682009,0.011736919755186443,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),53.64,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-direct,3,M5 direct,17,DistCBD,cbd_distance,D_location,log,minutes,-0.036,,0.4,,,,,high,"ln(travel time by car to CBD, minutes); SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.036,0.08999999999999998,b (log-log),|b/t|,0.0060424891069786706,0.015106222767446676,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-direct,3,M5 direct,17,ACCESS,employment_access,D_location,log,index,0.161,,2.0,,,,,high,"ln of gravity-based labour market accessibility measure (eq. 2); SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,0.161,0.0805,b (log-log),|b/t|,0.030199216944456812,0.015099608472228406,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,4382.0,index,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-direct,3,M5 direct,17,MCT,employment_access,D_location,log,minutes,0.247,,1.8,,,,,high,"ln of mean commuting time of residents of the zone (minutes); SDM direct impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; direct impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,0.247,0.13722222222222222,b (log-log),|b/t|,0.027181650351384177,0.015100916861880097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-total,3,M5 total,17,Lotsize,lot_size,A_structural,log,m2,-0.161,,-1.84,,,,,high,"ln(LotSize); lot size in m2; SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.161,0.0875,b (log-log),|b/t|,-0.027785225763158658,0.015100666175629704,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.84,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-total,3,M5 total,17,Age,age,A_structural,log,years,-0.285,,-6.22,,,,,high,"ln(Age) of building (all continuous variables in logarithmic form); SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.285,0.04581993569131833,b (log-log),|b/t|,-0.09355035345480538,0.01504024975157643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.22,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-total,3,M5 total,17,Garage,garage,A_structural,binary,binary,0.048,,2.86,,,,,high,"Garage dummy; SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,pct_premium,4.902290244079954,1.7608458550900208,100*(exp(b - se^2/2) - 1),|b/t|,0.04316431859963904,0.015092419090782886,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.86,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-total,3,M5 total,17,LivingArea,living_area,A_structural,log,m2,0.581,,20.94,,,,,high,"ln(LivingArea); printed as 'Size of house' in Table A.1; SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,0.581,0.02774594078319006,b (log-log),|b/t|,0.30160002452302365,0.014403057522589477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.94,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-total,3,M5 total,17,DistCBD,cbd_distance,D_location,log,minutes,-0.139,,-4.23,,,,,high,"ln(travel time by car to CBD, minutes); SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,-0.139,0.03286052009456265,b (log-log),|b/t|,-0.06377042549798478,0.015075750708743445,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.23,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-total,3,M5 total,17,ACCESS,employment_access,D_location,log,index,0.109,,5.22,,,,,high,"ln of gravity-based labour market accessibility measure (eq. 2); SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,0.109,0.02088122605363985,b (log-log),|b/t|,0.07861188678311787,0.015059748425884652,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.22,4382.0,index,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:T3-M5-total,3,M5 total,17,MCT,employment_access,D_location,log,minutes,0.125,,3.43,,,,,high,"ln of mean commuting time of residents of the zone (minutes); SDM total impact, z-value",ln real selling price (1998 NOK),log,other,4392.0,,t,Spatial Durbin model (k=3 nearest neighbours) variant of M5; total impact summary (LeSage-Pace); z-values in parentheses; MCT2 not reported in this table,elasticity,0.125,0.03644314868804664,b (log-log),|b/t|,0.05174587230763722,0.015086260147999192,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.43,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,other,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M0,A.1,M0,22,Lotsize,lot_size,A_structural,log,m2,-0.187,,-6.11,,,,,high,ln(LotSize); lot size in m2,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M0 base; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.187,0.03060556464811784,b (log-log),|b/t|,-0.09191002640275243,0.015042557512725438,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.11,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M0,A.1,M0,22,Age,age,A_structural,log,years,-0.1809,,-10.71,,,,,high,ln(Age) of building (all continuous variables in logarithmic form),ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M0 base; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.1809,0.016890756302521008,b (log-log),|b/t|,-0.15971375325810105,0.014912582003557518,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.71,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M0,A.1,M0,22,Garage,garage,A_structural,binary,binary,0.039,,6.71,,,,,high,Garage dummy,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M0 base; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",pct_premium,3.9752921083118675,0.6043375389322825,100*(exp(b - se^2/2) - 1),|b/t|,0.10084783449875753,0.015029483531856562,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.71,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M0,A.1,M0,22,Size of house,living_area,A_structural,log,m2,0.493,,52.31,,,,,high,ln(LivingArea); printed as 'Size of house' in Table A.1,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M0 base; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,0.493,0.009424584209520168,b (log-log),|b/t|,0.6200054043700826,0.011852521589946137,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),52.31,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M0,A.1,M0,22,DistCBD,cbd_distance,D_location,log,minutes,-0.0574,,-2.58,,,,,high,"ln(travel time by car to CBD, minutes)",ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M0 base; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.0574,0.022248062015503875,b (log-log),|b/t|,-0.03894519797915314,0.015095037976415947,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.58,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M1,A.1,M1,22,Lotsize,lot_size,A_structural,log,m2,-0.204,,-6.61,,,,,high,ln(LotSize); lot size in m2,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M1 = M0 + gravity accessibility; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.204,0.030862329803328287,b (log-log),|b/t|,-0.09935983492987666,0.015031745072598586,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.61,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M1,A.1,M1,22,Age,age,A_structural,log,years,-0.178,,-10.51,,,,,high,ln(Age) of building (all continuous variables in logarithmic form),ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M1 = M0 + gravity accessibility; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.178,0.01693625118934348,b (log-log),|b/t|,-0.15680525090912034,0.014919624253960073,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.51,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M1,A.1,M1,22,Garage,garage,A_structural,binary,binary,0.04,,6.82,,,,,high,Garage dummy,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M1 = M0 + gravity accessibility; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",pct_premium,4.079287269819032,0.6104462018723684,100*(exp(b - se^2/2) - 1),|b/t|,0.10248385235746159,0.01502695782367472,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.82,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M1,A.1,M1,22,Size of house,living_area,A_structural,log,m2,0.491,,52.19,,,,,high,ln(LivingArea); printed as 'Size of house' in Table A.1,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M1 = M0 + gravity accessibility; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,0.491,0.009407932554129144,b (log-log),|b/t|,0.6191286854609346,0.01186297538725684,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),52.19,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M1,A.1,M1,22,DistCBD,cbd_distance,D_location,log,minutes,-0.101,,-4.14,,,,,high,"ln(travel time by car to CBD, minutes)",ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M1 = M0 + gravity accessibility; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.101,0.024396135265700485,b (log-log),|b/t|,-0.06241895149709479,0.015077041424419032,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.14,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M1,A.1,M1,22,ACCESS,employment_access,D_location,log,index,0.059,,4.36,,,,,high,ln of gravity-based labour market accessibility measure (eq. 2),ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M1 = M0 + gravity accessibility; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,0.059,0.013532110091743118,b (log-log),|b/t|,0.06572193345224697,0.015073837947763066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.36,4382.0,index,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M2,A.1,M2,22,Lotsize,lot_size,A_structural,log,m2,-0.183,,-5.94,,,,,high,ln(LotSize); lot size in m2,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M2 = M0 + IN-COM, OUT-COM; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.183,0.030808080808080805,b (log-log),|b/t|,-0.08937350774823243,0.015046045075460004,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.94,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M2,A.1,M2,22,Age,age,A_structural,log,years,-0.183,,-10.78,,,,,high,ln(Age) of building (all continuous variables in logarithmic form),ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M2 = M0 + IN-COM, OUT-COM; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.183,0.01697588126159555,b (log-log),|b/t|,-0.16073075130319373,0.014910088247049511,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.78,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M2,A.1,M2,22,Garage,garage,A_structural,binary,binary,0.038,,6.59,,,,,high,Garage dummy,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M2 = M0 + IN-COM, OUT-COM; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",pct_premium,3.8713963927840656,0.5989648990801656,100*(exp(b - se^2/2) - 1),|b/t|,0.09906215468481133,0.015032193427133739,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.59,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M2,A.1,M2,22,Size of house,living_area,A_structural,log,m2,0.493,,52.31,,,,,high,ln(LivingArea); printed as 'Size of house' in Table A.1,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M2 = M0 + IN-COM, OUT-COM; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,0.493,0.009424584209520168,b (log-log),|b/t|,0.6200054043700826,0.011852521589946137,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),52.31,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M2,A.1,M2,22,DistCBD,cbd_distance,D_location,log,minutes,-0.04,,-1.58,,,,,high,"ln(travel time by car to CBD, minutes)",ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M2 = M0 + IN-COM, OUT-COM; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.04,0.02531645569620253,b (log-log),|b/t|,-0.02386147180842529,0.015102197347104612,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.58,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M2,A.1,M2,22,IN-COM,employment_access,D_location,log,share,-0.033,,-1.78,,,,,high,"ln of share of jobs in zone held by in-commuters (observed in-commuting), zone level",ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M2 = M0 + IN-COM, OUT-COM; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.033,0.01853932584269663,b (log-log),|b/t|,-0.026879851455410934,0.01510104014348929,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.78,4382.0,share,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M2,A.1,M2,22,OUT-COM,employment_access,D_location,log,share,-0.006,,-0.22,,,,,high,"ln of share of working population in zone commuting out (observed out-commuting), zone level",ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M2 = M0 + IN-COM, OUT-COM; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.006,0.027272727272727275,b (log-log),|b/t|,-0.0033234113275881047,0.015106415125400476,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.22,4382.0,share,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M3,A.1,M3,22,Lotsize,lot_size,A_structural,log,m2,-0.202,,-6.56,,,,,high,ln(LotSize); lot size in m2,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M3 = M2 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.202,0.03079268292682927,b (log-log),|b/t|,-0.09861558446975101,0.015032863486242533,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.56,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M3,A.1,M3,22,Age,age,A_structural,log,years,-0.182,,-10.82,,,,,high,ln(Age) of building (all continuous variables in logarithmic form),ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M3 = M2 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.182,0.016820702402957487,b (log-log),|b/t|,-0.1613116634893092,0.014908656514723586,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.82,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M3,A.1,M3,22,Garage,garage,A_structural,binary,binary,0.039,,6.7,,,,,high,Garage dummy,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M3 = M2 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",pct_premium,3.9752868618866177,0.6052395352590471,100*(exp(b - se^2/2) - 1),|b/t|,0.10069906482419604,0.015029711167790451,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.7,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M3,A.1,M3,22,Size of house,living_area,A_structural,log,m2,0.49,,52.27,,,,,high,ln(LivingArea); printed as 'Size of house' in Table A.1,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M3 = M2 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,0.49,0.009374402142720489,b (log-log),|b/t|,0.6197134223420983,0.01185600578423758,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),52.27,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M3,A.1,M3,22,DistCBD,cbd_distance,D_location,log,minutes,-0.105,,-3.93,,,,,high,"ln(travel time by car to CBD, minutes)",ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M3 = M2 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.105,0.026717557251908396,b (log-log),|b/t|,-0.05926418920039903,0.01507994636142469,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.93,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M3,A.1,M3,22,ACCESS,employment_access,D_location,log,index,0.088,,5.81,,,,,high,ln of gravity-based labour market accessibility measure (eq. 2),ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M3 = M2 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,0.088,0.015146299483648882,b (log-log),|b/t|,0.08743264033200827,0.015048647217213128,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.81,4382.0,index,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M3,A.1,M3,22,IN-COM,employment_access,D_location,log,share,-0.082,,-4.39,,,,,high,"ln of share of jobs in zone held by in-commuters (observed in-commuting), zone level",ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M3 = M2 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.082,0.018678815489749433,b (log-log),|b/t|,-0.06617217518701116,0.01507338842528728,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.39,4382.0,share,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M3,A.1,M3,22,OUT-COM,employment_access,D_location,log,share,0.034,,1.65,,,,,high,"ln of share of working population in zone commuting out (observed out-commuting), zone level",ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M3 = M2 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,0.034,0.02060606060606061,b (log-log),|b/t|,0.024917983144904877,0.015101807966609015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.65,4382.0,share,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M4,A.1,M4,22,Lotsize,lot_size,A_structural,log,m2,-0.189,,-6.15,,,,,high,ln(LotSize); lot size in m2,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M4 = M0 + MCT, MCT2; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.189,0.03073170731707317,b (log-log),|b/t|,-0.0925065962561703,0.015041722968482975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.15,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M4,A.1,M4,22,Age,age,A_structural,log,years,-0.182,,-10.78,,,,,high,ln(Age) of building (all continuous variables in logarithmic form),ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M4 = M0 + MCT, MCT2; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.182,0.016883116883116885,b (log-log),|b/t|,-0.16073075130319373,0.014910088247049511,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.78,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M4,A.1,M4,22,Garage,garage,A_structural,binary,binary,0.039,,6.68,,,,,high,Garage dummy,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M4 = M0 + MCT, MCT2; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",pct_premium,3.975276298263397,0.6070516296759902,100*(exp(b - se^2/2) - 1),|b/t|,0.10040150521982046,0.015030165452068932,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.68,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M4,A.1,M4,22,Size of house,living_area,A_structural,log,m2,0.493,,52.47,,,,,high,ln(LivingArea); printed as 'Size of house' in Table A.1,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M4 = M0 + MCT, MCT2; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,0.493,0.009395845244901849,b (log-log),|b/t|,0.6211707606320215,0.011838588919992786,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),52.47,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M4,A.1,M4,22,DistCBD,cbd_distance,D_location,log,minutes,-0.074,,-2.96,,,,,high,"ln(travel time by car to CBD, minutes)",ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M4 = M0 + MCT, MCT2; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.074,0.024999999999999998,b (log-log),|b/t|,-0.0446705996472286,0.015091418799739393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.96,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M4,A.1,M4,22,MCT,employment_access,D_location,log,minutes,0.315,,1.48,,,,,high,ln of mean commuting time of residents of the zone (minutes),ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M4 = M0 + MCT, MCT2; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,0.315,0.21283783783783783,b (log-log),|b/t|,0.022352032076768086,0.015102724376194655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.48,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M5,A.1,M5,22,Lotsize,lot_size,A_structural,log,m2,-0.214,,-6.93,,,,,high,ln(LotSize); lot size in m2,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M5 = M4 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.214,0.03088023088023088,b (log-log),|b/t|,-0.10411903899371747,0.015024392351185783,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.93,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,True
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M5,A.1,M5,22,Age,age,A_structural,log,years,-0.18,,-10.67,,,,,high,ln(Age) of building (all continuous variables in logarithmic form),ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M5 = M4 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.18,0.016869728209934393,b (log-log),|b/t|,-0.15913238289330806,0.014914000271162893,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.67,4382.0,years,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M5,A.1,M5,22,Garage,garage,A_structural,binary,binary,0.039,,6.67,,,,,high,Garage dummy,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M5 = M4 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",pct_premium,3.9752709807822084,0.6079617520593127,100*(exp(b - se^2/2) - 1),|b/t|,0.10025271530915254,0.01503039210032272,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.67,4382.0,binary,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M5,A.1,M5,22,Size of house,living_area,A_structural,log,m2,0.491,,52.36,,,,,high,ln(LivingArea); printed as 'Size of house' in Table A.1,ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M5 = M4 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,0.491,0.009377387318563789,b (log-log),|b/t|,0.6203700200046256,0.011848166921402324,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),52.36,4382.0,m2,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M5,A.1,M5,22,DistCBD,cbd_distance,D_location,log,minutes,-0.163,,-5.71,,,,,high,"ln(travel time by car to CBD, minutes)",ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M5 = M4 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,-0.163,0.028546409807355518,b (log-log),|b/t|,-0.0859389863936631,0.015050610576823659,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.71,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M5,A.1,M5,22,ACCESS,employment_access,D_location,log,index,0.109,,6.07,,,,,high,ln of gravity-based labour market accessibility measure (eq. 2),ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M5 = M4 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,0.109,0.017957166392092255,b (log-log),|b/t|,0.09131335756578327,0.015043386748893451,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.07,4382.0,index,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159,b8c37b8ea0a12e9cbed953c9880d16a2673b2159:TA1-M5,A.1,M5,22,MCT,employment_access,D_location,log,minutes,0.306,,1.47,,,,,high,ln of mean commuting time of residents of the zone (minutes),ln real selling price (1998 NOK),log,spatial_error,4392.0,,t,"M5 = M4 + ACCESS; spatial error model (k=3 nearest neighbours), z-values in parentheses; lambda 0.36-0.37",elasticity,0.306,0.20816326530612245,b (log-log),|b/t|,0.022201079525581962,0.015102775187470722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.47,4382.0,minutes,,2020.0,Norway,Europe,High income,2003.0,2007.0,single_family,transaction,journal,True,False,OLS,,2005.0,spatial,journal,True,True,False
b922ab81201881b47779769df9e76de174e13df7,b922ab81201881b47779769df9e76de174e13df7,b922ab81201881b47779769df9e76de174e13df7:TA1-MRA,A1,MRA (OLS),16,bedroom,bedrooms,A_structural,level,count,0.0084,,,0.0015,,,,high,; p-value printed in parentheses,"ln(price, BRL)",log,OLS,32688.0,0.9386,p,Training set,semi_elasticity,0.84,0.26459330283965976,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.0175592410858308,0.005531020945545029,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.174683527455075,32678.0,count,,2025.0,Brazil,South America,Upper middle income,2017.0,2021.0,condo_apartment,transaction_and_listing,journal,True,False,unknown,MARS;M5P;random_forest;quantile_random_forest;GBM;LightGBM;CatBoost;XGBoost;deep_learning,2019.0,ols,journal,True,True,False
bbc85c0376ef4c6974813a189124a40708684478,bbc85c0376ef4c6974813a189124a40708684478,bbc85c0376ef4c6974813a189124a40708684478:T5-c1,5,1,11,Area (b01),living_area,A_structural,level,m2,0.0088,0.0003,31.099,0.001,***,,,high,"Transferred (living) house area in m2, grand-mean centred; Level-2 house attribute","ln(sale price, NT$10,000)",log,other,7076.0,,se,"Non-randomly varying slope model; 7,076 repeat sales nested in 3,167 houses; robust SEs",semi_elasticity,0.88,0.03,100*b/1 (X per m2->m2),reported,0.3469792832424123,0.011157248890395583,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),31.099,7066.0,m2,,2023.0,Taiwan,Asia,High income,2012.0,2020.0,condo_apartment,transaction,journal,False,False,robust,,2016.0,other,journal,True,True,False
bbc85c0376ef4c6974813a189124a40708684478,bbc85c0376ef4c6974813a189124a40708684478,bbc85c0376ef4c6974813a189124a40708684478:T5-c1,5,1,11,Type1 (b02),dwelling_type,A_structural,dummy,binary,0.2395,0.0907,2.641,0.009,***,,,high,Luxury condominium (<=10 floors with elevator) =1; reference = condominium; grand-mean centred dummy,"ln(sale price, NT$10,000)",log,other,7076.0,,se,"Non-randomly varying slope model; 7,076 repeat sales nested in 3,167 houses; robust SEs",pct_premium,26.53980731381065,11.524466119556974,100*(exp(b - se^2/2) - 1),reported,0.031402725530403554,0.011890467826733643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.641,7066.0,binary,,2023.0,Taiwan,Asia,High income,2012.0,2020.0,condo_apartment,transaction,journal,False,False,robust,,2016.0,other,journal,True,True,False
bbc85c0376ef4c6974813a189124a40708684478,bbc85c0376ef4c6974813a189124a40708684478,bbc85c0376ef4c6974813a189124a40708684478:T5-c1,5,1,11,Type2 (b03),dwelling_type,A_structural,dummy,binary,0.418,0.0698,5.987,0.001,***,,,high,Apartment building (>=11 floors with elevator) =1; reference = condominium; grand-mean centred dummy,"ln(sale price, NT$10,000)",log,other,7076.0,,se,"Non-randomly varying slope model; 7,076 repeat sales nested in 3,167 houses; robust SEs",pct_premium,51.52250563882224,10.602066307327636,100*(exp(b - se^2/2) - 1),reported,0.07104339199475038,0.011866275596250272,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.987,7066.0,binary,,2023.0,Taiwan,Asia,High income,2012.0,2020.0,condo_apartment,transaction,journal,False,False,robust,,2016.0,other,journal,True,True,False
bbc85c0376ef4c6974813a189124a40708684478,bbc85c0376ef4c6974813a189124a40708684478,bbc85c0376ef4c6974813a189124a40708684478:T5-c1,5,1,11,Location (b04),cbd_distance,D_location,dummy,binary,0.5478,0.0571,9.591,0.001,***,,,high,"CBD (13 central districts) =1, suburbs =0; grand-mean centred; positive sign = CBD premium (not a distance)","ln(sale price, NT$10,000)",log,other,7076.0,,se,"Non-randomly varying slope model; 7,076 repeat sales nested in 3,167 houses; robust SEs",pct_premium,72.66270010939455,9.87512554049523,100*(exp(b - se^2/2) - 1),reported,0.11336224286450437,0.011819647884944676,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.591,7066.0,binary,,2023.0,Taiwan,Asia,High income,2012.0,2020.0,condo_apartment,transaction,journal,False,False,robust,,2016.0,other,journal,True,True,True
bbc85c0376ef4c6974813a189124a40708684478,bbc85c0376ef4c6974813a189124a40708684478,bbc85c0376ef4c6974813a189124a40708684478:T5-c1,5,1,11,Age (b30),age,A_structural,level,years,-0.0211,0.003,-7.09,0.001,***,,,high,"House age at time of sale, grand-mean centred; Level-1 variable","ln(sale price, NT$10,000)",log,other,7076.0,,se,"Non-randomly varying slope model; 7,076 repeat sales nested in 3,167 houses; robust SEs",semi_elasticity,-2.11,0.3,100*b/1 (per year),reported,-0.08404658745464616,0.011854243646635567,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.09,7066.0,years,,2023.0,Taiwan,Asia,High income,2012.0,2020.0,condo_apartment,transaction,journal,False,False,robust,,2016.0,other,journal,True,True,False
bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827:T4-c1,4,1,10,AREA,living_area,A_structural,level,ping (1 ping = 3.306 m2),0.001,0.001,6.831,,***,,,medium,registered house area; coefficient rounded to 3 decimals,ln housing transaction price,log,other,19157.0,,none,Full sample within 800 m of urban renewal projects; HLM random intercept; SE and t-ratio in separate columns,semi_elasticity,0.03024986387561256,0.03024986387561256,100*b/3.3058 (X per pyeong->m2),reported,0.049306634224393256,0.0072180697151798074,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.831,19147.0,pyeong,,2022.0,Taiwan,Asia,High income,2008.0,2016.0,mixed,transaction,journal,False,False,unknown,,2012.0,other,journal,True,True,False
bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827:T4-c1,4,1,10,AGE,age,A_structural,level,years,-0.012,0.001,-18.253,,***,,,high,house age; squared term AGES also included,ln housing transaction price,log,other,19157.0,,none,Full sample within 800 m of urban renewal projects; HLM random intercept; SE and t-ratio in separate columns,semi_elasticity,-1.2,0.1,100*b/1 (per year),reported,-0.13077895420039592,0.007164792319092529,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-18.253,19147.0,years,,2022.0,Taiwan,Asia,High income,2008.0,2016.0,mixed,transaction,journal,False,False,unknown,,2012.0,other,journal,True,True,False
bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827:T4-c1,4,1,10,ROOM,bedrooms,A_structural,level,count,-0.016,0.003,-5.233,,***,,,high,number of rooms (bedrooms),ln housing transaction price,log,other,19157.0,,none,Full sample within 800 m of urban renewal projects; HLM random intercept; SE and t-ratio in separate columns,semi_elasticity,-1.6,0.3,100*b/1 (per unit count),reported,-0.03779114245418392,0.00722169739235313,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.233,19147.0,count,,2022.0,Taiwan,Asia,High income,2008.0,2016.0,mixed,transaction,journal,False,False,unknown,,2012.0,other,journal,True,True,False
bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827:T4-c1,4,1,10,BATH,bathrooms,A_structural,level,count,0.049,0.005,10.971,,***,,,high,,ln housing transaction price,log,other,19157.0,,none,Full sample within 800 m of urban renewal projects; HLM random intercept; SE and t-ratio in separate columns,semi_elasticity,4.9,0.5,100*b/1 (per unit count),reported,0.07903784254571243,0.007204251439769612,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.971,19147.0,count,,2022.0,Taiwan,Asia,High income,2008.0,2016.0,mixed,transaction,journal,False,False,unknown,,2012.0,other,journal,True,True,False
bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827:T4-c1,4,1,10,FLOOR1,floor_level,A_structural,dummy,binary,0.167,0.008,20.975,,***,,,high,dummy = 1 if house is on the first (ground) floor,ln housing transaction price,log,other,19157.0,,none,Full sample within 800 m of urban renewal projects; HLM random intercept; SE and t-ratio in separate columns,pct_premium,18.171644977692345,0.9454034122466892,100*(exp(b - se^2/2) - 1),reported,0.14987132787731647,0.007145236132410797,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.975,19147.0,binary,,2022.0,Taiwan,Asia,High income,2008.0,2016.0,mixed,transaction,journal,False,False,unknown,,2012.0,other,journal,True,True,False
bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827:T4-c1,4,1,10,BUILDING,dwelling_type,A_structural,dummy,binary,0.197,0.007,29.409,,***,,,high,high-rise residential building vs apartment building (reference),ln housing transaction price,log,other,19157.0,,none,Full sample within 800 m of urban renewal projects; HLM random intercept; SE and t-ratio in separate columns,pct_premium,21.77142063423836,0.8524208284941358,100*(exp(b - se^2/2) - 1),reported,0.20789125052232202,0.007068967000657011,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.409,19147.0,binary,,2022.0,Taiwan,Asia,High income,2008.0,2016.0,mixed,transaction,journal,False,False,unknown,,2012.0,other,journal,True,True,False
bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827:T4-c1,4,1,10,HUAXIA,dwelling_type,A_structural,dummy,binary,0.174,0.006,28.168,,***,,,high,low-rise residential building (huaxia) vs apartment building (reference),ln housing transaction price,log,other,19157.0,,none,Full sample within 800 m of urban renewal projects; HLM random intercept; SE and t-ratio in separate columns,pct_premium,19.003414501296568,0.7140333394922176,100*(exp(b - se^2/2) - 1),reported,0.19947509686249643,0.007081620876970195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.168,19147.0,binary,,2022.0,Taiwan,Asia,High income,2008.0,2016.0,mixed,transaction,journal,False,False,unknown,,2012.0,other,journal,True,True,False
bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827,bd42cea5779904b39c488f5e59235573696a2827:T4-c1,4,1,10,PARKING,parking,A_structural,binary,binary,-0.065,0.006,-10.403,,***,,,high,availability of parking lot(s),ln housing transaction price,log,other,19157.0,,none,Full sample within 800 m of urban renewal projects; HLM random intercept; SE and t-ratio in separate columns,pct_premium,-6.294940368513336,0.5622404780264421,100*(exp(b - se^2/2) - 1),reported,-0.07496945070489841,0.007206522224829222,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.403,19147.0,binary,,2022.0,Taiwan,Asia,High income,2008.0,2016.0,mixed,transaction,journal,False,False,unknown,,2012.0,other,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1A,2,1A,54,LogBLDAGE,age,A_structural,log,years,-0.163,,-3.454,,**,,,high,"building age, log","LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,elasticity,-0.163,0.047191661841343366,b (log-log),|b/t|,-0.19310555692836473,0.05590780455366669,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.454,308.0,years,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1A,2,1A,54,LogBFLOAREA,living_area,A_structural,log,m2,2.381,,10.627,,***,,,high,"building floor area, log","LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,elasticity,2.381,0.22405194316363974,b (log-log),|b/t|,0.5179694274130044,0.048740889000941416,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.627,308.0,m2,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1A,2,1A,54,NBEDROOM,bedrooms,A_structural,level,count,0.025,,0.576,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,semi_elasticity,2.5,4.340277777777779,100*b/1 (per unit count),|b/t|,0.032802983174141986,0.05694962356621873,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.576,308.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1A,2,1A,54,NBATROOM,bathrooms,A_structural,level,count,-0.114,,-0.953,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,semi_elasticity,-11.4,11.962224554039876,100*b/1 (per unit count),|b/t|,-0.054222330009594304,0.05689646380859844,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.953,308.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,True
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1A,2,1A,54,NFLOORS,storeys,A_structural,level,count,0.031,,3.966,,***,,,high,number of floors,"LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,semi_elasticity,3.1,0.7816439737771054,100*b/1 (per unit count),|b/t|,0.2204254836442602,0.05557879063143222,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.966,308.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1A,2,1A,54,GARAGE_YES,garage,A_structural,binary,binary,0.152,,3.468,,**,,,high,,"LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,pct_premium,16.304259315558145,5.102432408814333,100*(exp(b - se^2/2) - 1),|b/t|,0.19385890812964915,0.05589933913773043,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.468,308.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1A,2,1A,54,BLDCOND_Excellent,condition,A_structural,binary,binary,0.028,,0.892,,,,,high,building condition excellent dummy,"LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,pct_premium,2.788914922661556,3.2281478883183747,100*(exp(b - se^2/2) - 1),|b/t|,0.05076089345661183,0.05690683122938547,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.892,308.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1A,2,1A,54,LSCAPQUA_Excellent,landscaping,C_exterior,binary,binary,0.028,,0.817,,,,,high,landscape quality excellent dummy,"LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,pct_premium,2.7791910041724766,3.5244894937331583,100*(exp(b - se^2/2) - 1),|b/t|,0.0465025332590807,0.0569186453599519,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.817,308.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1A,2,1A,54,LogDISCOAST,water_proximity,E_environment,log,m,0.001,,0.009,,,,,high,"distance to coastline, log","LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,elasticity,0.001,0.11111111111111112,b (log-log),|b/t|,0.0005128225266355429,0.056980280737282556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.009,308.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1A,2,1A,54,LogDISTWORK,employment_access,D_location,log,m,-0.029,,-0.932,,,,,high,"distance to workplace, log","LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,elasticity,-0.029,0.03111587982832618,b (log-log),|b/t|,-0.05303090219731193,0.05690010965376817,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.932,308.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1A,2,1A,54,LogDISBSTOP,transit_distance,D_location,log,m,-0.437,,-1.22,,,,,high,"distance to bus stop, log","LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,elasticity,-0.437,0.3581967213114754,b (log-log),|b/t|,-0.06934859118004497,0.05684310752462701,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.22,308.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1A,2,1A,54,LogDISTSCH,school_distance,D_location,log,m,-0.002,,-0.04,,,,,high,"distance to school, log","LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,elasticity,-0.002,0.05,b (log-log),|b/t|,-0.0022792056091858783,0.05698014022964695,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.04,308.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1B,2,1B,54,LogBLDAGE,age,A_structural,log,years,-0.098,,-1.3,,,,,high,"building age, log","LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,elasticity,-0.098,0.07538461538461538,b (log-log),|b/t|,-0.12412516364311554,0.09548089511008888,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3,108.0,years,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1B,2,1B,54,LogBFLOAREA,living_area,A_structural,log,m2,1.856,,6.04,,***,,,high,"building floor area, log","LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,elasticity,1.856,0.3072847682119205,b (log-log),|b/t|,0.5024937535082539,0.08319433005103541,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.04,108.0,m2,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1B,2,1B,54,NBEDROOM,bedrooms,A_structural,level,count,0.071,,1.083,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,semi_elasticity,7.1,6.555863342566943,100*b/1 (per unit count),|b/t|,0.10365041734664666,0.095706756552767,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.083,108.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1B,2,1B,54,NBATROOM,bathrooms,A_structural,level,count,0.105,,0.624,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,semi_elasticity,10.5,16.826923076923077,100*b/1 (per unit count),|b/t|,0.05993647971147509,0.09605205081967161,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.624,108.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1B,2,1B,54,NFLOORS,storeys,A_structural,level,count,0.01,,0.803,,,,,high,number of floors,"LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,semi_elasticity,1.0,1.2453300124533,100*b/1 (per unit count),|b/t|,0.07703907416269351,0.09593907118641783,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.803,108.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1B,2,1B,54,GARAGE_YES,garage,A_structural,binary,binary,0.059,,0.851,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,pct_premium,5.82289000613716,7.354375934626249,100*(exp(b - se^2/2) - 1),|b/t|,0.08161433526052428,0.09590403673387107,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.851,108.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1B,2,1B,54,BLDCOND_Excellent,condition,A_structural,binary,binary,-0.007,,-0.162,,,,,high,building condition excellent dummy,"LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,pct_premium,-0.7902159193335478,4.290846358353485,100*(exp(b - se^2/2) - 1),|b/t|,-0.015586563615672991,0.09621335565230241,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.162,108.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1B,2,1B,54,LSCAPQUA_Excellent,landscaping,C_exterior,binary,binary,0.039,,0.743,,,,,high,landscape quality excellent dummy,"LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,pct_premium,3.833908709060241,5.457745472726265,100*(exp(b - se^2/2) - 1),|b/t|,0.07131317968092271,0.09598005340635629,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.743,108.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1B,2,1B,54,LogDISCOAST,water_proximity,E_environment,log,m,0.077,,0.359,,,,,high,"distance to coastline, log","LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,elasticity,0.077,0.21448467966573817,b (log-log),|b/t|,0.03452419765067697,0.09616768147820884,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.359,108.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1B,2,1B,54,LogDISTWORK,employment_access,D_location,log,m,-0.048,,-0.852,,,,,high,"distance to workplace, log","LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,elasticity,-0.048,0.056338028169014086,b (log-log),|b/t|,-0.08170959937118119,0.09590328564692628,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.852,108.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1B,2,1B,54,LogDISBSTOP,transit_distance,D_location,log,m,1.074,,0.952,,,,,high,"distance to bus stop, log","LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,elasticity,1.074,1.128151260504202,b (log-log),|b/t|,0.09122427881009469,0.09582382227951122,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.952,108.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,True
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1B,2,1B,54,LogDISTSCH,school_distance,D_location,log,m,-0.073,,-0.653,,,,,high,"distance to school, log","LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,elasticity,-0.073,0.111791730474732,b (log-log),|b/t|,-0.06271127693434075,0.0960356461475356,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.653,108.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1C,2,1C,54,LogBLDAGE,age,A_structural,log,years,-0.235,,-3.775,,***,,,high,"building age, log","LogRENT (annual rent, Naira)",log,OLS,200.0,0.637,t,251-500 m from coastline,elasticity,-0.235,0.06225165562913907,b (log-log),|b/t|,-0.26414066014268034,0.06997103579938552,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.775,190.0,years,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1C,2,1C,54,LogBFLOAREA,living_area,A_structural,log,m2,2.672,,8.368,,***,,,high,"building floor area, log","LogRENT (annual rent, Naira)",log,OLS,200.0,0.637,t,251-500 m from coastline,elasticity,2.672,0.3193116634799235,b (log-log),|b/t|,0.51893795388882,0.06201457383948614,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.368,190.0,m2,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,True
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1C,2,1C,54,NBEDROOM,bedrooms,A_structural,level,count,0.029,,0.489,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,200.0,0.637,t,251-500 m from coastline,semi_elasticity,2.9000000000000004,5.930470347648263,100*b/1 (per unit count),|b/t|,0.03545348597947628,0.0725020163179474,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.489,190.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1C,2,1C,54,NBATROOM,bathrooms,A_structural,level,count,-0.252,,-1.471,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,200.0,0.637,t,251-500 m from coastline,semi_elasticity,-25.2,17.131203263086334,100*b/1 (per unit count),|b/t|,-0.10611501438625313,0.07213801113953305,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.471,190.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,True
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1C,2,1C,54,NFLOORS,storeys,A_structural,level,count,0.055,,4.682,,***,,,high,number of floors,"LogRENT (annual rent, Naira)",log,OLS,200.0,0.637,t,251-500 m from coastline,semi_elasticity,5.5,1.1747116616830413,100*b/1 (per unit count),|b/t|,0.3216209163629306,0.0686930620168583,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.682,190.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1C,2,1C,54,GARAGE_YES,garage,A_structural,binary,binary,0.183,,3.124,,**,,,high,,"LogRENT (annual rent, Naira)",log,OLS,200.0,0.637,t,251-500 m from coastline,pct_premium,19.875589557485608,7.034220124161076,100*(exp(b - se^2/2) - 1),|b/t|,0.22103316316951543,0.07075325325528663,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.124,190.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1C,2,1C,54,BLDCOND_Excellent,condition,A_structural,binary,binary,0.02,,0.46,,,,,high,building condition excellent dummy,"LogRENT (annual rent, Naira)",log,OLS,200.0,0.637,t,251-500 m from coastline,pct_premium,1.9237522110731486,4.435658000116329,100*(exp(b - se^2/2) - 1),|b/t|,0.033353340129035396,0.07250726115007694,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.46,190.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1C,2,1C,54,LSCAPQUA_Excellent,landscaping,C_exterior,binary,binary,-0.031,,-0.679,,,,,high,landscape quality excellent dummy,"LogRENT (annual rent, Naira)",log,OLS,200.0,0.637,t,251-500 m from coastline,pct_premium,-3.15342944846424,4.426177137755052,100*(exp(b - se^2/2) - 1),|b/t|,-0.04920018065425251,0.07245976532290502,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.679,190.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,True
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1C,2,1C,54,LogDISCOAST,water_proximity,E_environment,log,m,0.233,,0.763,,,,,high,"distance to coastline, log","LogRENT (annual rent, Naira)",log,OLS,200.0,0.637,t,251-500 m from coastline,elasticity,0.233,0.3053735255570118,b (log-log),|b/t|,0.05526922887767511,0.07243673509524916,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.763,190.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1C,2,1C,54,LogDISTWORK,employment_access,D_location,log,m,-0.065,,-1.51,,,,,high,"distance to workplace, log","LogRENT (annual rent, Naira)",log,OLS,200.0,0.637,t,251-500 m from coastline,elasticity,-0.065,0.04304635761589404,b (log-log),|b/t|,-0.108895460959624,0.07211619931100928,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.51,190.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1C,2,1C,54,LogDISBSTOP,transit_distance,D_location,log,m,-0.345,,-0.718,,,,,high,"distance to bus stop, log","LogRENT (annual rent, Naira)",log,OLS,200.0,0.637,t,251-500 m from coastline,elasticity,-0.345,0.48050139275766013,b (log-log),|b/t|,-0.05201867184219125,0.0724494036799321,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.718,190.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T2-1C,2,1C,54,LogDISTSCH,school_distance,D_location,log,m,0.023,,0.301,,,,,high,"distance to school, log","LogRENT (annual rent, Naira)",log,OLS,200.0,0.637,t,251-500 m from coastline,elasticity,0.023,0.07641196013289037,b (log-log),|b/t|,0.021831630570889247,0.07253033412255565,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.301,190.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2A,3,2A,55,LogBLDAGE,age,A_structural,log,years,-0.162,,-3.44,,**,,,high,"building age, log","LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,elasticity,-0.162,0.04709302325581396,b (log-log),|b/t|,-0.19235186405281957,0.05591623955023825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.44,308.0,years,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2A,3,2A,55,LogBFLOAREA,living_area,A_structural,log,m2,2.385,,10.622,,***,,,high,"building floor area, log","LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,elasticity,2.385,0.2245339860666541,b (log-log),|b/t|,0.5177910732345553,0.04874704135139853,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.622,308.0,m2,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,True
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2A,3,2A,55,NBEDROOM,bedrooms,A_structural,level,count,0.025,,0.569,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,semi_elasticity,2.5,4.393673110720563,100*b/1 (per unit count),|b/t|,0.032404756988303286,0.05695036377557696,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.569,308.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2A,3,2A,55,NBATROOM,bathrooms,A_structural,level,count,-0.117,,-0.986,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,semi_elasticity,-11.700000000000001,11.866125760649087,100*b/1 (per unit count),|b/t|,-0.05609410397212255,0.056890571979840314,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.986,308.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,True
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2A,3,2A,55,NFLOORS,storeys,A_structural,level,count,0.032,,3.975,,***,,,high,number of floors,"LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,semi_elasticity,3.2,0.8050314465408804,100*b/1 (per unit count),|b/t|,0.22090131014844505,0.055572656641118254,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.975,308.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2A,3,2A,55,GARAGE_YES,garage,A_structural,binary,binary,0.152,,3.484,,**,,,high,,"LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,pct_premium,16.305283009155836,5.07899988340072,100*(exp(b - se^2/2) - 1),|b/t|,0.19471946111113103,0.05588962718459559,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.484,308.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2A,3,2A,55,BLDCOND_Excellent,condition,A_structural,binary,binary,0.028,,0.891,,,,,high,building condition excellent dummy,"LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,pct_premium,2.7888011865609297,3.231770949921426,100*(exp(b - se^2/2) - 1),|b/t|,0.050704133009561704,0.056906995521393604,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.891,308.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2A,3,2A,55,LSCAPQUA_Excellent,landscaping,C_exterior,binary,binary,0.028,,0.841,,,,,high,landscape quality excellent dummy,"LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,pct_premium,2.782586929248554,3.4239095319619386,100*(exp(b - se^2/2) - 1),|b/t|,0.04786549554683916,0.056914976869012084,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.841,308.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2A,3,2A,55,LogDISTWORK,employment_access,D_location,log,m,-0.028,,-0.898,,,,,high,"distance to workplace, log","LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,elasticity,-0.028,0.031180400890868598,b (log-log),|b/t|,-0.05110144579039009,0.05690584163740545,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.898,308.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2A,3,2A,55,LogDISBSTOP,transit_distance,D_location,log,m,-0.494,,-1.545,,,,,high,"distance to bus stop, log","LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,elasticity,-0.494,0.3197411003236246,b (log-log),|b/t|,-0.0876953780412515,0.056760762486246924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.545,308.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2A,3,2A,55,LogDISTSCH,school_distance,D_location,log,m,-0.004,,-0.062,,,,,high,"distance to school, log","LogRENT (annual rent, Naira)",log,OLS,318.0,0.571,t,0-500 m from coastline,elasticity,-0.004,0.06451612903225806,b (log-log),|b/t|,-0.0035327558250036134,0.0569799326613486,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.062,308.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2B,3,2B,55,LogBLDAGE,age,A_structural,log,years,-0.101,,-1.318,,,,,high,"building age, log","LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,elasticity,-0.101,0.07663125948406677,b (log-log),|b/t|,-0.12581679653480743,0.09546039190804811,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.318,108.0,years,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2B,3,2B,55,LogBFLOAREA,living_area,A_structural,log,m2,1.863,,6.147,,***,,,high,"building floor area, log","LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,elasticity,1.863,0.30307467057101023,b (log-log),|b/t|,0.5091032686865636,0.08282141999130689,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.147,108.0,m2,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2B,3,2B,55,NBEDROOM,bedrooms,A_structural,level,count,0.073,,1.116,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,semi_elasticity,7.3,6.541218637992831,100*b/1 (per unit count),|b/t|,0.1067732602220089,0.09567496435663879,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.116,108.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2B,3,2B,55,NBATROOM,bathrooms,A_structural,level,count,0.103,,0.612,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,semi_elasticity,10.299999999999999,16.83006535947712,100*b/1 (per unit count),|b/t|,0.05878787750522922,0.09605862337455755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.612,108.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2B,3,2B,55,NFLOORS,storeys,A_structural,level,count,0.009,,0.75,,,,,high,number of floors,"LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,semi_elasticity,0.8999999999999999,1.2,100*b/1 (per unit count),|b/t|,0.07198157507486945,0.09597543343315927,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.75,108.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2B,3,2B,55,GARAGE_YES,garage,A_structural,binary,binary,0.058,,0.833,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,pct_premium,5.7149337467431005,7.378567797262508,100*(exp(b - se^2/2) - 1),|b/t|,0.07989920121147924,0.09591740841714194,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.833,108.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2B,3,2B,55,BLDCOND_Excellent,condition,A_structural,binary,binary,-0.006,,-0.14,,,,,high,building condition excellent dummy,"LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,pct_premium,-0.689449053814073,4.260076988802579,100*(exp(b - se^2/2) - 1),|b/t|,-0.013470284032991461,0.09621631452136757,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.14,108.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2B,3,2B,55,LSCAPQUA_Excellent,landscaping,C_exterior,binary,binary,0.044,,0.859,,,,,high,landscape quality excellent dummy,"LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,pct_premium,4.361237828533282,5.3526453568209,100*(exp(b - se^2/2) - 1),|b/t|,0.08237638529738632,0.09589800383863366,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.859,108.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2B,3,2B,55,LogDISTWORK,employment_access,D_location,log,m,-0.051,,-0.91,,,,,high,"distance to workplace, log","LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,elasticity,-0.051,0.05604395604395604,b (log-log),|b/t|,-0.08723100354319238,0.09585824565185977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.91,108.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2B,3,2B,55,LogDISBSTOP,transit_distance,D_location,log,m,1.004,,1.049,,,,,high,"distance to bus stop, log","LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,elasticity,1.004,0.9571020019065778,b (log-log),|b/t|,0.10042973454491917,0.0957385458006856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.049,108.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2B,3,2B,55,LogDISTSCH,school_distance,D_location,log,m,-0.079,,-0.751,,,,,high,"distance to school, log","LogRENT (annual rent, Naira)",log,OLS,118.0,0.553,t,0-250 m from coastline,elasticity,-0.079,0.1051930758988016,b (log-log),|b/t|,-0.07207705223642487,0.09597476995529278,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.751,108.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,True
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2C,3,2C,55,LogBLDAGE,age,A_structural,log,years,-0.237,,-3.78,,***,,,high,"building age, log","LogRENT (annual rent, Naira)",log,OLS,200.0,0.635,t,251-500 m from coastline,elasticity,-0.237,0.0626984126984127,b (log-log),|b/t|,-0.26446606069986733,0.06996456632271623,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.78,190.0,years,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2C,3,2C,55,LogBFLOAREA,living_area,A_structural,log,m2,2.712,,8.395,,***,,,high,"building floor area, log","LogRENT (annual rent, Naira)",log,OLS,200.0,0.635,t,251-500 m from coastline,elasticity,2.712,0.3230494341870161,b (log-log),|b/t|,0.5201598448630973,0.0619606724077543,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.395,190.0,m2,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,True
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2C,3,2C,55,NBEDROOM,bedrooms,A_structural,level,count,0.017,,0.294,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,200.0,0.635,t,251-500 m from coastline,semi_elasticity,1.7000000000000002,5.782312925170069,100*b/1 (per unit count),|b/t|,0.021324151845840966,0.07253112872735024,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.294,190.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2C,3,2C,55,NBATROOM,bathrooms,A_structural,level,count,-0.293,,-1.696,,,,,high,,"LogRENT (annual rent, Naira)",log,OLS,200.0,0.635,t,251-500 m from coastline,semi_elasticity,-29.299999999999997,17.275943396226413,100*b/1 (per unit count),|b/t|,-0.1221198561898335,0.07200463218740183,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.696,190.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,True
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2C,3,2C,55,NFLOORS,storeys,A_structural,level,count,0.053,,4.602,,***,,,high,number of floors,"LogRENT (annual rent, Naira)",log,OLS,200.0,0.635,t,251-500 m from coastline,semi_elasticity,5.3,1.1516731855714906,100*b/1 (per unit count),|b/t|,0.31668089426888,0.06881375364382443,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.602,190.0,count,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2C,3,2C,55,GARAGE_YES,garage,A_structural,binary,binary,0.198,,3.478,,**,,,high,,"LogRENT (annual rent, Naira)",log,OLS,200.0,0.635,t,251-500 m from coastline,pct_premium,21.69887003542208,6.939463886621198,100*(exp(b - se^2/2) - 1),|b/t|,0.2446528046137066,0.07034295704821926,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.478,190.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2C,3,2C,55,BLDCOND_Excellent,condition,A_structural,binary,binary,0.022,,0.517,,,,,high,building condition excellent dummy,"LogRENT (annual rent, Naira)",log,OLS,200.0,0.635,t,251-500 m from coastline,pct_premium,2.1318677036345823,4.349973550938035,100*(exp(b - se^2/2) - 1),|b/t|,0.03748076772005881,0.07249664936181588,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.517,190.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2C,3,2C,55,LSCAPQUA_Excellent,landscaping,C_exterior,binary,binary,-0.028,,-0.597,,,,,high,landscape quality excellent dummy,"LogRENT (annual rent, Naira)",log,OLS,200.0,0.635,t,251-500 m from coastline,pct_premium,-2.868053633073875,4.560615455684241,100*(exp(b - se^2/2) - 1),|b/t|,-0.043270367071651133,0.07247967683693658,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.597,190.0,binary,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2C,3,2C,55,LogDISTWORK,employment_access,D_location,log,m,-0.052,,-1.241,,,,,high,"distance to workplace, log","LogRENT (annual rent, Naira)",log,OLS,200.0,0.635,t,251-500 m from coastline,elasticity,-0.052,0.0419016921837228,b (log-log),|b/t|,-0.0896689218816425,0.07225537621405519,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.241,190.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2C,3,2C,55,LogDISBSTOP,transit_distance,D_location,log,m,-0.687,,-1.525,,,,,high,"distance to bus stop, log","LogRENT (annual rent, Naira)",log,OLS,200.0,0.635,t,251-500 m from coastline,elasticity,-0.687,0.4504918032786886,b (log-log),|b/t|,-0.10996418694095503,0.07210766356783938,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.525,190.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd,c0719dfc2e99247adf55e3df25480bbce55099dd:T3-2C,3,2C,55,LogDISTSCH,school_distance,D_location,log,m,0.015,,0.195,,,,,high,"distance to school, log","LogRENT (annual rent, Naira)",log,OLS,200.0,0.635,t,251-500 m from coastline,elasticity,0.015,0.07692307692307691,b (log-log),|b/t|,0.014145371480193528,0.07254036656509501,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.195,190.0,m,,2022.0,Nigeria,Africa,Lower middle income,,,rental,rent,journal,False,False,unknown,,2019.0,ols,journal,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-total,2.4,Total Effects,35,Coal Dummy_0.75~1.00,hazard_site,E_environment,dummy,binary,-0.11,,,0.02,**,,,high,1 if located 0.75-1.00 mile from an active coal mine,log sale price of house,log,spatial_lag,683.0,0.5,p,Same SAR estimation as T2.4-direct; total effects = direct + indirect (spatial spillover) effects,pct_premium,-10.516676527520364,4.235899367511711,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.08931572570675653,0.038393108229173,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3263478740408408,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-direct,2.4,Direct Effects,35,Coal Dummy_1.00~1.25,hazard_site,E_environment,dummy,binary,-0.093,,,0.01,**,,,high,1 if located 1.00-1.25 miles from an active coal mine,log sale price of house,log,spatial_lag,683.0,0.5,p,All 683 single-family sales 2004-2005; direct (own-house) effects of the Bayesian heteroskedastic SAR model (2 nearest neighbours),pct_premium,-8.940020487372868,3.2898529188555874,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.09880507326491056,0.038358548498838754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-total,2.4,Total Effects,35,Coal Dummy_1.00~1.25,hazard_site,E_environment,dummy,binary,-0.099,,,0.01,**,,,high,1 if located 1.00-1.25 miles from an active coal mine,log sale price of house,log,spatial_lag,683.0,0.5,p,Same SAR estimation as T2.4-direct; total effects = direct + indirect (spatial spillover) effects,pct_premium,-9.49260218226674,3.481151797240162,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.09880507326491056,0.038358548498838754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.575829303548901,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-direct,2.4,Direct Effects,35,Coal Dummy_1.25~1.50,hazard_site,E_environment,dummy,binary,-0.02,,,0.57,,,,high,1 if located 1.25-1.50 miles from an active coal mine,log sale price of house,log,spatial_lag,683.0,0.5,p,All 683 single-family sales 2004-2005; direct (own-house) effects of the Bayesian heteroskedastic SAR model (2 nearest neighbours),pct_premium,-2.0408669797326695,3.451090882333435,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.021891528575072924,0.03853792946429167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5680514983389829,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-total,2.4,Total Effects,35,Coal Dummy_1.25~1.50,hazard_site,E_environment,dummy,binary,-0.021,,,0.57,,,,high,1 if located 1.25-1.50 miles from an active coal mine,log sale price of house,log,spatial_lag,683.0,0.5,p,Same SAR estimation as T2.4-direct; total effects = direct + indirect (spatial spillover) effects,pct_premium,-2.1449940695919434,3.6200235922425805,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.021891528575072924,0.03853792946429167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5680514983389829,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-direct,2.4,Direct Effects,35,Age,age,A_structural,level,hundred_years,-0.105,,,0.16,,,,high,Age of house at sale in hundreds of years (Table 2.2); quadratic term also included,log sale price of house,log,spatial_lag,683.0,0.5,p,All 683 single-family sales 2004-2005; direct (own-house) effects of the Bayesian heteroskedastic SAR model (2 nearest neighbours),semi_elasticity,-0.105,0.07472928992802427,100*b/100 (hundred years->year),|b/z(p)| (two-sided normal),-0.05408226210850041,0.038490752810185984,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4050715603096329,673.0,hundred_years,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-total,2.4,Total Effects,35,Age,age,A_structural,level,hundred_years,-0.11,,,0.17,,,,high,Age of house at sale in hundreds of years (Table 2.2); quadratic term also included,log sale price of house,log,spatial_lag,683.0,0.5,p,Same SAR estimation as T2.4-direct; total effects = direct + indirect (spatial spillover) effects,semi_elasticity,-0.11,0.08016301899079056,100*b/100 (hundred years->year),|b/z(p)| (two-sided normal),-0.052820729447756835,0.038493355798435824,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3722038089987258,673.0,hundred_years,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-direct,2.4,Direct Effects,35,Fair Condition,condition,A_structural,dummy,binary,-0.026,,,0.75,,,,high,Assessor condition = fair; omitted category = poor condition,log sale price of house,log,spatial_lag,683.0,0.5,p,All 683 single-family sales 2004-2005; direct (own-house) effects of the Bayesian heteroskedastic SAR model (2 nearest neighbours),pct_premium,-2.8903109145449135,7.950277082733494,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.012281718451325313,0.0385442598758716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.31863936396437514,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-total,2.4,Total Effects,35,Fair Condition,condition,A_structural,dummy,binary,-0.027,,,0.75,,,,high,Assessor condition = fair; omitted category = poor condition,log sale price of house,log,spatial_lag,683.0,0.5,p,Same SAR estimation as T2.4-direct; total effects = direct + indirect (spatial spillover) effects,pct_premium,-3.0126894365061885,8.247805040213224,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.012281718451325313,0.0385442598758716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.31863936396437514,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-direct,2.4,Direct Effects,35,Bedrooms,bedrooms,A_structural,level,count,0.01,,,0.3,,,,high,Number of bedrooms,log sale price of house,log,spatial_lag,683.0,0.5,p,All 683 single-family sales 2004-2005; direct (own-house) effects of the Bayesian heteroskedastic SAR model (2 nearest neighbours),semi_elasticity,1.0,0.964847341022481,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.03991972538786661,0.03851644089483072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0364333894937894,673.0,count,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-total,2.4,Total Effects,35,Bedrooms,bedrooms,A_structural,level,count,0.01,,,0.3,,,,high,Number of bedrooms,log sale price of house,log,spatial_lag,683.0,0.5,p,Same SAR estimation as T2.4-direct; total effects = direct + indirect (spatial spillover) effects,semi_elasticity,1.0,0.964847341022481,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.03991972538786661,0.03851644089483072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0364333894937894,673.0,count,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-direct,2.4,Direct Effects,35,Bathrooms,bathrooms,A_structural,level,count,0.029,,,0.01,**,,,high,Number of bathrooms,log sale price of house,log,spatial_lag,683.0,0.5,p,All 683 single-family sales 2004-2005; direct (own-house) effects of the Bayesian heteroskedastic SAR model (2 nearest neighbours),semi_elasticity,2.9000000000000004,1.1258510010754463,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.09880507326491056,0.038358548498838754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,673.0,count,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-total,2.4,Total Effects,35,Bathrooms,bathrooms,A_structural,level,count,0.03,,,0.01,**,,,high,Number of bathrooms,log sale price of house,log,spatial_lag,683.0,0.5,p,Same SAR estimation as T2.4-direct; total effects = direct + indirect (spatial spillover) effects,semi_elasticity,3.0,1.1646734493883928,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.09880507326491056,0.038358548498838754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,673.0,count,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-direct,2.4,Direct Effects,35,Heating,heating,A_structural,dummy,binary,0.044,,,0.33,,,,high,1 if presence of a heating system,log sale price of house,log,spatial_lag,683.0,0.5,p,All 683 single-family sales 2004-2005; direct (own-house) effects of the Bayesian heteroskedastic SAR model (2 nearest neighbours),pct_premium,4.391687966720381,4.720107648388637,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.03752288709348223,0.03852002109523141,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.974113877059309,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-total,2.4,Total Effects,35,Heating,heating,A_structural,dummy,binary,0.046,,,0.33,,,,high,1 if presence of a heating system,log sale price of house,log,spatial_lag,683.0,0.5,p,Same SAR estimation as T2.4-direct; total effects = direct + indirect (spatial spillover) effects,pct_premium,4.590759687603696,4.944537187933578,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.03752288709348223,0.03852002109523141,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.974113877059309,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-direct,2.4,Direct Effects,35,Fireplace,fireplace,B_interior,dummy,binary,0.028,,,0.06,*,,,high,1 if presence of a fireplace,log sale price of house,log,spatial_lag,683.0,0.5,p,All 683 single-family sales 2004-2005; direct (own-house) effects of the Bayesian heteroskedastic SAR model (2 nearest neighbours),pct_premium,2.8281727693970193,1.5310068600299198,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.07230948028286521,0.03844626011566611,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.880793608151251,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-total,2.4,Total Effects,35,Fireplace,fireplace,B_interior,dummy,binary,0.028,,,0.06,*,,,high,1 if presence of a fireplace,log sale price of house,log,spatial_lag,683.0,0.5,p,Same SAR estimation as T2.4-direct; total effects = direct + indirect (spatial spillover) effects,pct_premium,2.8281727693970193,1.5310068600299198,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.07230948028286521,0.03844626011566611,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.880793608151251,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-direct,2.4,Direct Effects,35,Full Basement,basement,A_structural,dummy,binary,-0.01,,,0.62,,,,high,1 if full basement; omitted category = crawl space,log sale price of house,log,spatial_lag,683.0,0.5,p,All 683 single-family sales 2004-2005; direct (own-house) effects of the Bayesian heteroskedastic SAR model (2 nearest neighbours),pct_premium,-1.0151483810479922,1.9966706467897628,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.01911013581660229,0.03854012792132097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.49585034734745326,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-total,2.4,Total Effects,35,Full Basement,basement,A_structural,dummy,binary,-0.011,,,0.62,,,,high,1 if full basement; omitted category = crawl space,log sale price of house,log,spatial_lag,683.0,0.5,p,Same SAR estimation as T2.4-direct; total effects = direct + indirect (spatial spillover) effects,pct_premium,-1.118306680330572,2.194142471560161,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.01911013581660229,0.03854012792132097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.49585034734745326,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-direct,2.4,Direct Effects,35,Part Basement,basement,A_structural,dummy,binary,-0.004,,,0.86,,,,high,1 if part basement; omitted category = crawl space,log sale price of house,log,spatial_lag,683.0,0.5,p,All 683 single-family sales 2004-2005; direct (own-house) effects of the Bayesian heteroskedastic SAR model (2 nearest neighbours),pct_premium,-0.42481209450055957,2.258852345141356,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.006798567301808662,0.03854627637928514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.17637416478086135,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-total,2.4,Total Effects,35,Part Basement,basement,A_structural,dummy,binary,-0.004,,,0.86,,,,high,1 if part basement; omitted category = crawl space,log sale price of house,log,spatial_lag,683.0,0.5,p,Same SAR estimation as T2.4-direct; total effects = direct + indirect (spatial spillover) effects,pct_premium,-0.42481209450055957,2.258852345141356,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.006798567301808662,0.03854627637928514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.17637416478086135,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-direct,2.4,Direct Effects,35,No Basement,basement,A_structural,dummy,binary,0.049,,,0.06,*,,,high,1 if no basement; omitted category = crawl space (sign reversed relative to basement presence),log sale price of house,log,spatial_lag,683.0,0.5,p,All 683 single-family sales 2004-2005; direct (own-house) effects of the Bayesian heteroskedastic SAR model (2 nearest neighbours),pct_premium,4.986399265098074,2.736121441674049,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.07230948028286521,0.03844626011566611,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.880793608151251,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964,c0c750e0ff9e1fcc59888eee28b0b7208f559964:T2.4-total,2.4,Total Effects,35,No Basement,basement,A_structural,dummy,binary,0.052,,,0.06,*,,,high,1 if no basement; omitted category = crawl space (sign reversed relative to basement presence),log sale price of house,log,spatial_lag,683.0,0.5,p,Same SAR estimation as T2.4-direct; total effects = direct + indirect (spatial spillover) effects,pct_premium,5.297321577655056,2.912363077655142,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0723094802828652,0.03844626011566611,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8807936081512509,673.0,binary,,2010.0,United States,North America,High income,2004.0,2005.0,single_family,transaction,thesis,False,False,robust,,2004.5,spatial,other,True,True,False
c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662:T3-Batikent,3,1,11,Site/ Apartment,dwelling_type,A_structural,dummy,binary,0.14,0.072,1.945,0.07,,,,high,Located in a gated site complex vs apartment building,"ln(house asking price, TL)",log,OLS,24.0,0.535,se,24 for-sale listings within 1500 m of Batikent metro station (middle-lower income area); distance to school dropped from the printed table,pct_premium,14.729614987077788,8.281971351772036,100*(exp(b - se^2/2) - 1),reported,0.4612291913596902,0.23713583103325978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.945,14.0,binary,,2023.0,Turkey,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,OLS,,2022.0,ols,journal,True,True,False
c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662:T3-Batikent,3,1,11,Square Meter (m2),living_area,A_structural,level,m2,0.008,0.004,2.099,0.052,,,,high,Total residential area in m2,"ln(house asking price, TL)",log,OLS,24.0,0.535,se,24 for-sale listings within 1500 m of Batikent metro station (middle-lower income area); distance to school dropped from the printed table,semi_elasticity,0.8,0.4,100*b/1 (X per m2->m2),reported,0.4892547800992092,0.233089461695669,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.099,14.0,m2,,2023.0,Turkey,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,OLS,,2022.0,ols,journal,True,True,False
c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662:T3-Batikent,3,1,11,Number of Rooms,bedrooms,A_structural,level,count,0.018,0.099,0.184,0.856,,,,high,Number of rooms incl. living rooms,"ln(house asking price, TL)",log,OLS,24.0,0.535,se,24 for-sale listings within 1500 m of Batikent metro station (middle-lower income area); distance to school dropped from the printed table,semi_elasticity,1.7999999999999998,9.9,100*b/1 (per unit count),reported,0.04911671524809719,0.2669386698266152,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.184,14.0,count,,2023.0,Turkey,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,OLS,,2022.0,ols,journal,True,True,False
c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662:T3-Batikent,3,1,11,Floor,floor_level,A_structural,level,count,0.021,0.01,2.015,0.061,,,,high,,"ln(house asking price, TL)",log,OLS,24.0,0.535,se,24 for-sale listings within 1500 m of Batikent metro station (middle-lower income area); distance to school dropped from the printed table,semi_elasticity,2.1,1.0,100*b/1 (per unit count),reported,0.47414750780755527,0.23530893687719862,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.015,14.0,count,,2023.0,Turkey,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,OLS,,2022.0,ols,journal,True,True,False
c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662:T3-Batikent,3,1,11,Building Age (years),age,A_structural,level,years,-0.05,0.043,-1.153,0.266,,,,high,,"ln(house asking price, TL)",log,OLS,24.0,0.535,se,24 for-sale listings within 1500 m of Batikent metro station (middle-lower income area); distance to school dropped from the printed table,semi_elasticity,-5.0,4.3,100*b/1 (per year),reported,-0.29448732117523385,0.25540964542518113,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.153,14.0,years,,2023.0,Turkey,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,OLS,,2022.0,ols,journal,True,True,True
c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662:T5-Koru,5,1,12,Distance to Metro Station(M),transit_distance,D_location,level,m,-1.345e-05,,-0.09,0.93,,,,medium,SE printed .000 (rounded); beta printed -1.345E-5,"ln(house asking price, TL)",log,OLS,18.0,0.932,se,18 for-sale listings within 1500 m of Koru metro station (upper-middle income area),semi_elasticity,-1.345,14.944444444444445,100*b/0.001 (X per m->km),|b/t|,-0.03180370859932566,0.3533745399925073,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.09,8.0,m,,2023.0,Turkey,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,OLS,,2022.0,ols,journal,True,True,False
c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662:T5-Koru,5,1,12,Site/ Apartment,dwelling_type,A_structural,dummy,binary,-0.168,0.164,-1.027,0.331,,,,high,Located in a gated site complex vs apartment building,"ln(house asking price, TL)",log,OLS,18.0,0.932,se,18 for-sale listings within 1500 m of Koru metro station (upper-middle income area),pct_premium,-16.593838462015242,13.863802888828404,100*(exp(b - se^2/2) - 1),reported,-0.34129719202735964,0.3323244323538069,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.027,8.0,binary,,2023.0,Turkey,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,OLS,,2022.0,ols,journal,True,True,False
c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662:T5-Koru,5,1,12,Square Meter (M2),living_area,A_structural,level,m2,0.004,0.001,6.015,0.0,,,,high,Total residential area in m2,"ln(house asking price, TL)",log,OLS,18.0,0.932,se,18 for-sale listings within 1500 m of Koru metro station (upper-middle income area),semi_elasticity,0.4,0.1,100*b/1 (X per m2->m2),reported,0.9049439273201987,0.1504478682161594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.015,8.0,m2,,2023.0,Turkey,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,OLS,,2022.0,ols,journal,True,True,False
c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662:T5-Koru,5,1,12,Number of Rooms,bedrooms,A_structural,level,count,0.344,0.099,3.484,0.007,,,,high,Number of rooms incl. living rooms,"ln(house asking price, TL)",log,OLS,18.0,0.932,se,18 for-sale listings within 1500 m of Koru metro station (upper-middle income area),semi_elasticity,34.4,9.9,100*b/1 (per unit count),reported,0.7763672690856761,0.22283790731506203,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.484,8.0,count,,2023.0,Turkey,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,OLS,,2022.0,ols,journal,True,True,False
c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662:T5-Koru,5,1,12,Floor,floor_level,A_structural,level,count,0.028,0.009,3.105,0.013,,,,high,,"ln(house asking price, TL)",log,OLS,18.0,0.932,se,18 for-sale listings within 1500 m of Koru metro station (upper-middle income area),semi_elasticity,2.8000000000000003,0.8999999999999999,100*b/1 (per unit count),reported,0.7392642365409504,0.23808832094716598,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.105,8.0,count,,2023.0,Turkey,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,OLS,,2022.0,ols,journal,True,True,False
c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662,c15ba8a0a6017224eaf4694459bf962179074662:T5-Koru,5,1,12,Building Age (Years),age,A_structural,level,years,0.029,0.055,0.526,0.612,,,,high,,"ln(house asking price, TL)",log,OLS,18.0,0.932,se,18 for-sale listings within 1500 m of Koru metro station (upper-middle income area),semi_elasticity,2.9000000000000004,5.5,100*b/1 (per year),reported,0.1828343393638654,0.34759380107198745,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.526,8.0,years,,2023.0,Turkey,Asia,Upper middle income,2022.0,2022.0,condo_apartment,listing,journal,False,False,OLS,,2022.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T2-c1,2,1,7,ln(building age),age,A_structural,log,years,-0.011,,-0.734,,,,,high,"building age in years (age=1 if built 2014), log","ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.567,t,Model 1 traditional hedonic; adj R2,elasticity,-0.011,0.014986376021798364,b (log-log),|b/t|,-0.03012808436941698,0.04104643647059534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.734,593.0,years,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T2-c1,2,1,7,Nearby university,university_distance,D_location,binary,binary,0.046,,2.979,,***,,,high,1 = college/university within 1000 m,"ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.567,t,Model 1 traditional hedonic; adj R2,pct_premium,4.6949587467338905,1.6168319202423334,100*(exp(b - se^2/2) - 1),|b/t|,0.12142763951526665,0.0407612082964977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.979,593.0,binary,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T2-c1,2,1,7,Nearby subway,transit_distance,D_location,binary,binary,0.02,,1.162,,,,,high,1 = metro station within 500 m,"ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.567,t,Model 1 traditional hedonic; adj R2,pct_premium,2.005023759090818,1.7559403442801307,100*(exp(b - se^2/2) - 1),|b/t|,0.04766338754352698,0.04101840580337951,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.162,593.0,binary,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T2-c1,2,1,7,ln(distance to Wulin Square),cbd_distance,D_location,log,km,-0.067,,-3.429,,***,,,high,"walking distance to traditional CBD (Wulin Square), km, log","ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.567,t,Model 1 traditional hedonic; adj R2,elasticity,-0.067,0.019539224263633713,b (log-log),|b/t|,-0.13943655982735914,0.0406639136271097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.429,593.0,km,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T2-c1,2,1,7,ln(distance to the West Lake),water_proximity,E_environment,log,km,-0.221,,-12.694,,***,,,high,"walking distance to the West Lake, km, log","ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.567,t,Model 1 traditional hedonic; adj R2,elasticity,-0.221,0.01740979990546715,b (log-log),|b/t|,-0.4622460262236959,0.036414528613809345,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.694,593.0,km,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T2-c1,2,1,7,ln(distance to the Qianjiang New Center),cbd_distance,D_location,log,km,-0.059,,-4.018,,***,,,high,"walking distance to new CBD (Qianjiang New Center), km, log","ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.567,t,Model 1 traditional hedonic; adj R2,elasticity,-0.059,0.014683922349427576,b (log-log),|b/t|,-0.16279828725190018,0.040517244214011996,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.018,593.0,km,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T3-c1,3,1,8,ln(building age),age,A_structural,log,years,-0.061,,-3.765,,***,,,high,"building age in years (age=1 if built 2014), log; base term of spatial expansion model (interaction terms with coordinates not extracted); only terms significant at 10% are printed","ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.671,t,Model 2 one-degree spatial expansion (OLS with coordinate interactions); base coefficients only; adj R2,elasticity,-0.061,0.016201859229747675,b (log-log),|b/t|,-0.15279458362603907,0.04058289073732777,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.765,593.0,years,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T3-c1,3,1,8,ln(distance to Wulin Square),cbd_distance,D_location,log,km,-0.087,,1.786,,*,,,medium,"walking distance to traditional CBD (Wulin Square), km, log; base term of spatial expansion model (interaction terms with coordinates not extracted); only terms significant at 10% are printed; printed t = 1.786 has sign inconsistent with negative coefficient","ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.671,t,Model 2 one-degree spatial expansion (OLS with coordinate interactions); base coefficients only; adj R2,elasticity,-0.087,0.04871220604703247,b (log-log),|b/t|,0.07314576480728978,0.04095507548000547,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.786,593.0,km,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T3-c1,3,1,8,ln(distance to the West Lake),water_proximity,E_environment,log,km,-0.269,,-7.596,,***,,,high,"walking distance to the West Lake, km, log; base term of spatial expansion model (interaction terms with coordinates not extracted); only terms significant at 10% are printed","ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.671,t,Model 2 one-degree spatial expansion (OLS with coordinate interactions); base coefficients only; adj R2,elasticity,-0.269,0.03541337546076883,b (log-log),|b/t|,-0.29777951232097755,0.039202147488280346,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.596,593.0,km,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T3-c1,3,1,8,ln(distance to the Qianjiang New Center),cbd_distance,D_location,log,km,-0.185,,-4.028,,***,,,high,"walking distance to new CBD (Qianjiang New Center), km, log; base term of spatial expansion model (interaction terms with coordinates not extracted); only terms significant at 10% are printed","ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.671,t,Model 2 one-degree spatial expansion (OLS with coordinate interactions); base coefficients only; adj R2,elasticity,-0.185,0.04592850049652433,b (log-log),|b/t|,-0.1631926822402144,0.04051456857999366,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.028,593.0,km,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T3-c2,3,2,8,ln(building age),age,A_structural,log,years,-0.079,,-3.247,,***,,,high,"building age in years (age=1 if built 2014), log; base term of spatial expansion model (interaction terms with coordinates not extracted); only terms significant at 10% are printed","ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.704,t,Model 3 quadratic spatial expansion; base coefficients only; adj R2,elasticity,-0.079,0.024330150908530954,b (log-log),|b/t|,-0.13216856561431098,0.04070482464253495,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.247,593.0,years,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T3-c2,3,2,8,Nearby subway,transit_distance,D_location,binary,binary,-0.209,,-3.208,,***,,,high,1 = metro station within 500 m; base term of spatial expansion model (interaction terms with coordinates not extracted); only terms significant at 10% are printed,"ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.704,t,Model 3 quadratic spatial expansion; base coefficients only; adj R2,pct_premium,-19.03249113244415,5.2862096087740955,100*(exp(b - se^2/2) - 1),|b/t|,-0.13060831943954102,0.04071331653352276,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.208,593.0,binary,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T3-c2,3,2,8,ln(distance to Wulin Square),cbd_distance,D_location,log,km,-0.168,,-2.149,,**,,,high,"walking distance to traditional CBD (Wulin Square), km, log; base term of spatial expansion model (interaction terms with coordinates not extracted); only terms significant at 10% are printed","ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.704,t,Model 3 quadratic spatial expansion; base coefficients only; adj R2,elasticity,-0.168,0.07817589576547232,b (log-log),|b/t|,-0.08790721221488794,0.040906101542525795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.149,593.0,km,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T3-c2,3,2,8,ln(distance to the West Lake),water_proximity,E_environment,log,km,-0.336,,-6.557,,***,,,high,"walking distance to the West Lake, km, log; base term of spatial expansion model (interaction terms with coordinates not extracted); only terms significant at 10% are printed","ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.704,t,Model 3 quadratic spatial expansion; base coefficients only; adj R2,elasticity,-0.336,0.05124294646942199,b (log-log),|b/t|,-0.2600031379134061,0.03965275856541195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.557,593.0,km,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,True
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T3-c2,3,2,8,ln(distance to the Qianjiang New Center),cbd_distance,D_location,log,km,-0.237,,-3.061,,***,,,high,"walking distance to new CBD (Qianjiang New Center), km, log; base term of spatial expansion model (interaction terms with coordinates not extracted); only terms significant at 10% are printed","ln(P), average community housing price (RMB, likely per m2)",log,OLS,603.0,0.704,t,Model 3 quadratic spatial expansion; base coefficients only; adj R2,elasticity,-0.237,0.07742567788304476,b (log-log),|b/t|,-0.12471875387342918,0.040744447524805355,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.061,593.0,km,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,ols,journal,True,True,False
c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7:T5-c1,5,1,10,Nearby university,university_distance,D_location,binary,binary,0.04,,2.635,,,,,high,"1 = college/university within 1000 m; MGWR global coefficient; t value printed, no stars (critical values 1.648/1.965)","ln(P), average community housing price (RMB, likely per m2)",log,GWR,603.0,0.766,t,"Model 5 MGWR, global (fixed) variables; critical t 1.648 (10%), 1.965 (5%); adj R2 from Table 6",pct_premium,4.069085864129884,1.5799784048461303,100*(exp(b - se^2/2) - 1),|b/t|,0.10757851446610504,0.04082676070819927,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.635,593.0,binary,,2017.0,China,Asia,Upper middle income,2014.0,2014.0,condo_apartment,unknown,journal,False,False,OLS,,2014.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c1,3,OLS,12,Living area,living_area,A_structural,level,sqft,0.0003,4.07e-06,,,***,,,medium,Square feet of living space; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,OLS,8241.0,0.823,se,OLS,semi_elasticity,0.32291731250129163,0.004380911539600857,100*b/0.092903 (X per sqft->m2),reported,0.6305726619654912,0.008554769113998498,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),73.7100737100737,8231.0,sqft,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,ols,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c2,3,800-m weights,12,Living area,living_area,A_structural,level,sqft,0.0002,3.95e-06,,,***,,,medium,Square feet of living space; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 800-m distance weights",semi_elasticity,0.21527820833419445,0.00425174461460034,100*b/0.092903 (X per sqft->m2),reported,0.4873351962756465,0.009624870126444017,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),50.63291139240506,8231.0,sqft,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c3,3,1000-m weights,12,Living area,living_area,A_structural,level,sqft,0.0002,3.96e-06,,,***,,,medium,Square feet of living space; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 1000-m distance weights",semi_elasticity,0.21527820833419445,0.00426250852501705,100*b/0.092903 (X per sqft->m2),reported,0.4863959801751084,0.009630640407467146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),50.505050505050505,8231.0,sqft,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c4,3,Nearest 10 weights,12,Living area,living_area,A_structural,level,sqft,0.0002,3.99e-06,,,***,,,medium,Square feet of living space; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 10 nearest neighbours weights",semi_elasticity,0.21527820833419445,0.004294800256267179,100*b/0.092903 (X per sqft->m2),reported,0.48359661833600825,0.009647752535803364,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),50.12531328320802,8231.0,sqft,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c5,3,Nearest 20 weights,12,Living area,living_area,A_structural,level,sqft,0.0002,3.97e-06,,,***,,,medium,Square feet of living space; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 20 nearest neighbours weights (preferred, lowest AIC)",semi_elasticity,0.21527820833419445,0.004273272435433759,100*b/0.092903 (X per sqft->m2),reported,0.4854598192694568,0.009636377412498717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),50.377833753148614,8231.0,sqft,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c6,3,Nearest 30 weights,12,Living area,living_area,A_structural,level,sqft,0.0002,3.96e-06,,,***,,,medium,Square feet of living space; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 30 nearest neighbours weights",semi_elasticity,0.21527820833419445,0.00426250852501705,100*b/0.092903 (X per sqft->m2),reported,0.4863959801751084,0.009630640407467146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),50.505050505050505,8231.0,sqft,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c1,3,OLS,12,Lot size,lot_size,A_structural,level,sqft,7.04e-06,3.8e-07,,,***,,,medium,Square feet of lot; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,OLS,8241.0,0.823,se,OLS,semi_elasticity,0.007577792933363644,0.00040902859583496945,100*b/0.092903 (X per sqft->m2),reported,0.20007445400320978,0.010799473369491434,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.526315789473685,8231.0,sqft,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,ols,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c2,3,800-m weights,12,Lot size,lot_size,A_structural,level,sqft,6.67e-06,3.58e-07,,,***,,,medium,Square feet of lot; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 800-m distance weights",semi_elasticity,0.007179528247945384,0.00038534799291820807,100*b/0.092903 (X per sqft->m2),reported,0.20116231628682757,0.010797017875664807,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.631284916201118,8231.0,sqft,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c3,3,1000-m weights,12,Lot size,lot_size,A_structural,level,sqft,6.81e-06,3.61e-07,,,***,,,medium,Square feet of lot; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 1000-m distance weights",semi_elasticity,0.00733022299377932,0.000388577166043221,100*b/0.092903 (X per sqft->m2),reported,0.20357418534014743,0.010791524362377857,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.86426592797784,8231.0,sqft,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c4,3,Nearest 10 weights,12,Lot size,lot_size,A_structural,level,sqft,6.29e-06,3.53e-07,,,***,,,medium,Square feet of lot; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 10 nearest neighbours weights",semi_elasticity,0.006770499652110415,0.00037996603770985317,100*b/0.092903 (X per sqft->m2),reported,0.19272179441381057,0.010815706427356936,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.81869688385269,8231.0,sqft,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c5,3,Nearest 20 weights,12,Lot size,lot_size,A_structural,level,sqft,6.58e-06,3.54e-07,,,***,,,medium,Square feet of lot; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 20 nearest neighbours weights (preferred, lowest AIC)",semi_elasticity,0.007082653054194996,0.00038104242875152414,100*b/0.092903 (X per sqft->m2),reported,0.20070936724286717,0.010798041945892855,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.587570621468924,8231.0,sqft,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c6,3,Nearest 30 weights,12,Lot size,lot_size,A_structural,level,sqft,6.73e-06,3.56e-07,,,***,,,medium,Square feet of lot; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 30 nearest neighbours weights",semi_elasticity,0.0072441117104456425,0.0003831952108348661,100*b/0.092903 (X per sqft->m2),reported,0.2039902652270957,0.010790569750497187,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.90449438202247,8231.0,sqft,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c1,3,OLS,12,Bedroom,bedrooms,A_structural,level,count,-0.0188,0.0029,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,OLS,8241.0,0.823,se,OLS,semi_elasticity,-1.8800000000000001,0.29,100*b/1 (per unit count),reported,-0.07127342886170468,0.010994305515901255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.482758620689656,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,ols,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c2,3,800-m weights,12,Bedroom,bedrooms,A_structural,level,count,-0.012,0.0027,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 800-m distance weights",semi_elasticity,-1.2,0.27,100*b/1 (per unit count),reported,-0.04892948972520965,0.01100913518817217,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.444444444444445,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c3,3,1000-m weights,12,Bedroom,bedrooms,A_structural,level,count,-0.0135,0.0028,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 1000-m distance weights",semi_elasticity,-1.35,0.27999999999999997,100*b/1 (per unit count),reported,-0.0530685264309536,0.011006805481975562,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.821428571428571,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c4,3,Nearest 10 weights,12,Bedroom,bedrooms,A_structural,level,count,-0.0101,0.0027,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 10 nearest neighbours weights",semi_elasticity,-1.01,0.27,100*b/1 (per unit count),reported,-0.041196702974143934,0.011012980002988972,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.7407407407407405,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c5,3,Nearest 20 weights,12,Bedroom,bedrooms,A_structural,level,count,-0.0106,0.0027,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 20 nearest neighbours weights (preferred, lowest AIC)",semi_elasticity,-1.06,0.27,100*b/1 (per unit count),reported,-0.04323242165521708,0.011012031931045862,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.9259259259259256,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c6,3,Nearest 30 weights,12,Bedroom,bedrooms,A_structural,level,count,-0.0117,0.0027,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 30 nearest neighbours weights",semi_elasticity,-1.17,0.27,100*b/1 (per unit count),reported,-0.04770907237289852,0.011009785932207352,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.333333333333333,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c1,3,OLS,12,Bathroom,bathrooms,A_structural,level,count,0.0319,0.0031,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,OLS,8241.0,0.823,se,OLS,semi_elasticity,3.19,0.31,100*b/1 (per unit count),reported,0.11270078325213381,0.010952113732965984,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.29032258064516,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,ols,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c2,3,800-m weights,12,Bathroom,bathrooms,A_structural,level,count,0.0275,0.0029,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 800-m distance weights",semi_elasticity,2.75,0.29,100*b/1 (per unit count),reported,0.1039558543314992,0.010962617365867188,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.482758620689657,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c3,3,1000-m weights,12,Bathroom,bathrooms,A_structural,level,count,0.0287,0.0029,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 1000-m distance weights",semi_elasticity,2.87,0.29,100*b/1 (per unit count),reported,0.10843986963637885,0.010957338743745597,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.896551724137932,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c4,3,Nearest 10 weights,12,Bathroom,bathrooms,A_structural,level,count,0.027,0.0029,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 10 nearest neighbours weights",semi_elasticity,2.7,0.29,100*b/1 (per unit count),reported,0.10208562603659456,0.010964752426152748,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.310344827586208,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c5,3,Nearest 20 weights,12,Bathroom,bathrooms,A_structural,level,count,0.0263,0.0029,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 20 nearest neighbours weights (preferred, lowest AIC)",semi_elasticity,2.63,0.29,100*b/1 (per unit count),reported,0.09946549104823459,0.01096767772014754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.06896551724138,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c6,3,Nearest 30 weights,12,Bathroom,bathrooms,A_structural,level,count,0.0268,0.0029,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 30 nearest neighbours weights",semi_elasticity,2.68,0.29,100*b/1 (per unit count),reported,0.10133723038048492,0.010965595824753965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.24137931034483,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c1,3,OLS,13,Garage,garage,A_structural,level,count,0.1169,0.0039,,,***,,,medium,Number of garages; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,OLS,8241.0,0.823,se,OLS,semi_elasticity,11.690000000000001,0.38999999999999996,100*b/1 (per unit count),reported,0.31370923727687633,0.010465919806499722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.974358974358978,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,ols,journal,True,True,True
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c2,3,800-m weights,13,Garage,garage,A_structural,level,count,0.1105,0.0037,,,***,,,medium,Number of garages; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 800-m distance weights",semi_elasticity,11.05,0.37,100*b/1 (per unit count),reported,0.3126755014958113,0.010469677425651603,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.864864864864863,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c3,3,1000-m weights,13,Garage,garage,A_structural,level,count,0.1122,0.0037,,,***,,,medium,Number of garages; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 1000-m distance weights",semi_elasticity,11.219999999999999,0.37,100*b/1 (per unit count),reported,0.3170057838454296,0.01045384492181898,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.324324324324323,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c4,3,Nearest 10 weights,13,Garage,garage,A_structural,level,count,0.1041,0.0037,,,***,,,medium,Number of garages; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 10 nearest neighbours weights",semi_elasticity,10.41,0.37,100*b/1 (per unit count),reported,0.29619893619739357,0.010527723957063941,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.135135135135133,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c5,3,Nearest 20 weights,13,Garage,garage,A_structural,level,count,0.1057,0.0037,,,***,,,medium,Number of garages; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 20 nearest neighbours weights (preferred, lowest AIC)",semi_elasticity,10.57,0.37,100*b/1 (per unit count),reported,0.3003436303168339,0.010513447797278006,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.56756756756757,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c6,3,Nearest 30 weights,13,Garage,garage,A_structural,level,count,0.1069,0.0037,,,***,,,medium,Number of garages; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 30 nearest neighbours weights",semi_elasticity,10.69,0.37,100*b/1 (per unit count),reported,0.3034410394569565,0.010502636538734697,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.891891891891888,8231.0,count,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c1,3,OLS,13,House age,age,A_structural,level,years,-0.0024,0.0001,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,OLS,8241.0,0.823,se,OLS,semi_elasticity,-0.24,0.01,100*b/1 (per year),reported,-0.2557391654052089,0.010655798558550374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-23.999999999999996,8231.0,years,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,ols,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c2,3,800-m weights,13,House age,age,A_structural,level,years,-0.0022,0.0001,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 800-m distance weights",semi_elasticity,-0.22,0.01,100*b/1 (per year),reported,-0.23566168852837724,0.010711894933108057,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.0,8231.0,years,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c3,3,1000-m weights,13,House age,age,A_structural,level,years,-0.0022,0.0001,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 1000-m distance weights",semi_elasticity,-0.22,0.01,100*b/1 (per year),reported,-0.23566168852837724,0.010711894933108057,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.0,8231.0,years,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c4,3,Nearest 10 weights,13,House age,age,A_structural,level,years,-0.0023,0.0001,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 10 nearest neighbours weights",semi_elasticity,-0.22999999999999998,0.01,100*b/1 (per year),reported,-0.24573995982314573,0.010684346079267205,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-23.0,8231.0,years,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c5,3,Nearest 20 weights,13,House age,age,A_structural,level,years,-0.0022,0.0001,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 20 nearest neighbours weights (preferred, lowest AIC)",semi_elasticity,-0.22,0.01,100*b/1 (per year),reported,-0.23566168852837724,0.010711894933108057,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.0,8231.0,years,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c6,3,Nearest 30 weights,13,House age,age,A_structural,level,years,-0.0022,0.0001,,,***,,,medium,parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 30 nearest neighbours weights",semi_elasticity,-0.22,0.01,100*b/1 (per year),reported,-0.23566168852837724,0.010711894933108057,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.0,8231.0,years,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c1,3,OLS,13,Downtown,cbd_distance,D_location,level,km,-0.0054,0.0014,,,***,,,medium,Distance to the downtown area (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,OLS,8241.0,0.823,se,OLS,semi_elasticity,-0.54,0.13999999999999999,100*b/1 (X per km->km),reported,-0.04247635907499242,0.01101238938981285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.857142857142857,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,ols,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c2,3,800-m weights,13,Downtown,cbd_distance,D_location,level,km,-0.0127,0.0013,,,***,,,medium,Distance to the downtown area (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 800-m distance weights",semi_elasticity,-1.27,0.13,100*b/1 (X per km->km),reported,-0.10706086445931844,0.010958986125757004,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.76923076923077,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c3,3,1000-m weights,13,Downtown,cbd_distance,D_location,level,km,-0.0143,0.0013,,,***,,,medium,Distance to the downtown area (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 1000-m distance weights",semi_elasticity,-1.43,0.13,100*b/1 (X per km->km),reported,-0.12036423012141234,0.010942202738310213,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.0,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c4,3,Nearest 10 weights,13,Downtown,cbd_distance,D_location,level,km,-0.0081,0.0013,,,***,,,medium,Distance to the downtown area (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 10 nearest neighbours weights",semi_elasticity,-0.8099999999999999,0.13,100*b/1 (X per km->km),reported,-0.06851624803644325,0.010996434870046447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.230769230769231,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c5,3,Nearest 20 weights,13,Downtown,cbd_distance,D_location,level,km,-0.0096,0.0013,,,***,,,medium,Distance to the downtown area (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 20 nearest neighbours weights (preferred, lowest AIC)",semi_elasticity,-0.96,0.13,100*b/1 (X per km->km),reported,-0.08112742040027039,0.010986004845869951,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.384615384615384,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c6,3,Nearest 30 weights,13,Downtown,cbd_distance,D_location,level,km,-0.0108,0.0013,,,***,,,medium,Distance to the downtown area (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 30 nearest neighbours weights",semi_elasticity,-1.08,0.13,100*b/1 (X per km->km),reported,-0.09118867232355501,0.010976414261168658,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.307692307692308,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c1,3,OLS,13,University of Alberta,university_distance,D_location,level,km,-0.0114,0.0015,,,***,,,medium,Distance to the University of Alberta (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,OLS,8241.0,0.823,se,OLS,semi_elasticity,-1.1400000000000001,0.15,100*b/1 (X per km->km),reported,-0.08347737997932358,0.010983865786753104,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.6000000000000005,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,ols,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c2,3,800-m weights,13,University of Alberta,university_distance,D_location,level,km,-0.0028,0.0015,,,***,,,medium,Distance to the University of Alberta (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 800-m distance weights",semi_elasticity,-0.27999999999999997,0.15,100*b/1 (X per km->km),reported,-0.020570676080559885,0.01102000504315708,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8666666666666667,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c3,3,1000-m weights,13,University of Alberta,university_distance,D_location,level,km,-0.0012,0.0015,,,***,,,medium,Distance to the University of Alberta (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 1000-m distance weights",semi_elasticity,-0.12,0.15,100*b/1 (X per km->km),reported,-0.008817527088726513,0.011021908860908142,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7999999999999999,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c4,3,Nearest 10 weights,13,University of Alberta,university_distance,D_location,level,km,-0.007,0.0014,,,***,,,medium,Distance to the University of Alberta (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 10 nearest neighbours weights",semi_elasticity,-0.7000000000000001,0.13999999999999999,100*b/1 (X per km->km),reported,-0.05502818164535149,0.011005636329070298,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c5,3,Nearest 20 weights,13,University of Alberta,university_distance,D_location,level,km,-0.0056,0.0014,,,***,,,medium,Distance to the University of Alberta (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 20 nearest neighbours weights (preferred, lowest AIC)",semi_elasticity,-0.5599999999999999,0.13999999999999999,100*b/1 (X per km->km),reported,-0.04404655979864707,0.011011639949661768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c6,3,Nearest 30 weights,13,University of Alberta,university_distance,D_location,level,km,-0.0043,0.0014,,,***,,,medium,Distance to the University of Alberta (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 30 nearest neighbours weights",semi_elasticity,-0.43,0.13999999999999999,100*b/1 (X per km->km),reported,-0.033834938064387116,0.01101602634654464,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0714285714285716,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c1,3,OLS,13,Hospital,hospital_distance,D_location,level,km,-0.0037,0.0011,,,***,,,medium,Distance to a hospital (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,OLS,8241.0,0.823,se,OLS,semi_elasticity,-0.37,0.11,100*b/1 (X per km->km),reported,-0.0370496798788878,0.011014769693723399,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.3636363636363638,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,ols,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c2,3,800-m weights,13,Hospital,hospital_distance,D_location,level,km,-0.005,0.001,,,***,,,medium,Distance to a hospital (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 800-m distance weights",semi_elasticity,-0.5,0.1,100*b/1 (X per km->km),reported,-0.05502818164535149,0.011005636329070298,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c3,3,1000-m weights,13,Hospital,hospital_distance,D_location,level,km,-0.0054,0.001,,,***,,,medium,Distance to a hospital (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 1000-m distance weights",semi_elasticity,-0.54,0.1,100*b/1 (X per km->km),reported,-0.05941546904861625,0.011002864638632637,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.4,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c4,3,Nearest 10 weights,13,Hospital,hospital_distance,D_location,level,km,-0.0035,0.001,,,***,,,medium,Distance to a hospital (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 10 nearest neighbours weights",semi_elasticity,-0.35000000000000003,0.1,100*b/1 (X per km->km),reported,-0.03854950525862757,0.011014144359607876,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c5,3,Nearest 20 weights,13,Hospital,hospital_distance,D_location,level,km,-0.0043,0.001,,,***,,,medium,Distance to a hospital (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 20 nearest neighbours weights (preferred, lowest AIC)",semi_elasticity,-0.43,0.1,100*b/1 (X per km->km),reported,-0.04734290524921149,0.011009977964932905,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.3,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c6,3,Nearest 30 weights,13,Hospital,hospital_distance,D_location,level,km,-0.0049,0.001,,,***,,,medium,Distance to a hospital (km); parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 30 nearest neighbours weights",semi_elasticity,-0.49,0.1,100*b/1 (X per km->km),reported,-0.05393085160884531,0.011006296246703125,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.8999999999999995,8231.0,km,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c1,3,OLS,13,River buffer,water_proximity,E_environment,binary,binary,0.0302,0.0044,,,***,,,medium,1 if within 2 km of the North Saskatchewan River; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,OLS,8241.0,0.823,se,OLS,pct_premium,3.0650668724011565,0.4534906840071399,100*(exp(b - se^2/2) - 1),reported,0.07543774240404066,0.010990929356880098,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.863636363636363,8231.0,binary,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,ols,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c2,3,800-m weights,13,River buffer,water_proximity,E_environment,binary,binary,0.0106,0.0042,,,***,,,medium,1 if within 2 km of the North Saskatchewan River; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 800-m distance weights",pct_premium,1.064746507986336,0.42447567919252266,100*(exp(b - se^2/2) - 1),reported,0.027807522555393305,0.01101807497477848,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.523809523809524,8231.0,binary,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c3,3,1000-m weights,13,River buffer,water_proximity,E_environment,binary,binary,0.0088,0.0042,,,***,,,medium,1 if within 2 km of the North Saskatchewan River; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 1000-m distance weights",pct_premium,0.8829935909705711,0.4237123102081717,100*(exp(b - se^2/2) - 1),reported,0.02308826485796865,0.011019399136757766,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0952380952380953,8231.0,binary,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,True
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c4,3,Nearest 10 weights,13,River buffer,water_proximity,E_environment,binary,binary,0.0189,0.0041,,,***,,,medium,1 if within 2 km of the North Saskatchewan River; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 10 nearest neighbours weights",pct_premium,1.9071170219103317,0.41782269157479673,100*(exp(b - se^2/2) - 1),reported,0.050744825474978376,0.01100813674324928,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.609756097560975,8231.0,binary,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c5,3,Nearest 20 weights,13,River buffer,water_proximity,E_environment,binary,binary,0.0164,0.0041,,,***,,,medium,1 if within 2 km of the North Saskatchewan River; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 20 nearest neighbours weights (preferred, lowest AIC)",pct_premium,1.6526674238789063,0.4167794394543707,100*(exp(b - se^2/2) - 1),reported,0.04404655979864707,0.011011639949661768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,8231.0,binary,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6,c8acd4a142f8c89ba5c53a61a81bfd91957160a6:T3-c6,3,Nearest 30 weights,13,River buffer,water_proximity,E_environment,binary,binary,0.0158,0.0041,,,***,,,medium,1 if within 2 km of the North Saskatchewan River; parentheses not labelled in table note (only star legend); values consistent with standard errors,Log of transacted price (2016 CAD$),log,spatial_lag,8241.0,,se,"SAR, 30 nearest neighbours weights",pct_premium,1.5916941172457566,0.4165294467959954,100*(exp(b - se^2/2) - 1),reported,0.04243805751662775,0.011012407330264163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8536585365853657,8231.0,binary,,2024.0,Canada,North America,High income,2015.0,2017.0,single_family,transaction,journal,True,False,unknown,,2016.0,spatial,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M1,5,Model 1,9,Age,age,A_structural,level,years,0.000901,0.000118,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.632006,se,"Model 1 (Base): linear ASB, no squared terms",semi_elasticity,0.0901,0.0118,100*b/1 (per year),reported,0.06325915794001948,0.008284773181933738,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.635593220338984,14511.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M2,5,Model 2,9,Age,age,A_structural,level,years,0.002997,0.000507,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.651338,se,Model 2 (Base 2): adds squared terms,semi_elasticity,0.2997,0.050699999999999995,100*b/1 (per year),reported,0.04901261181166318,0.008291422818990068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9112426035502965,14511.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M3,5,Model 3,9,Age,age,A_structural,level,years,0.002931,0.000506,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.652927,se,Model 3 (Density): adds ASB x population density interaction,semi_elasticity,0.2931,0.050600000000000006,100*b/1 (per year),reported,0.0480302794204838,0.008291818965119347,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.792490118577074,14511.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M4,5,Model 4,9,Age,age,A_structural,level,years,0.002727,0.000361,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.823421,se,Model 4 (Property price): adds ASB x price interaction (price on RHS),semi_elasticity,0.2727,0.0361,100*b/1 (per year),reported,0.06258597583337143,0.0082851255136953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.554016620498615,14511.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M5,5,Model 5,9,Age,age,A_structural,level,years,0.002858,0.000507,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.65152,se,Model 5 (Private): adds ASB x Private interaction,semi_elasticity,0.2858,0.050699999999999995,100*b/1 (per year),reported,0.04674450848376119,0.00829232533284357,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.6370808678500985,14511.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M6,5,Model 6,9,Age,age,A_structural,level,years,0.002771,0.000509,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.651877,se,Model 6 (Belfast): adds ASB x Belfast interaction,semi_elasticity,0.2771,0.0509,100*b/1 (per year),reported,0.04514680528365604,0.00829293536246154,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.444007858546169,14511.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M1,5,Model 1,9,Size,living_area,A_structural,level,m2,0.005028,6.64e-05,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,14521.0,0.632006,se,"Model 1 (Base): linear ASB, no squared terms",semi_elasticity,0.5028,0.00664,100*b/1 (X per m2->m2),reported,0.5321925218636238,0.007028158999949207,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),75.72289156626506,14511.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M2,5,Model 2,9,Size,living_area,A_structural,level,m2,0.008369,0.000173,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,14521.0,0.651338,se,Model 2 (Base 2): adds squared terms,semi_elasticity,0.8369,0.0173,100*b/1 (X per m2->m2),reported,0.37265925591022947,0.007703435448974753,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),48.3757225433526,14511.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M3,5,Model 3,9,Size,living_area,A_structural,level,m2,0.008245,0.000173,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,14521.0,0.652927,se,Model 3 (Density): adds ASB x population density interaction,semi_elasticity,0.8245,0.0173,100*b/1 (X per m2->m2),reported,0.3678898686004863,0.007719217376335249,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.65895953757226,14511.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M4,5,Model 4,9,Size,living_area,A_structural,level,m2,0.005017,0.000126,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,14521.0,0.823421,se,Model 4 (Property price): adds ASB x price interaction (price on RHS),semi_elasticity,0.5016999999999999,0.0126,100*b/1 (X per m2->m2),reported,0.31384034410916195,0.00788197794653267,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),39.817460317460316,14511.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M5,5,Model 5,9,Size,living_area,A_structural,level,m2,0.008363,0.000173,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,14521.0,0.65152,se,Model 5 (Private): adds ASB x Private interaction,semi_elasticity,0.8363,0.0173,100*b/1 (X per m2->m2),reported,0.3724291537568201,0.007704202271903608,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),48.34104046242775,14511.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M6,5,Model 6,9,Size,living_area,A_structural,level,m2,0.008346,0.000173,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,14521.0,0.651877,se,Model 6 (Belfast): adds ASB x Belfast interaction,semi_elasticity,0.8345999999999999,0.0173,100*b/1 (X per m2->m2),reported,0.3717768246038096,0.007706373191523972,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),48.24277456647398,14511.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M1,5,Model 1,9,Parking onsite,parking,A_structural,binary,binary,0.085923,0.010863,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.632006,se,"Model 1 (Base): linear ASB, no squared terms",pct_premium,8.965812212426139,1.1837654609880022,100*(exp(b - se^2/2) - 1),reported,0.06552043579487225,0.008283561957097601,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.909693454846728,14511.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M2,5,Model 2,9,Parking onsite,parking,A_structural,binary,binary,0.063596,0.010765,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.651338,se,Model 2 (Base 2): adds squared terms,pct_premium,6.560003898339151,1.1471849109306695,100*(exp(b - se^2/2) - 1),reported,0.048983009036047784,0.008291434874411195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.907663725034835,14511.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M3,5,Model 3,9,Parking onsite,parking,A_structural,binary,binary,0.054154,0.010803,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.652927,se,Model 3 (Density): adds ASB x population density interaction,pct_premium,5.558556154754801,1.1404156261922123,100*(exp(b - se^2/2) - 1),reported,0.04157782651503092,0.008294221291906028,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.012866796260298,14511.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M4,5,Model 4,9,Parking onsite,parking,A_structural,binary,binary,0.027686,0.007667,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.823421,se,Model 4 (Property price): adds ASB x price interaction (price on RHS),pct_premium,2.804260276791304,0.7882234302269092,100*(exp(b - se^2/2) - 1),reported,0.029963396191029126,0.008297672419151208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.611060388678753,14511.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M5,5,Model 5,9,Parking onsite,parking,A_structural,binary,binary,0.064033,0.010774,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.65152,se,Model 5 (Private): adds ASB x Private interaction,pct_premium,6.606570463458072,1.1486458551134338,100*(exp(b - se^2/2) - 1),reported,0.04927768186025674,0.008291314546599505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.943289400408391,14511.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T5-M6,5,Model 6,9,Parking onsite,parking,A_structural,binary,binary,0.060777,0.010773,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.651877,se,Model 6 (Belfast): adds ASB x Belfast interaction,pct_premium,6.260025098699362,1.1448056801200617,100*(exp(b - se^2/2) - 1),reported,0.04678193379631546,0.008292310788418423,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.641604010025063,14511.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M7,6,Model 7,10,Age,age,A_structural,level,years,0.006723,0.000856,,,***,,,high,,ln property price (GBP),log,OLS,4018.0,0.523332,se,Model 7: detached houses only,semi_elasticity,0.6723,0.0856,100*b/1 (per year),reported,0.1231144290853871,0.01567543526656126,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.853971962616822,4008.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M8,6,Model 8,10,Age,age,A_structural,level,years,0.000851,0.000923,,,,,,high,,ln property price (GBP),log,OLS,4990.0,0.471448,se,Model 8: semi-detached houses only,semi_elasticity,0.0851,0.0923,100*b/1 (per year),reported,0.013063998576847273,0.01416929575373682,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9219934994582881,4980.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M9,6,Model 9,10,Age,age,A_structural,level,years,-0.002881,0.001315,,,**,,,high,,ln property price (GBP),log,OLS,3571.0,0.379724,se,Model 9: terraced houses only,semi_elasticity,-0.28809999999999997,0.1315,100*b/1 (per year),reported,-0.03668926565468227,0.016746402060363482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.190874524714829,3561.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M10,6,Model 10,10,Age,age,A_structural,level,years,-0.005064,0.002595,,,**,,,high,,ln property price (GBP),log,OLS,520.0,0.492908,se,Model 10: apartments only,semi_elasticity,-0.5064,0.2595,100*b/1 (per year),reported,-0.0860906219946471,0.0441163436169252,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9514450867052022,510.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M11,6,Model 11,10,Age,age,A_structural,level,years,0.003915,0.002399,,,*,,,high,,ln property price (GBP),log,OLS,626.0,0.790389,se,Model 11: townhouses only,semi_elasticity,0.3915,0.2399,100*b/1 (per year),reported,0.06561065572911921,0.04020433284652796,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6319299708211754,616.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M7,6,Model 7,10,Size,living_area,A_structural,level,m2,0.007221,0.000264,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,4018.0,0.523332,se,Model 7: detached houses only,semi_elasticity,0.7221,0.026400000000000003,100*b/1 (X per m2->m2),reported,0.39661194654237797,0.014500145947540202,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),27.352272727272727,4008.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M8,6,Model 8,10,Size,living_area,A_structural,level,m2,0.010776,0.00046,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,4990.0,0.471448,se,Model 8: semi-detached houses only,semi_elasticity,1.0776000000000001,0.046,100*b/1 (X per m2->m2),reported,0.31505402741777866,0.01344885417707667,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.42608695652174,4980.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M9,6,Model 9,10,Size,living_area,A_structural,level,m2,0.008178,0.000864,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,3571.0,0.379724,se,Model 9: terraced houses only,semi_elasticity,0.8178,0.08639999999999999,100*b/1 (X per m2->m2),reported,0.15665769982744557,0.016550776797617142,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.465277777777777,3561.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M10,6,Model 10,10,Size,living_area,A_structural,level,m2,0.007011,0.001226,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,520.0,0.492908,se,Model 10: apartments only,semi_elasticity,0.7011,0.12260000000000001,100*b/1 (X per m2->m2),reported,0.2454757778668499,0.04292587414987278,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.718597063621533,510.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M11,6,Model 11,10,Size,living_area,A_structural,level,m2,0.01103,0.000841,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,626.0,0.790389,se,Model 11: townhouses only,semi_elasticity,1.103,0.0841,100*b/1 (X per m2->m2),reported,0.4672110112518819,0.03562325117523415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.115338882282996,616.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M7,6,Model 7,10,Parking onsite,parking,A_structural,binary,binary,-0.011208,0.043728,,,,,,high,,ln property price (GBP),log,OLS,4018.0,0.523332,se,Model 7: detached houses only,pct_premium,-1.2090385769979228,4.324063288320339,100*(exp(b - se^2/2) - 1),reported,-0.004048564775705302,0.015795471137762446,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2563117453347969,4008.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M8,6,Model 8,10,Parking onsite,parking,A_structural,binary,binary,0.063166,0.030378,,,**,,,high,,ln property price (GBP),log,OLS,4990.0,0.471448,se,Model 8: semi-detached houses only,pct_premium,6.471226458372237,3.2358756429921685,100*(exp(b - se^2/2) - 1),reported,0.029452426556998614,0.014164357628289015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.079333728356047,4980.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M9,6,Model 9,10,Parking onsite,parking,A_structural,binary,binary,0.027108,0.014338,,,*,,,high,,ln property price (GBP),log,OLS,3571.0,0.379724,se,Model 9: terraced houses only,pct_premium,2.73731562657189,1.4731990525085745,100*(exp(b - se^2/2) - 1),reported,0.03166686362010658,0.016749280307845955,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8906402566606222,3561.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T6-M11,6,Model 11,10,Parking onsite,parking,A_structural,binary,binary,0.091669,0.02917,,,***,,,high,,ln property price (GBP),log,OLS,626.0,0.790389,se,Model 11: townhouses only,pct_premium,9.553579659137522,3.1970377913461543,100*(exp(b - se^2/2) - 1),reported,0.12561513982083203,0.03997200393343082,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.142577991086733,616.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M12,7,Model 12,11,Age,age,A_structural,level,years,0.001584,0.000491,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.67557,se,Model 12 (MDM): adds ASB x multiple deprivation rank interaction,semi_elasticity,0.15839999999999999,0.0491,100*b/1 (per year),reported,0.026771291838238592,0.008298424427130777,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.226069246435845,14511.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M13,7,Model 13,11,Age,age,A_structural,level,years,0.002053,0.0005,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.67557,se,Model 13 (Income): adds ASB x income rank interaction (column printed identical to Model 12),semi_elasticity,0.2053,0.05,100*b/1 (per year),reported,0.03406576400245073,0.008296581588516982,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.106,14511.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M14,7,Model 14,11,Age,age,A_structural,level,years,0.002412,0.00049,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.674713,se,Model 14 (Employment): adds ASB x employment rank interaction,semi_elasticity,0.2412,0.049,100*b/1 (per year),reported,0.04082914277035956,0.008294477594310191,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.922448979591837,14511.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M15,7,Model 15,11,Age,age,A_structural,level,years,0.001954,0.00049,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.675966,se,Model 15 (Education): adds ASB x education rank interaction,semi_elasticity,0.1954,0.049,100*b/1 (per year),reported,0.03308582536707044,0.008296854877105688,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.9877551020408166,14511.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M16,7,Model 16,11,Age,age,A_structural,level,years,0.000785,0.000122,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.651339,se,Model 16 (Access): adds ASB x access-to-services rank interaction,semi_elasticity,0.0785,0.012199999999999999,100*b/1 (per year),reported,0.05333870739016917,0.008289582549809731,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.434426229508197,14511.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M17,7,Model 17,11,Age,age,A_structural,level,years,0.002597,0.000505,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.654687,se,Model 17 (Crime): adds ASB x crime rank interaction,semi_elasticity,0.2597,0.0505,100*b/1 (per year),reported,0.04265171643602745,0.008293845514129329,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.142574257425742,14511.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M12,7,Model 12,11,Size,living_area,A_structural,level,m2,0.007935,0.000167,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,14521.0,0.67557,se,Model 12 (MDM): adds ASB x multiple deprivation rank interaction,semi_elasticity,0.7935,0.0167,100*b/1 (X per m2->m2),reported,0.36692822505647293,0.007722370962121108,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.514970059880234,14511.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M13,7,Model 13,11,Size,living_area,A_structural,level,m2,0.008168,0.00017,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,14521.0,0.67557,se,Model 13 (Income): adds ASB x income rank interaction (column printed identical to Model 12),semi_elasticity,0.8168,0.017,100*b/1 (X per m2->m2),reported,0.3704759417421579,0.007710689286993985,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),48.047058823529404,14511.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M14,7,Model 14,11,Size,living_area,A_structural,level,m2,0.008002,0.000168,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,14521.0,0.674713,se,Model 14 (Employment): adds ASB x employment rank interaction,semi_elasticity,0.8002,0.0168,100*b/1 (X per m2->m2),reported,0.3677029132144088,0.007719831219697658,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.63095238095239,14511.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M15,7,Model 15,11,Size,living_area,A_structural,level,m2,0.007704,0.000168,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,14521.0,0.675966,se,Model 15 (Education): adds ASB x education rank interaction,semi_elasticity,0.7704,0.0168,100*b/1 (X per m2->m2),reported,0.3557717743505355,0.007758262992067751,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),45.85714285714286,14511.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M16,7,Model 16,11,Size,living_area,A_structural,level,m2,0.005029,6.64e-05,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,14521.0,0.651339,se,Model 16 (Access): adds ASB x access-to-services rank interaction,semi_elasticity,0.5029,0.00664,100*b/1 (X per m2->m2),reported,0.5322683826430585,0.007027763095545652,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),75.73795180722891,14511.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M17,7,Model 17,11,Size,living_area,A_structural,level,m2,0.008321,0.00017,,,***,,,high,property size in square metres,ln property price (GBP),log,OLS,14521.0,0.654687,se,Model 17 (Crime): adds ASB x crime rank interaction,semi_elasticity,0.8321000000000001,0.017,100*b/1 (X per m2->m2),reported,0.3764399490305086,0.007690757280998252,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),48.94705882352941,14511.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M12,7,Model 12,11,Parking onsite,parking,A_structural,binary,binary,0.037509,0.010415,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.67557,se,Model 12 (MDM): adds ASB x multiple deprivation rank interaction,pct_premium,3.8165033469359955,1.0813075266846683,100*(exp(b - se^2/2) - 1),reported,0.02988364265065943,0.008297692239372363,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.60144023043687,14511.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M13,7,Model 13,11,Parking onsite,parking,A_structural,binary,binary,0.037509,0.010415,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.67557,se,Model 13 (Income): adds ASB x income rank interaction (column printed identical to Model 12),pct_premium,3.8165033469359955,1.0813075266846683,100*(exp(b - se^2/2) - 1),reported,0.02988364265065943,0.008297692239372363,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.60144023043687,14511.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M14,7,Model 14,11,Parking onsite,parking,A_structural,binary,binary,0.055876,0.010401,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.674713,se,Model 14 (Employment): adds ASB x employment rank interaction,pct_premium,5.740935251203605,1.0998709583994504,100*(exp(b - se^2/2) - 1),reported,0.044552296566252245,0.008293156929371995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.372175752331507,14511.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M15,7,Model 15,11,Parking onsite,parking,A_structural,binary,binary,0.036991,0.010409,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.675966,se,Model 15 (Education): adds ASB x education rank interaction,pct_premium,3.762746806293471,1.0801249442221945,100*(exp(b - se^2/2) - 1),reported,0.029488283145845808,0.008297789712770917,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.553751561149006,14511.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M16,7,Model 16,11,Parking onsite,parking,A_structural,binary,binary,0.086069,0.010858,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.651339,se,Model 16 (Access): adds ASB x access-to-services rank interaction,pct_premium,8.981728300403446,1.183393362598725,100*(exp(b - se^2/2) - 1),reported,0.06566138096704442,0.008283485047347688,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.926782096150305,14511.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T7-M17,7,Model 17,11,Parking onsite,parking,A_structural,binary,binary,0.054918,0.010735,,,***,,,high,,ln property price (GBP),log,OLS,14521.0,0.654687,se,Model 17 (Crime): adds ASB x crime rank interaction,pct_premium,5.6393110653516265,1.134103349566519,100*(exp(b - se^2/2) - 1),reported,0.04242996855770863,0.008293923895025349,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.11578947368421,14511.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,ols,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T8-M18,8,Model 18,12,Age,age,A_structural,level,years,0.001332,5.1e-05,,,***,,,high,,ln property price (GBP),log,spatial_lag,13421.0,0.693112,se,"Model 18 (SLM 1): spatial lag model, reformulation of Model 1 (SL term 1.418***)",semi_elasticity,0.1332,0.0051,100*b/1 (per year),reported,0.22000385804726671,0.008423571141449399,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.117647058823533,13411.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,spatial,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T8-M19,8,Model 19,12,Age,age,A_structural,level,years,0.002344,7e-06,,,***,,,high,,ln property price (GBP),log,spatial_lag,13421.0,0.71551,se,"Model 19 (SLM 2): spatial lag model, reformulation of Model 2 (SL term 1.219***)",semi_elasticity,0.23440000000000003,0.0007,100*b/1 (per year),reported,0.945078700961426,0.002822334004577637,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),334.8571428571429,13411.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,spatial,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T8-M20,8,Model 20,12,Age,age,A_structural,level,years,0.002423,0.000126,,,***,,,high,,ln property price (GBP),log,IV,13421.0,0.703323,se,"Model 20 (2SLS): ASB instrumented by 2010 ASB, with spatial lag term (SL term 1.218***)",semi_elasticity,0.2423,0.0126,100*b/1 (per year),reported,0.1638119838038374,0.008518493586167361,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.230158730158728,13411.0,years,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,iv,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T8-M18,8,Model 18,12,Size,living_area,A_structural,level,m2,0.004137,6.23e-05,,,***,,,high,property size in square metres,ln property price (GBP),log,spatial_lag,13421.0,0.693112,se,"Model 18 (SLM 1): spatial lag model, reformulation of Model 1 (SL term 1.418***)",semi_elasticity,0.4137,0.006229999999999999,100*b/1 (X per m2->m2),reported,0.4974355718564769,0.007490992537263357,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),66.40449438202248,13411.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,spatial,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T8-M19,8,Model 19,12,Size,living_area,A_structural,level,m2,0.006478,0.000154,,,***,,,high,property size in square metres,ln property price (GBP),log,spatial_lag,13421.0,0.71551,se,"Model 19 (SLM 2): spatial lag model, reformulation of Model 2 (SL term 1.219***)",semi_elasticity,0.6478,0.0154,100*b/1 (X per m2->m2),reported,0.3414112083304778,0.008116289917087616,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.064935064935064,13411.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,spatial,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T8-M20,8,Model 20,12,Size,living_area,A_structural,level,m2,0.005343,0.000243,,,***,,,high,property size in square metres,ln property price (GBP),log,IV,13421.0,0.703323,se,"Model 20 (2SLS): ASB instrumented by 2010 ASB, with spatial lag term (SL term 1.218***)",semi_elasticity,0.5343,0.0243,100*b/1 (X per m2->m2),reported,0.1865340466829433,0.008483581011408427,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.98765432098765,13411.0,m2,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,iv,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T8-M18,8,Model 18,12,Parking onsite,parking,A_structural,binary,binary,0.077516,0.019778,,,**,,,high,,ln property price (GBP),log,spatial_lag,13421.0,0.693112,se,"Model 18 (SLM 1): spatial lag model, reformulation of Model 1 (SL term 1.418***)",pct_premium,8.038819390888552,2.1372097344387297,100*(exp(b - se^2/2) - 1),reported,0.03382437825551439,0.00863019961217766,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.919304277480028,13411.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,spatial,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T8-M19,8,Model 19,12,Parking onsite,parking,A_structural,binary,binary,0.075456,0.006855,,,***,,,high,,ln property price (GBP),log,spatial_lag,13421.0,0.71551,se,"Model 19 (SLM 2): spatial lag model, reformulation of Model 2 (SL term 1.219***)",pct_premium,7.835044144600567,0.739226595914922,100*(exp(b - se^2/2) - 1),reported,0.09462430398099836,0.008596395300436597,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.007439824945294,13411.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,spatial,journal,True,True,False
cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1,cc4e9f217dbac07b4b73c8b633af8dfec0f75eb1:T8-M20,8,Model 20,12,Parking onsite,parking,A_structural,binary,binary,0.043993,0.009233,,,***,,,high,,ln property price (GBP),log,IV,13421.0,0.703323,se,"Model 20 (2SLS): ASB instrumented by 2010 ASB, with spatial lag term (SL term 1.218***)",pct_premium,4.493049981970709,0.9648254544666806,100*(exp(b - se^2/2) - 1),reported,0.041109564249281305,0.00862784094545983,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.764756850427813,13411.0,binary,,2025.0,United Kingdom,Europe,High income,2018.0,2022.0,mixed,transaction,journal,True,True,unknown,,2020.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c1,6,(1) 2SLS,30,Living area,living_area,A_structural,level,1000 sqft,0.32,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.3444451333347111,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.3940635690280088,0.003694345959637582,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),106.66666666666667,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c2,6,(2) Q: 0.05,30,Living area,living_area,A_structural,level,1000 sqft,0.286,0.006,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.30784783791789805,0.006458346250025833,100*b/92.903 (X per 1000sqft->m2),reported,0.1881779320619847,0.003947788784517162,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.666666666666664,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c3,6,(3) Q: 0.25,30,Living area,living_area,A_structural,level,1000 sqft,0.307,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.3304520497929885,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.3804131357949758,0.0037173922064655624,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),102.33333333333333,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c4,6,(4) Q: 0.50,30,Living area,living_area,A_structural,level,1000 sqft,0.321,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.34552152437638206,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.3951030334703139,0.003692551714675831,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),107.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c5,6,(5) Q: 0.75,30,Living area,living_area,A_structural,level,1000 sqft,0.341,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.36704934520980154,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.3241666022833246,0.003802540789247209,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),85.25,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c6,6,(6) Q: 0.95,30,Living area,living_area,A_structural,level,1000 sqft,0.348,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.37458408250149827,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.2694192561544632,0.0038709663240583804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),69.6,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c1,6,(1) 2SLS,30,Lot area,lot_size,A_structural,level,1000 sqft,0.021,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.022604211875090416,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.08411244939884005,0.004005354733278097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c2,6,(2) Q: 0.05,30,Lot area,lot_size,A_structural,level,1000 sqft,0.008,0.002,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.008611128333367779,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.01607631859730484,0.00401907964932621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c3,6,(3) Q: 0.25,30,Lot area,lot_size,A_structural,level,1000 sqft,0.013,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.013993083541722639,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.05218359172933882,0.004014122440718371,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c4,6,(4) Q: 0.50,30,Lot area,lot_size,A_structural,level,1000 sqft,0.02,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.021527820833419444,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.08013345319170002,0.004006672659585001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c5,6,(5) Q: 0.75,30,Lot area,lot_size,A_structural,level,1000 sqft,0.026,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.027986167083445278,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.10394347012419862,0.003997825774007639,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c6,6,(6) Q: 0.95,30,Lot area,lot_size,A_structural,level,1000 sqft,0.038,0.002,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.04090285958349694,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.0761506225926853,0.004007927504878174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c1,6,(1) 2SLS,30,Bedrooms,bedrooms,A_structural,level,count,-0.019,0.002,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,-1.9,0.2,100*b/1 (per unit count),reported,-0.03815838070142761,0.004016671652781854,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c2,6,(2) Q: 0.05,30,Bedrooms,bedrooms,A_structural,level,count,-0.009,0.003,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.8999999999999999,0.3,100*b/1 (per unit count),reported,-0.012057920667875591,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.9999999999999996,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c3,6,(3) Q: 0.25,30,Bedrooms,bedrooms,A_structural,level,count,-0.012,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,-1.2,0.2,100*b/1 (per unit count),reported,-0.024110583627583122,0.0040184306045971865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c4,6,(4) Q: 0.50,30,Bedrooms,bedrooms,A_structural,level,count,-0.012,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,-1.2,0.1,100*b/1 (per unit count),reported,-0.04817917426179949,0.004014931188483291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c5,6,(5) Q: 0.75,30,Bedrooms,bedrooms,A_structural,level,count,-0.014,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,-1.4000000000000001,0.1,100*b/1 (per unit count),reported,-0.056185493585738,0.004013249541838429,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c6,6,(6) Q: 0.95,30,Bedrooms,bedrooms,A_structural,level,count,-0.018,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,-1.7999999999999998,0.3,100*b/1 (per unit count),reported,-0.02411058362758312,0.0040184306045971865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.999999999999999,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c1,6,(1) 2SLS,30,Bathrooms (Full),bathrooms,A_structural,level,count,0.003,0.002,,,,,,high,Number of full bathrooms,Log (Sale Price),log,IV,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.3,0.2,100*b/1 (per unit count),reported,0.006029289075079203,0.004019526050052801,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c2,6,(2) Q: 0.05,30,Bathrooms (Full),bathrooms,A_structural,level,count,-0.01,0.004,,,**,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-1.0,0.4,100*b/1 (per unit count),reported,-0.010048490431704502,0.0040193961726818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c3,6,(3) Q: 0.25,30,Bathrooms (Full),bathrooms,A_structural,level,count,0.002,0.003,,,,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.2,0.3,100*b/1 (per unit count),reported,0.0026797231195861745,0.004019584679379263,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6666666666666666,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c4,6,(4) Q: 0.50,30,Bathrooms (Full),bathrooms,A_structural,level,count,0.005,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.5,0.2,100*b/1 (per unit count),reported,0.010048490431704502,0.0040193961726818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c5,6,(5) Q: 0.75,30,Bathrooms (Full),bathrooms,A_structural,level,count,0.004,0.002,,,**,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.4,0.2,100*b/1 (per unit count),reported,0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c6,6,(6) Q: 0.95,30,Bathrooms (Full),bathrooms,A_structural,level,count,0.01,0.003,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,1.0,0.3,100*b/1 (per unit count),reported,0.013397461175148244,0.004019238352544473,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3333333333333335,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c1,6,(1) 2SLS,30,One story,storeys,A_structural,binary,binary,-0.093,0.007,,,***,,,high,One-story property =1,Log (Sale Price),log,IV,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-8.882882367114696,0.6378354502072984,100*(exp(b - se^2/2) - 1),reported,-0.05332725730017737,0.004013879581733781,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.285714285714285,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c2,6,(2) Q: 0.05,30,One story,storeys,A_structural,binary,binary,-0.062,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-6.012886167156795,0.46994144339554444,100*(exp(b - se^2/2) - 1),reported,-0.04978123090037987,0.004014615395191924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.4,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c3,6,(3) Q: 0.25,30,One story,storeys,A_structural,binary,binary,-0.076,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-7.318564707117725,0.18536324131187645,100*(exp(b - se^2/2) - 1),reported,-0.15099350992814012,0.003973513419161582,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-38.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c4,6,(4) Q: 0.50,30,One story,storeys,A_structural,binary,binary,-0.081,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-7.781045841766621,0.2766581074333824,100*(exp(b - se^2/2) - 1),reported,-0.10789560755340154,0.003996133613088947,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-27.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c5,6,(5) Q: 0.75,30,One story,storeys,A_structural,binary,binary,-0.087,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,-8.332473771920556,0.18333541912663046,100*(exp(b - se^2/2) - 1),reported,-0.17223941045694194,0.003959526677171079,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-43.49999999999999,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c6,6,(6) Q: 0.95,30,One story,storeys,A_structural,binary,binary,-0.099,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-9.426136780946702,0.27172281240706453,100*(exp(b - se^2/2) - 1),reported,-0.13149497712968528,0.003984696276657129,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-33.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c1,6,(1) 2SLS,30,Renovated,renovation,A_structural,binary,binary,-0.046,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,IV,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-4.501581610018701,1.0505461584097862,100*(exp(b - se^2/2) - 1),reported,-0.016806858424771982,0.004019031362445475,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.181818181818182,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c2,6,(2) Q: 0.05,30,Renovated,renovation,A_structural,binary,binary,-0.275,0.017,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-24.05376270171916,1.2912726094824465,100*(exp(b - se^2/2) - 1),reported,-0.06488590330233307,0.00401112856778059,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.176470588235293,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,True
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c3,6,(3) Q: 0.25,30,Renovated,renovation,A_structural,binary,binary,-0.107,0.012,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-10.153901852922708,1.0782308075883666,100*(exp(b - se^2/2) - 1),reported,-0.03581842648102667,0.004017019792264673,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.916666666666666,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c4,6,(4) Q: 0.50,30,Renovated,renovation,A_structural,binary,binary,-0.006,0.006,,,,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-0.5999928108387786,0.5964107784323611,100*(exp(b - se^2/2) - 1),reported,-0.004019566639313255,0.004019566639313255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c5,6,(5) Q: 0.75,30,Renovated,renovation,A_structural,binary,binary,0.025,0.005,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,2.5302304165524703,0.5126575602622144,100*(exp(b - se^2/2) - 1),reported,0.020093937701409933,0.004018787540281986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c6,6,(6) Q: 0.95,30,Renovated,renovation,A_structural,binary,binary,0.047,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,4.805859961626191,1.1529342099876212,100*(exp(b - se^2/2) - 1),reported,0.01717211831823326,0.004019006414905655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.272727272727273,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c1,6,(1) 2SLS,30,Fireplace,fireplace,B_interior,binary,binary,0.04,0.005,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,4.079776413902381,0.5204053870961941,100*(exp(b - se^2/2) - 1),reported,0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c2,6,(2) Q: 0.05,30,Fireplace,fireplace,B_interior,binary,binary,0.062,0.008,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,6.392829847774539,0.851169875782427,100*(exp(b - se^2/2) - 1),reported,0.031136788579101626,0.00401765013923892,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.75,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c3,6,(3) Q: 0.25,30,Fireplace,fireplace,B_interior,binary,binary,0.041,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,4.185002184335218,0.2083704211090959,100*(exp(b - se^2/2) - 1),reported,0.08212344218496902,0.004006021569998489,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c4,6,(4) Q: 0.50,30,Fireplace,fireplace,B_interior,binary,binary,0.029,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,2.942407976296235,0.10294245944751308,100*(exp(b - se^2/2) - 1),reported,0.11578437869023656,0.00399256478242195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c5,6,(5) Q: 0.75,30,Fireplace,fireplace,B_interior,binary,binary,0.02,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,2.019929962611622,0.20404026800535116,100*(exp(b - se^2/2) - 1),reported,0.04016355772598999,0.004016355772598999,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c6,6,(6) Q: 0.95,30,Fireplace,fireplace,B_interior,binary,binary,0.014,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,1.4093895505694842,0.3042295376815477,100*(exp(b - se^2/2) - 1),reported,0.018754829870992466,0.004018892115212671,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.666666666666667,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c1,6,(1) 2SLS,30,Lake/Mountain view,view,E_environment,binary,binary,0.105,0.006,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,IV,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,11.069061774465293,0.6664263662134231,100*(exp(b - se^2/2) - 1),reported,0.07016959434880864,0.004009691105646207,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c2,6,(2) Q: 0.05,30,Lake/Mountain view,view,E_environment,binary,binary,0.065,0.007,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,6.713287930837364,0.7470113170689349,100*(exp(b - se^2/2) - 1),reported,0.03729887657665404,0.004016802092870434,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.285714285714286,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c3,6,(3) Q: 0.25,30,Lake/Mountain view,view,E_environment,binary,binary,0.069,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,7.142763769295879,0.42857448365933853,100*(exp(b - se^2/2) - 1),reported,0.06917200251825996,0.004009971160478838,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.25,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c4,6,(4) Q: 0.50,30,Lake/Mountain view,view,E_environment,binary,binary,0.081,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,8.436222163428763,0.4337483586267042,100*(exp(b - se^2/2) - 1),reported,0.08112856896415577,0.004006349084649667,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.25,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c5,6,(5) Q: 0.75,30,Lake/Mountain view,view,E_environment,binary,binary,0.104,0.006,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,10.958048228714823,0.6657602729493495,100*(exp(b - se^2/2) - 1),reported,0.06950455633494922,0.0040098782500932245,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.333333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T6-c6,6,(6) Q: 0.95,30,Lake/Mountain view,view,E_environment,binary,binary,0.176,0.008,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Without spatial autocorrelation adjustment; 911 calls as IV for number of crimes; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,19.23999012433144,0.9539504469205357,100*(exp(b - se^2/2) - 1),reported,0.08808742611158363,0.004003973914162892,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c1,7 Panel A,(1) 2SLS,34,Living area,living_area,A_structural,level,1000 sqft,0.261,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.28093806187612375,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.25369799088088457,0.00388809181426643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),65.25,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c2,7 Panel A,(2) Q: 0.05,34,Living area,living_area,A_structural,level,1000 sqft,0.241,0.006,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.25941024104270427,0.006458346250025833,100*b/92.903 (X per 1000sqft->m2),reported,0.15938982626211692,0.0039682114422103796,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.166666666666664,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c3,7 Panel A,(3) Q: 0.25,34,Living area,living_area,A_structural,level,1000 sqft,0.252,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.271250542501085,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.31990310072026185,0.003808370246669784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),84.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c4,7 Panel A,(4) Q: 0.50,34,Living area,living_area,A_structural,level,1000 sqft,0.267,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.2873964081261496,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.33683860199528165,0.0037847033932054117,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),89.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c5,7 Panel A,(5) Q: 0.75,34,Living area,living_area,A_structural,level,1000 sqft,0.286,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.30784783791789805,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.4983425486371538,0.0034849129275325453,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),142.99999999999997,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c6,7 Panel A,(6) Q: 0.95,34,Living area,living_area,A_structural,level,1000 sqft,0.299,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.3218409214596207,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.233714961155575,0.00390827694240092,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),59.8,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c1,7 Panel A,(1) 2SLS,34,Lot area,lot_size,A_structural,level,1000 sqft,0.018,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.019375038750077497,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.07216414361374496,0.0040091190896524975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c2,7 Panel A,(2) Q: 0.05,34,Lot area,lot_size,A_structural,level,1000 sqft,0.008,0.002,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.008611128333367779,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.01607631859730484,0.00401907964932621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c4,7 Panel A,(4) Q: 0.50,34,Lot area,lot_size,A_structural,level,1000 sqft,0.018,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.019375038750077497,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.07216414361374496,0.0040091190896524975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c5,7 Panel A,(5) Q: 0.75,34,Lot area,lot_size,A_structural,level,1000 sqft,0.022,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.023680602916761384,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.08808742611158363,0.004003973914162892,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c6,7 Panel A,(6) Q: 0.95,34,Lot area,lot_size,A_structural,level,1000 sqft,0.034,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.03659729541681306,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.13540766833933668,0.003982578480568726,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c1,7 Panel A,(1) 2SLS,34,Bedrooms,bedrooms,A_structural,level,count,-0.007,0.001,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,-0.7000000000000001,0.1,100*b/1 (per unit count),reported,-0.028126062258739027,0.004018008894105575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c2,7 Panel A,(2) Q: 0.05,34,Bedrooms,bedrooms,A_structural,level,count,-0.0,0.004,,,,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.0,0.4,100*b/1 (per unit count),reported,-0.0,0.004019599111606953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c3,7 Panel A,(3) Q: 0.25,34,Bedrooms,bedrooms,A_structural,level,count,-0.002,0.001,,,*,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,-0.2,0.1,100*b/1 (per unit count),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c4,7 Panel A,(4) Q: 0.50,34,Bedrooms,bedrooms,A_structural,level,count,-0.002,0.001,,,*,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,-0.2,0.1,100*b/1 (per unit count),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c5,7 Panel A,(5) Q: 0.75,34,Bedrooms,bedrooms,A_structural,level,count,-0.002,0.001,,,*,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,-0.2,0.1,100*b/1 (per unit count),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c6,7 Panel A,(6) Q: 0.95,34,Bedrooms,bedrooms,A_structural,level,count,-0.008,0.004,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,-0.8,0.4,100*b/1 (per unit count),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c1,7 Panel A,(1) 2SLS,34,Bathrooms (Full),bathrooms,A_structural,level,count,0.008,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,IV,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.8,0.1,100*b/1 (per unit count),reported,0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c2,7 Panel A,(2) Q: 0.05,34,Bathrooms (Full),bathrooms,A_structural,level,count,-0.007,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.7000000000000001,0.2,100*b/1 (per unit count),reported,-0.01406720483080051,0.004019201380228717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c3,7 Panel A,(3) Q: 0.25,34,Bathrooms (Full),bathrooms,A_structural,level,count,0.006,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.6,0.2,100*b/1 (per unit count),reported,0.012057920667875593,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c4,7 Panel A,(4) Q: 0.50,34,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.8999999999999999,0.2,100*b/1 (per unit count),reported,0.0180852376545314,0.004018941701006978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c5,7 Panel A,(5) Q: 0.75,34,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.8999999999999999,0.2,100*b/1 (per unit count),reported,0.0180852376545314,0.004018941701006978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c6,7 Panel A,(6) Q: 0.95,34,Bathrooms (Full),bathrooms,A_structural,level,count,0.015,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,1.5,0.2,100*b/1 (per unit count),reported,0.030133303253020185,0.004017773767069358,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c1,7 Panel A,(1) 2SLS,34,One story,storeys,A_structural,binary,binary,-0.076,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,IV,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-7.319537857079251,0.4634081032796911,100*(exp(b - se^2/2) - 1),reported,-0.06098418693732637,0.004012117561666209,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.2,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c2,7 Panel A,(2) Q: 0.05,34,One story,storeys,A_structural,binary,binary,-0.053,0.007,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-5.164322254337739,0.6638660087376087,100*(exp(b - se^2/2) - 1),reported,-0.030420022776587435,0.004017738857285133,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.571428571428571,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c3,7 Panel A,(3) Q: 0.25,34,One story,storeys,A_structural,binary,binary,-0.064,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-6.19968764773936,0.1876009999061459,100*(exp(b - se^2/2) - 1),reported,-0.12757613078535945,0.003986754087042483,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-32.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c4,7 Panel A,(4) Q: 0.50,34,One story,storeys,A_structural,binary,binary,-0.067,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-6.480666905175569,0.18703904026735532,100*(exp(b - se^2/2) - 1),reported,-0.133452102765036,0.003983644858657791,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-33.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c5,7 Panel A,(5) Q: 0.75,34,One story,storeys,A_structural,binary,binary,-0.071,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,-6.8539970794329275,0.18629237842551843,100*(exp(b - se^2/2) - 1),reported,-0.1412647934828903,0.003979289957264516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-35.49999999999999,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c6,7 Panel A,(6) Q: 0.95,34,One story,storeys,A_structural,binary,binary,-0.084,0.004,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-8.057609932550235,0.3677725024380499,100*(exp(b - se^2/2) - 1),reported,-0.08411244939884005,0.004005354733278097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c1,7 Panel A,(1) 2SLS,34,Renovated,renovation,A_structural,binary,binary,-0.028,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,IV,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-2.767046091538816,1.0696272034813716,100*(exp(b - se^2/2) - 1),reported,-0.010231171304026659,0.004019388726581901,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.545454545454546,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c2,7 Panel A,(2) Q: 0.05,34,Renovated,renovation,A_structural,binary,binary,-0.264,0.012,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-23.20817524476095,0.9215682475880473,100*(exp(b - se^2/2) - 1),reported,-0.08808742611158363,0.004003973914162892,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c3,7 Panel A,(3) Q: 0.25,34,Renovated,renovation,A_structural,binary,binary,-0.102,0.012,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-9.703546411824693,1.083635462002652,100*(exp(b - se^2/2) - 1),reported,-0.03414666760248229,0.004017255012056741,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c4,7 Panel A,(4) Q: 0.50,34,Renovated,renovation,A_structural,binary,binary,0.021,0.006,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,2.120366980603605,0.6127332309825171,100*(exp(b - se^2/2) - 1),reported,0.01406720483080051,0.004019201380228717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c5,7 Panel A,(5) Q: 0.75,34,Renovated,renovation,A_structural,binary,binary,0.048,0.002,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,4.916855698525824,0.20983413106489415,100*(exp(b - se^2/2) - 1),reported,0.09602458544121234,0.004001024393383848,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c6,7 Panel A,(6) Q: 0.95,34,Renovated,renovation,A_structural,binary,binary,0.069,0.01,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,7.138263867716166,1.0714362091483463,100*(exp(b - se^2/2) - 1),reported,0.027724572450614767,0.004018053978349966,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.9,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c1,7 Panel A,(1) 2SLS,34,Fireplace,fireplace,B_interior,binary,binary,0.025,0.004,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,2.5306918036274606,0.41012604820977155,100*(exp(b - se^2/2) - 1),reported,0.025114570296134366,0.004018331247381499,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.25,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c2,7 Panel A,(2) Q: 0.05,34,Fireplace,fireplace,B_interior,binary,binary,0.044,0.007,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,4.495675313437175,0.7314876484219107,100*(exp(b - se^2/2) - 1),reported,0.025257990830651594,0.004018316723058209,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.285714285714286,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c3,7 Panel A,(3) Q: 0.25,34,Fireplace,fireplace,B_interior,binary,binary,0.025,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,2.5313069896238494,0.20506302410488578,100*(exp(b - se^2/2) - 1),reported,0.05018168551256579,0.004014534841005264,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c4,7 Panel A,(4) Q: 0.50,34,Fireplace,fireplace,B_interior,binary,binary,0.013,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,1.308284119210068,0.20261697347196184,100*(exp(b - se^2/2) - 1),reported,0.026118480976874945,0.004018227842596146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c5,7 Panel A,(5) Q: 0.75,34,Fireplace,fireplace,B_interior,binary,binary,0.01,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,1.004814698585399,0.20201003341683357,100*(exp(b - se^2/2) - 1),reported,0.020093937701409933,0.004018787540281986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c6,7 Panel A,(6) Q: 0.95,34,Fireplace,fireplace,B_interior,binary,binary,0.007,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,0.7022543219748156,0.20140491145336972,100*(exp(b - se^2/2) - 1),reported,0.01406720483080051,0.004019201380228717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c1,7 Panel A,(1) 2SLS,34,Lake/Mountain view,view,E_environment,binary,binary,0.063,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,IV,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,6.501352647901992,0.5325134196156527,100*(exp(b - se^2/2) - 1),reported,0.05058211592327567,0.004014453644704418,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.6,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c2,7 Panel A,(2) Q: 0.05,34,Lake/Mountain view,view,E_environment,binary,binary,0.037,0.006,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,3.7674342531887284,0.6226158125028943,100*(exp(b - se^2/2) - 1),reported,0.024779916366743225,0.0040183648162286315,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.166666666666666,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c3,7 Panel A,(3) Q: 0.25,34,Lake/Mountain view,view,E_environment,binary,binary,0.036,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,3.665118155011071,0.3109967539472771,100*(exp(b - se^2/2) - 1),reported,0.04817917426179948,0.004014931188483291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.999999999999998,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c4,7 Panel A,(4) Q: 0.50,34,Lake/Mountain view,view,E_environment,binary,binary,0.047,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,4.811729254122699,0.31443660272389673,100*(exp(b - se^2/2) - 1),reported,0.0628492224763869,0.004011652498492782,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.666666666666666,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c5,7 Panel A,(5) Q: 0.75,34,Lake/Mountain view,view,E_environment,binary,binary,0.059,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,6.077046726231594,0.3182325722220477,100*(exp(b - se^2/2) - 1),reported,0.07880625986810323,0.00400709795939508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.666666666666664,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7A-c6,7 Panel A,(6) Q: 0.95,34,Lake/Mountain view,view,E_environment,binary,binary,0.107,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial autocorrelation adjustment (log WY spatial lag of neighbour prices as regressor); 911 calls as IV; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,11.292535104090362,0.4451737017917303,100*(exp(b - se^2/2) - 1),reported,0.10690804517368448,0.00399656243639942,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.75,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c1,7 Panel B,(1) 2SLS,35,Living area,living_area,A_structural,level,1000 sqft,0.26,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; 2SLS; SE clustered by year and month",semi_elasticity,0.2798616708344528,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.2527881938022088,0.0038890491354185972,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),65.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c2,7 Panel B,(2) Q: 0.05,35,Living area,living_area,A_structural,level,1000 sqft,0.237,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.05; SE bootstrap",semi_elasticity,0.2551046768760204,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.18716216573631722,0.00394856889739066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.4,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c3,7 Panel B,(3) Q: 0.25,35,Living area,living_area,A_structural,level,1000 sqft,0.252,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.25; SE bootstrap",semi_elasticity,0.271250542501085,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.31990310072026185,0.003808370246669784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),84.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c4,7 Panel B,(4) Q: 0.50,35,Living area,living_area,A_structural,level,1000 sqft,0.266,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.50; SE bootstrap",semi_elasticity,0.28632001708447863,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.4714622721708457,0.0035448291140665095,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),133.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c5,7 Panel B,(5) Q: 0.75,35,Living area,living_area,A_structural,level,1000 sqft,0.285,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.75; SE bootstrap",semi_elasticity,0.30677144687622704,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.4970311166303093,0.0034879376605635747,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),142.49999999999997,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c6,7 Panel B,(6) Q: 0.95,35,Living area,living_area,A_structural,level,1000 sqft,0.299,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.95; SE bootstrap",semi_elasticity,0.3218409214596207,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.233714961155575,0.00390827694240092,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),59.8,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c1,7 Panel B,(1) 2SLS,35,Lot area,lot_size,A_structural,level,1000 sqft,0.018,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; 2SLS; SE clustered by year and month",semi_elasticity,0.019375038750077497,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.07216414361374496,0.0040091190896524975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c2,7 Panel B,(2) Q: 0.05,35,Lot area,lot_size,A_structural,level,1000 sqft,0.005,0.002,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.05; SE bootstrap",semi_elasticity,0.005381955208354861,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.010048490431704502,0.0040193961726818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c4,7 Panel B,(4) Q: 0.50,35,Lot area,lot_size,A_structural,level,1000 sqft,0.017,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.50; SE bootstrap",semi_elasticity,0.01829864770840653,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.0681742031339563,0.0040102472431739,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c5,7 Panel B,(5) Q: 0.75,35,Lot area,lot_size,A_structural,level,1000 sqft,0.022,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.75; SE bootstrap",semi_elasticity,0.023680602916761384,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.08808742611158363,0.004003973914162892,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c6,7 Panel B,(6) Q: 0.95,35,Lot area,lot_size,A_structural,level,1000 sqft,0.034,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.95; SE bootstrap",semi_elasticity,0.03659729541681306,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.13540766833933668,0.003982578480568726,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c1,7 Panel B,(1) 2SLS,35,Bedrooms,bedrooms,A_structural,level,count,-0.008,0.001,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; 2SLS; SE clustered by year and month",semi_elasticity,-0.8,0.1,100*b/1 (per unit count),reported,-0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c2,7 Panel B,(2) Q: 0.05,35,Bedrooms,bedrooms,A_structural,level,count,-0.003,0.004,,,,,,high,,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.05; SE bootstrap",semi_elasticity,-0.3,0.4,100*b/1 (per unit count),reported,-0.003014685634383684,0.0040195808458449115,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.75,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c3,7 Panel B,(3) Q: 0.25,35,Bedrooms,bedrooms,A_structural,level,count,-0.003,0.001,,,*,,,high,,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.25; SE bootstrap",semi_elasticity,-0.3,0.1,100*b/1 (per unit count),reported,-0.012057920667875593,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c4,7 Panel B,(4) Q: 0.50,35,Bedrooms,bedrooms,A_structural,level,count,-0.003,0.001,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.50; SE bootstrap",semi_elasticity,-0.3,0.1,100*b/1 (per unit count),reported,-0.012057920667875593,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c5,7 Panel B,(5) Q: 0.75,35,Bedrooms,bedrooms,A_structural,level,count,-0.003,0.001,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.75; SE bootstrap",semi_elasticity,-0.3,0.1,100*b/1 (per unit count),reported,-0.012057920667875593,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c6,7 Panel B,(6) Q: 0.95,35,Bedrooms,bedrooms,A_structural,level,count,-0.008,0.004,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.95; SE bootstrap",semi_elasticity,-0.8,0.4,100*b/1 (per unit count),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c1,7 Panel B,(1) 2SLS,35,Bathrooms (Full),bathrooms,A_structural,level,count,0.008,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,IV,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; 2SLS; SE clustered by year and month",semi_elasticity,0.8,0.1,100*b/1 (per unit count),reported,0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c2,7 Panel B,(2) Q: 0.05,35,Bathrooms (Full),bathrooms,A_structural,level,count,-0.006,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.05; SE bootstrap",semi_elasticity,-0.6,0.2,100*b/1 (per unit count),reported,-0.012057920667875593,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c3,7 Panel B,(3) Q: 0.25,35,Bathrooms (Full),bathrooms,A_structural,level,count,0.005,0.003,,,*,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.25; SE bootstrap",semi_elasticity,0.5,0.3,100*b/1 (per unit count),reported,0.006699181521223725,0.004019508912734235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6666666666666667,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c4,7 Panel B,(4) Q: 0.50,35,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.50; SE bootstrap",semi_elasticity,0.8999999999999999,0.1,100*b/1 (per unit count),reported,0.03615274262598033,0.004016971402886703,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c5,7 Panel B,(5) Q: 0.75,35,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.75; SE bootstrap",semi_elasticity,0.8999999999999999,0.2,100*b/1 (per unit count),reported,0.0180852376545314,0.004018941701006978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c6,7 Panel B,(6) Q: 0.95,35,Bathrooms (Full),bathrooms,A_structural,level,count,0.014,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.95; SE bootstrap",semi_elasticity,1.4000000000000001,0.2,100*b/1 (per unit count),reported,0.028126062258739027,0.004018008894105575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c1,7 Panel B,(1) 2SLS,35,One story,storeys,A_structural,binary,binary,-0.08,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,IV,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; 2SLS; SE clustered by year and month",pct_premium,-7.689519249557586,0.4615581731933179,100*(exp(b - se^2/2) - 1),reported,-0.06418098885674876,0.004011311803546798,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c2,7 Panel B,(2) Q: 0.05,35,One story,storeys,A_structural,binary,binary,-0.061,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.05; SE bootstrap",pct_premium,-5.9188520440986,0.47041161988800484,100*(exp(b - se^2/2) - 1),reported,-0.04898024983644974,0.0040147745767581755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.2,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c3,7 Panel B,(3) Q: 0.25,35,One story,storeys,A_structural,binary,binary,-0.068,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.25; SE bootstrap",pct_premium,-6.5741394941865146,0.18685209471544273,100*(exp(b - se^2/2) - 1),reported,-0.13540766833933668,0.003982578480568726,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-34.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c4,7 Panel B,(4) Q: 0.50,35,One story,storeys,A_structural,binary,binary,-0.07,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.50; SE bootstrap",pct_premium,-6.761037585680086,0.27971814597178446,100*(exp(b - se^2/2) - 1),reported,-0.09338082437105044,0.004002035330187876,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-23.333333333333336,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c5,7 Panel B,(5) Q: 0.75,35,One story,storeys,A_structural,binary,binary,-0.072,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.75; SE bootstrap",pct_premium,-6.947329156840376,0.2791592687433617,100*(exp(b - se^2/2) - 1),reported,-0.09602458544121233,0.004001024393383848,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-23.999999999999996,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c6,7 Panel B,(6) Q: 0.95,35,One story,storeys,A_structural,binary,binary,-0.085,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.95; SE bootstrap",pct_premium,-8.149184889452254,0.2755536853204372,100*(exp(b - se^2/2) - 1),reported,-0.11315714651535581,0.003993781641718441,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-28.333333333333336,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c1,7 Panel B,(1) 2SLS,35,Renovated,renovation,A_structural,binary,binary,-0.028,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,IV,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; 2SLS; SE clustered by year and month",pct_premium,-2.767046091538816,1.0696272034813716,100*(exp(b - se^2/2) - 1),reported,-0.010231171304026659,0.004019388726581901,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.545454545454546,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c2,7 Panel B,(2) Q: 0.05,35,Renovated,renovation,A_structural,binary,binary,-0.262,0.012,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.05; SE bootstrap",pct_premium,-23.05443790916064,0.923413228449091,100*(exp(b - se^2/2) - 1),reported,-0.08742521695147598,0.004004208409991267,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.833333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c3,7 Panel B,(3) Q: 0.25,35,Renovated,renovation,A_structural,binary,binary,-0.104,0.017,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.25; SE bootstrap",pct_premium,-9.890492022582098,1.5320830056160482,100*(exp(b - se^2/2) - 1),reported,-0.024583057215379938,0.004018384352514029,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.117647058823529,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c4,7 Panel B,(4) Q: 0.50,35,Renovated,renovation,A_structural,binary,binary,0.021,0.006,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.50; SE bootstrap",pct_premium,2.120366980603605,0.6127332309825171,100*(exp(b - se^2/2) - 1),reported,0.01406720483080051,0.004019201380228717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c5,7 Panel B,(5) Q: 0.75,35,Renovated,renovation,A_structural,binary,binary,0.048,0.003,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.75; SE bootstrap",pct_premium,4.916593406714442,0.3147511965973412,100*(exp(b - se^2/2) - 1),reported,0.06418098885674876,0.004011311803546798,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c6,7 Panel B,(6) Q: 0.95,35,Renovated,renovation,A_structural,binary,binary,0.07,0.009,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.95; SE bootstrap",pct_premium,7.246474555245452,0.9652573631287948,100*(exp(b - se^2/2) - 1),reported,0.0312482811925183,0.0040176361533237805,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.7777777777777795,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c1,7 Panel B,(1) 2SLS,35,Fireplace,fireplace,B_interior,binary,binary,0.025,0.004,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; 2SLS; SE clustered by year and month",pct_premium,2.5306918036274606,0.41012604820977155,100*(exp(b - se^2/2) - 1),reported,0.025114570296134366,0.004018331247381499,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.25,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c2,7 Panel B,(2) Q: 0.05,35,Fireplace,fireplace,B_interior,binary,binary,0.047,0.005,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.05; SE bootstrap",pct_premium,4.810890763642628,0.5240610045398278,100*(exp(b - se^2/2) - 1),reported,0.03775728919950944,0.004016732893564834,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.4,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c3,7 Panel B,(3) Q: 0.25,35,Fireplace,fireplace,B_interior,binary,binary,0.026,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.25; SE bootstrap",pct_premium,2.633889579359794,0.2052681896946884,100*(exp(b - se^2/2) - 1),reported,0.05218359172933882,0.004014122440718371,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c4,7 Panel B,(4) Q: 0.50,35,Fireplace,fireplace,B_interior,binary,binary,0.014,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.50; SE bootstrap",pct_premium,1.4096430743602673,0.20281969178769846,100*(exp(b - se^2/2) - 1),reported,0.028126062258739027,0.004018008894105575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c5,7 Panel B,(5) Q: 0.75,35,Fireplace,fireplace,B_interior,binary,binary,0.01,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.75; SE bootstrap",pct_premium,1.004814698585399,0.20201003341683357,100*(exp(b - se^2/2) - 1),reported,0.020093937701409933,0.004018787540281986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c6,7 Panel B,(6) Q: 0.95,35,Fireplace,fireplace,B_interior,binary,binary,0.006,0.003,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.95; SE bootstrap",pct_premium,0.6013508983088611,0.3018054108162195,100*(exp(b - se^2/2) - 1),reported,0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c1,7 Panel B,(1) 2SLS,35,Lake/Mountain view,view,E_environment,binary,binary,0.063,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,IV,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; 2SLS; SE clustered by year and month",pct_premium,6.501352647901992,0.5325134196156527,100*(exp(b - se^2/2) - 1),reported,0.05058211592327567,0.004014453644704418,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.6,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c2,7 Panel B,(2) Q: 0.05,35,Lake/Mountain view,view,E_environment,binary,binary,0.036,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.05; SE bootstrap",pct_premium,3.6642888373831006,0.5183279232454618,100*(exp(b - se^2/2) - 1),reported,0.028929000846614854,0.004017916784252063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.199999999999999,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c3,7 Panel B,(3) Q: 0.25,35,Lake/Mountain view,view,E_environment,binary,binary,0.037,0.002,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.25; SE bootstrap",pct_premium,3.7690945454190716,0.20753860416763142,100*(exp(b - se^2/2) - 1),reported,0.07415782749058782,0.004008531215707449,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c4,7 Panel B,(4) Q: 0.50,35,Lake/Mountain view,view,E_environment,binary,binary,0.046,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.50; SE bootstrap",pct_premium,4.706603439515589,0.4188297643827749,100*(exp(b - se^2/2) - 1),reported,0.04617608189162238,0.004015311468836729,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c5,7 Panel B,(5) Q: 0.75,35,Lake/Mountain view,view,E_environment,binary,binary,0.06,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.75; SE bootstrap",pct_premium,6.183176829165116,0.3185509639636079,100*(exp(b - se^2/2) - 1),reported,0.08013345319170002,0.004006672659585001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7B-c6,7 Panel B,(6) Q: 0.95,35,Lake/Mountain view,view,E_environment,binary,binary,0.107,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,"With spatial lag of neighbour prices; violent crimes (exogenous, OLS/quantile); year + month dummies; quantile regression at tau=0.95; SE bootstrap",pct_premium,11.292535104090362,0.4451737017917303,100*(exp(b - se^2/2) - 1),reported,0.10690804517368448,0.00399656243639942,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.75,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c1,7 Panel C,(1) 2SLS,35,Living area,living_area,A_structural,level,1000 sqft,0.268,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.28847279916782054,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.33795631871264253,0.00378309311991764,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),89.33333333333334,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c2,7 Panel C,(2) Q: 0.05,35,Living area,living_area,A_structural,level,1000 sqft,0.252,0.006,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.271250542501085,0.006458346250025833,100*b/92.903 (X per 1000sqft->m2),reported,0.1664675615205028,0.0039635133695357806,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c3,7 Panel C,(3) Q: 0.25,35,Living area,living_area,A_structural,level,1000 sqft,0.259,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.27878527979278184,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.4617283980831373,0.003565470255468242,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),129.5,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c4,7 Panel C,(4) Q: 0.50,35,Living area,living_area,A_structural,level,1000 sqft,0.276,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.29708392750118834,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.3468464527220603,0.003770070138283264,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),92.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c5,7 Panel C,(5) Q: 0.75,35,Living area,living_area,A_structural,level,1000 sqft,0.288,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.31000062000123996,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.5009551799969574,0.003478855416645538,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),144.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c6,7 Panel C,(6) Q: 0.95,35,Living area,living_area,A_structural,level,1000 sqft,0.302,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.3250700945846336,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.23593001210574505,0.003906126028240812,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),60.4,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c1,7 Panel C,(1) 2SLS,35,Lot area,lot_size,A_structural,level,1000 sqft,0.013,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.013993083541722639,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.05218359172933882,0.004014122440718371,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c2,7 Panel C,(2) Q: 0.05,35,Lot area,lot_size,A_structural,level,1000 sqft,-0.0,0.001,,,,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.0,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,-0.0,0.004019599111606953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c4,7 Panel C,(4) Q: 0.50,35,Lot area,lot_size,A_structural,level,1000 sqft,0.012,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.012916692500051665,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.04817917426179949,0.004014931188483291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c5,7 Panel C,(5) Q: 0.75,35,Lot area,lot_size,A_structural,level,1000 sqft,0.018,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.019375038750077497,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.07216414361374496,0.0040091190896524975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c6,7 Panel C,(6) Q: 0.95,35,Lot area,lot_size,A_structural,level,1000 sqft,0.03,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.032291731250129165,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.11972065843265513,0.003990688614421837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c1,7 Panel C,(1) 2SLS,35,Bedrooms,bedrooms,A_structural,level,count,-0.011,0.002,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,-1.0999999999999999,0.2,100*b/1 (per unit count),reported,-0.022102394450125195,0.004018617172750035,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c2,7 Panel C,(2) Q: 0.05,35,Bedrooms,bedrooms,A_structural,level,count,-0.009,0.004,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.8999999999999999,0.4,100*b/1 (per unit count),reported,-0.009043728139602736,0.004019434728712327,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.25,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c3,7 Panel C,(3) Q: 0.25,35,Bedrooms,bedrooms,A_structural,level,count,-0.007,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,-0.7000000000000001,0.1,100*b/1 (per unit count),reported,-0.028126062258739027,0.004018008894105575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c4,7 Panel C,(4) Q: 0.50,35,Bedrooms,bedrooms,A_structural,level,count,-0.006,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,-0.6,0.1,100*b/1 (per unit count),reported,-0.024110583627583122,0.0040184306045971865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c5,7 Panel C,(5) Q: 0.75,35,Bedrooms,bedrooms,A_structural,level,count,-0.004,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,-0.4,0.1,100*b/1 (per unit count),reported,-0.01607631859730484,0.00401907964932621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c6,7 Panel C,(6) Q: 0.95,35,Bedrooms,bedrooms,A_structural,level,count,-0.008,0.004,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,-0.8,0.4,100*b/1 (per unit count),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c1,7 Panel C,(1) 2SLS,36,Bathrooms (Full),bathrooms,A_structural,level,count,0.005,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.5,0.1,100*b/1 (per unit count),reported,0.020093937701409933,0.004018787540281986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c2,7 Panel C,(2) Q: 0.05,36,Bathrooms (Full),bathrooms,A_structural,level,count,-0.012,0.005,,,**,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-1.2,0.5,100*b/1 (per unit count),reported,-0.009646588996759433,0.004019412081983097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c3,7 Panel C,(3) Q: 0.25,36,Bathrooms (Full),bathrooms,A_structural,level,count,0.0,0.001,,,,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.0,0.1,100*b/1 (per unit count),reported,0.0,0.004019599111606953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c4,7 Panel C,(4) Q: 0.50,36,Bathrooms (Full),bathrooms,A_structural,level,count,0.005,0.002,,,**,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.5,0.2,100*b/1 (per unit count),reported,0.010048490431704502,0.0040193961726818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c5,7 Panel C,(5) Q: 0.75,36,Bathrooms (Full),bathrooms,A_structural,level,count,0.008,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.8,0.1,100*b/1 (per unit count),reported,0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c6,7 Panel C,(6) Q: 0.95,36,Bathrooms (Full),bathrooms,A_structural,level,count,0.016,0.003,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,1.6,0.3,100*b/1 (per unit count),reported,0.02143293739900748,0.004018675762313902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.333333333333333,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c1,7 Panel C,(1) 2SLS,36,One story,storeys,A_structural,binary,binary,-0.08,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-7.689519249557586,0.4615581731933179,100*(exp(b - se^2/2) - 1),reported,-0.06418098885674876,0.004011311803546798,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c2,7 Panel C,(2) Q: 0.05,36,One story,storeys,A_structural,binary,binary,-0.066,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-6.388083727104988,0.4680654321458094,100*(exp(b - se^2/2) - 1),reported,-0.05298417945655243,0.0040139529891327595,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.200000000000001,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c3,7 Panel C,(3) Q: 0.25,36,One story,storeys,A_structural,binary,binary,-0.068,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-6.5741394941865146,0.18685209471544273,100*(exp(b - se^2/2) - 1),reported,-0.13540766833933668,0.003982578480568726,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-34.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c4,7 Panel C,(4) Q: 0.50,36,One story,storeys,A_structural,binary,binary,-0.067,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-6.480666905175569,0.18703904026735532,100*(exp(b - se^2/2) - 1),reported,-0.133452102765036,0.003983644858657791,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-33.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c5,7 Panel C,(5) Q: 0.75,36,One story,storeys,A_structural,binary,binary,-0.071,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,-6.854229944149148,0.2794385676382776,100*(exp(b - se^2/2) - 1),reported,-0.09470295537376093,0.00400153332565187,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-23.666666666666664,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c6,7 Panel C,(6) Q: 0.95,36,One story,storeys,A_structural,binary,binary,-0.085,0.004,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-8.149506366742553,0.36740491376058293,100*(exp(b - se^2/2) - 1),reported,-0.0851065776146112,0.004005015417158174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.25,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c1,7 Panel C,(1) 2SLS,36,Renovated,renovation,A_structural,binary,binary,-0.031,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-3.058307842191943,1.0664231303836285,100*(exp(b - se^2/2) - 1),reported,-0.01132723438535498,0.004019341233513057,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.8181818181818183,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c2,7 Panel C,(2) Q: 0.05,36,Renovated,renovation,A_structural,binary,binary,-0.259,0.01,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-22.8215567142686,0.7718230230437034,100*(exp(b - se^2/2) - 1),reported,-0.1035479822755175,0.003997991593649324,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-25.9,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c3,7 Panel C,(3) Q: 0.25,36,Renovated,renovation,A_structural,binary,binary,-0.103,0.012,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-9.793797732231724,1.0825523681778197,100*(exp(b - se^2/2) - 1),reported,-0.03448104275966151,0.004017208865203283,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.583333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c4,7 Panel C,(4) Q: 0.50,36,Renovated,renovation,A_structural,binary,binary,0.015,0.008,,,*,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,1.5080581517383562,0.8120904516925751,100*(exp(b - se^2/2) - 1),reported,0.007536534290023725,0.00401948495467932,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.875,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c5,7 Panel C,(5) Q: 0.75,36,Renovated,renovation,A_structural,binary,binary,0.049,0.003,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,5.0215624759083255,0.3150661052220084,100*(exp(b - se^2/2) - 1),reported,0.06551241241849964,0.0040109640256224275,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.333333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c6,7 Panel C,(6) Q: 0.95,36,Renovated,renovation,A_structural,binary,binary,0.065,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,6.7094463216212485,1.1738749268226119,100*(exp(b - se^2/2) - 1),reported,0.023745479318286147,0.004018465730786886,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.90909090909091,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c1,7 Panel C,(1) 2SLS,36,Fireplace,fireplace,B_interior,binary,binary,0.031,0.005,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,3.147261039830851,0.5157427519432614,100*(exp(b - se^2/2) - 1),reported,0.024913778944489432,0.004018351442659586,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.2,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c2,7 Panel C,(2) Q: 0.05,36,Fireplace,fireplace,B_interior,binary,binary,0.061,0.006,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,6.287978217892842,0.6377393485123172,100*(exp(b - se^2/2) - 1),reported,0.04083184344981298,0.004016246896702915,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.166666666666666,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c3,7 Panel C,(3) Q: 0.25,36,Fireplace,fireplace,B_interior,binary,binary,0.031,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,3.1480862212198923,0.3094456511659568,100*(exp(b - se^2/2) - 1),reported,0.041500074379557404,0.004016136230279748,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.333333333333334,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c4,7 Panel C,(4) Q: 0.50,36,Fireplace,fireplace,B_interior,binary,binary,0.016,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,1.6126653150756232,0.203225737081219,100*(exp(b - se^2/2) - 1),reported,0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c5,7 Panel C,(5) Q: 0.75,36,Fireplace,fireplace,B_interior,binary,binary,0.014,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,1.4096430743602673,0.20281969178769846,100*(exp(b - se^2/2) - 1),reported,0.028126062258739027,0.004018008894105575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c6,7 Panel C,(6) Q: 0.95,36,Fireplace,fireplace,B_interior,binary,binary,0.01,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,1.0045621868642884,0.3030150501252504,100*(exp(b - se^2/2) - 1),reported,0.013397461175148244,0.004019238352544473,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3333333333333335,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c1,7 Panel C,(1) 2SLS,36,Lake/Mountain view,view,E_environment,binary,binary,0.06,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,6.182327367148344,0.5309182732726798,100*(exp(b - se^2/2) - 1),reported,0.04817917426179949,0.004014931188483291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c2,7 Panel C,(2) Q: 0.05,36,Lake/Mountain view,view,E_environment,binary,binary,0.039,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,3.9762165519561243,0.41590819346006314,100*(exp(b - se^2/2) - 1),reported,0.0391610283504275,0.004016515728248974,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.75,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c3,7 Panel C,(3) Q: 0.25,36,Lake/Mountain view,view,E_environment,binary,binary,0.04,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,4.080609055444251,0.3122432322577165,100*(exp(b - se^2/2) - 1),reported,0.05351784795060012,0.004013838596295009,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.333333333333334,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c4,7 Panel C,(4) Q: 0.50,36,Lake/Mountain view,view,E_environment,binary,binary,0.045,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,4.602315279393832,0.3138083579726151,100*(exp(b - se^2/2) - 1),reported,0.06018468926667303,0.004012312617778202,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c5,7 Panel C,(5) Q: 0.75,36,Lake/Mountain view,view,E_environment,binary,binary,0.053,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,5.4424900196629045,0.3163288935358068,100*(exp(b - se^2/2) - 1),reported,0.07083453881226437,0.0040095021969206255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.666666666666664,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7C-c6,7 Panel C,(6) Q: 0.95,36,Lake/Mountain view,view,E_environment,binary,binary,0.093,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in violent crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,9.744801708212991,0.548730867634041,100*(exp(b - se^2/2) - 1),reported,0.07455645836043782,0.004008411739808485,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.599999999999998,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c1,7 Panel D,(1) 2SLS,36,Living area,living_area,A_structural,level,1000 sqft,0.268,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.28847279916782054,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.33795631871264253,0.00378309311991764,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),89.33333333333334,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c2,7 Panel D,(2) Q: 0.05,36,Living area,living_area,A_structural,level,1000 sqft,0.252,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.271250542501085,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.1985542516600187,0.003939568485317832,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),50.4,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c3,7 Panel D,(3) Q: 0.25,36,Living area,living_area,A_structural,level,1000 sqft,0.259,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.27878527979278184,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.4617283980831373,0.003565470255468242,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),129.5,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c4,7 Panel D,(4) Q: 0.50,36,Living area,living_area,A_structural,level,1000 sqft,0.276,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.29708392750118834,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.48507424669809696,0.003515030773174615,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),138.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c5,7 Panel D,(5) Q: 0.75,36,Living area,living_area,A_structural,level,1000 sqft,0.288,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.31000062000123996,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.5009551799969574,0.003478855416645538,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),144.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c6,7 Panel D,(6) Q: 0.95,36,Living area,living_area,A_structural,level,1000 sqft,0.302,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.3250700945846336,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.23593001210574505,0.003906126028240812,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),60.4,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c1,7 Panel D,(1) 2SLS,36,Lot area,lot_size,A_structural,level,1000 sqft,0.013,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.013993083541722639,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.05218359172933882,0.004014122440718371,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c2,7 Panel D,(2) Q: 0.05,36,Lot area,lot_size,A_structural,level,1000 sqft,-0.001,0.001,,,,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.0010763910416709723,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,-0.004019566639313255,0.004019566639313255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c4,7 Panel D,(4) Q: 0.50,36,Lot area,lot_size,A_structural,level,1000 sqft,0.012,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.012916692500051665,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.04817917426179949,0.004014931188483291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c5,7 Panel D,(5) Q: 0.75,36,Lot area,lot_size,A_structural,level,1000 sqft,0.018,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.019375038750077497,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.07216414361374496,0.0040091190896524975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c6,7 Panel D,(6) Q: 0.95,36,Lot area,lot_size,A_structural,level,1000 sqft,0.03,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.032291731250129165,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.11972065843265513,0.003990688614421837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c1,7 Panel D,(1) 2SLS,36,Bedrooms,bedrooms,A_structural,level,count,-0.011,0.002,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,-1.0999999999999999,0.2,100*b/1 (per unit count),reported,-0.022102394450125195,0.004018617172750035,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c2,7 Panel D,(2) Q: 0.05,36,Bedrooms,bedrooms,A_structural,level,count,-0.009,0.004,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.8999999999999999,0.4,100*b/1 (per unit count),reported,-0.009043728139602736,0.004019434728712327,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.25,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c3,7 Panel D,(3) Q: 0.25,36,Bedrooms,bedrooms,A_structural,level,count,-0.007,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,-0.7000000000000001,0.1,100*b/1 (per unit count),reported,-0.028126062258739027,0.004018008894105575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c4,7 Panel D,(4) Q: 0.50,36,Bedrooms,bedrooms,A_structural,level,count,-0.006,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,-0.6,0.1,100*b/1 (per unit count),reported,-0.024110583627583122,0.0040184306045971865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c5,7 Panel D,(5) Q: 0.75,36,Bedrooms,bedrooms,A_structural,level,count,-0.004,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,-0.4,0.1,100*b/1 (per unit count),reported,-0.01607631859730484,0.00401907964932621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c6,7 Panel D,(6) Q: 0.95,36,Bedrooms,bedrooms,A_structural,level,count,-0.008,0.004,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,-0.8,0.4,100*b/1 (per unit count),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c1,7 Panel D,(1) 2SLS,36,Bathrooms (Full),bathrooms,A_structural,level,count,0.005,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.5,0.1,100*b/1 (per unit count),reported,0.020093937701409933,0.004018787540281986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c2,7 Panel D,(2) Q: 0.05,36,Bathrooms (Full),bathrooms,A_structural,level,count,-0.012,0.005,,,**,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-1.2,0.5,100*b/1 (per unit count),reported,-0.009646588996759433,0.004019412081983097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c3,7 Panel D,(3) Q: 0.25,36,Bathrooms (Full),bathrooms,A_structural,level,count,0.0,0.001,,,,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.0,0.1,100*b/1 (per unit count),reported,0.0,0.004019599111606953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c4,7 Panel D,(4) Q: 0.50,36,Bathrooms (Full),bathrooms,A_structural,level,count,0.005,0.002,,,**,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.5,0.2,100*b/1 (per unit count),reported,0.010048490431704502,0.0040193961726818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c5,7 Panel D,(5) Q: 0.75,36,Bathrooms (Full),bathrooms,A_structural,level,count,0.008,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.8,0.1,100*b/1 (per unit count),reported,0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c6,7 Panel D,(6) Q: 0.95,36,Bathrooms (Full),bathrooms,A_structural,level,count,0.016,0.003,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,1.6,0.3,100*b/1 (per unit count),reported,0.02143293739900748,0.004018675762313902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.333333333333333,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c1,7 Panel D,(1) 2SLS,36,One story,storeys,A_structural,binary,binary,-0.08,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-7.689519249557586,0.4615581731933179,100*(exp(b - se^2/2) - 1),reported,-0.06418098885674876,0.004011311803546798,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c2,7 Panel D,(2) Q: 0.05,36,One story,storeys,A_structural,binary,binary,-0.066,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-6.388083727104988,0.4680654321458094,100*(exp(b - se^2/2) - 1),reported,-0.05298417945655243,0.0040139529891327595,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.200000000000001,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c3,7 Panel D,(3) Q: 0.25,36,One story,storeys,A_structural,binary,binary,-0.068,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-6.5741394941865146,0.18685209471544273,100*(exp(b - se^2/2) - 1),reported,-0.13540766833933668,0.003982578480568726,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-34.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c4,7 Panel D,(4) Q: 0.50,36,One story,storeys,A_structural,binary,binary,-0.067,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-6.480900703216063,0.280558560401033,100*(exp(b - se^2/2) - 1),reported,-0.08941149327137186,0.004003499698718143,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.333333333333336,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c5,7 Panel D,(5) Q: 0.75,36,One story,storeys,A_structural,binary,binary,-0.071,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,-6.854229944149148,0.2794385676382776,100*(exp(b - se^2/2) - 1),reported,-0.09470295537376093,0.00400153332565187,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-23.666666666666664,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c6,7 Panel D,(6) Q: 0.95,36,One story,storeys,A_structural,binary,binary,-0.085,0.004,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-8.149506366742553,0.36740491376058293,100*(exp(b - se^2/2) - 1),reported,-0.0851065776146112,0.004005015417158174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.25,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c1,7 Panel D,(1) 2SLS,37,Renovated,renovation,A_structural,binary,binary,-0.031,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-3.058307842191943,1.0664231303836285,100*(exp(b - se^2/2) - 1),reported,-0.01132723438535498,0.004019341233513057,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.8181818181818183,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c2,7 Panel D,(2) Q: 0.05,37,Renovated,renovation,A_structural,binary,binary,-0.26,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-22.899506140628255,0.8481567443839229,100*(exp(b - se^2/2) - 1),reported,-0.09458278224477856,0.004001579248817554,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-23.63636363636364,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c3,7 Panel D,(3) Q: 0.25,37,Renovated,renovation,A_structural,binary,binary,-0.103,0.012,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-9.793797732231724,1.0825523681778197,100*(exp(b - se^2/2) - 1),reported,-0.03448104275966151,0.004017208865203283,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.583333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c4,7 Panel D,(4) Q: 0.50,37,Renovated,renovation,A_structural,binary,binary,0.014,0.007,,,*,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,1.4073613830602127,0.7098689212569446,100*(exp(b - se^2/2) - 1),reported,0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c5,7 Panel D,(5) Q: 0.75,37,Renovated,renovation,A_structural,binary,binary,0.049,0.003,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,5.0215624759083255,0.3150661052220084,100*(exp(b - se^2/2) - 1),reported,0.06551241241849964,0.0040109640256224275,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.333333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c6,7 Panel D,(6) Q: 0.95,37,Renovated,renovation,A_structural,binary,binary,0.066,0.012,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,6.814980761113465,1.281872060599192,100*(exp(b - se^2/2) - 1),reported,0.022102394450125195,0.004018617172750035,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c1,7 Panel D,(1) 2SLS,37,Fireplace,fireplace,B_interior,binary,binary,0.031,0.005,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,3.147261039830851,0.5157427519432614,100*(exp(b - se^2/2) - 1),reported,0.024913778944489432,0.004018351442659586,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.2,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c2,7 Panel D,(2) Q: 0.05,37,Fireplace,fireplace,B_interior,binary,binary,0.061,0.006,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,6.287978217892842,0.6377393485123172,100*(exp(b - se^2/2) - 1),reported,0.04083184344981298,0.004016246896702915,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.166666666666666,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c3,7 Panel D,(3) Q: 0.25,37,Fireplace,fireplace,B_interior,binary,binary,0.031,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,3.1480862212198923,0.3094456511659568,100*(exp(b - se^2/2) - 1),reported,0.041500074379557404,0.004016136230279748,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.333333333333334,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c4,7 Panel D,(4) Q: 0.50,37,Fireplace,fireplace,B_interior,binary,binary,0.016,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,1.6126653150756232,0.203225737081219,100*(exp(b - se^2/2) - 1),reported,0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c5,7 Panel D,(5) Q: 0.75,37,Fireplace,fireplace,B_interior,binary,binary,0.014,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,1.4096430743602673,0.20281969178769846,100*(exp(b - se^2/2) - 1),reported,0.028126062258739027,0.004018008894105575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c6,7 Panel D,(6) Q: 0.95,37,Fireplace,fireplace,B_interior,binary,binary,0.01,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,1.0045621868642884,0.3030150501252504,100*(exp(b - se^2/2) - 1),reported,0.013397461175148244,0.004019238352544473,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3333333333333335,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c1,7 Panel D,(1) 2SLS,37,Lake/Mountain view,view,E_environment,binary,binary,0.06,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,IV,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,6.182327367148344,0.5309182732726798,100*(exp(b - se^2/2) - 1),reported,0.04817917426179949,0.004014931188483291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c2,7 Panel D,(2) Q: 0.05,37,Lake/Mountain view,view,E_environment,binary,binary,0.04,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,4.079776413902381,0.5204053870961941,100*(exp(b - se^2/2) - 1),reported,0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c3,7 Panel D,(3) Q: 0.25,37,Lake/Mountain view,view,E_environment,binary,binary,0.04,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,4.080609055444251,0.3122432322577165,100*(exp(b - se^2/2) - 1),reported,0.05351784795060012,0.004013838596295009,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.333333333333334,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c4,7 Panel D,(4) Q: 0.50,37,Lake/Mountain view,view,E_environment,binary,binary,0.045,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,4.602315279393832,0.3138083579726151,100*(exp(b - se^2/2) - 1),reported,0.06018468926667303,0.004012312617778202,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c5,7 Panel D,(5) Q: 0.75,37,Lake/Mountain view,view,E_environment,binary,binary,0.054,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,5.547985248505705,0.31664538064652403,100*(exp(b - se^2/2) - 1),reported,0.07216414361374496,0.0040091190896524975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7D-c6,7 Panel D,(6) Q: 0.95,37,Lake/Mountain view,view,E_environment,binary,binary,0.093,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,With spatial lag of neighbour prices; change in social crimes and changes in demographics; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,9.744801708212991,0.548730867634041,100*(exp(b - se^2/2) - 1),reported,0.07455645836043782,0.004008411739808485,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.599999999999998,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c1,7 Panel E,(1) 2SLS,37,Living area,living_area,A_structural,level,1000 sqft,0.262,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,IV,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.28201445291779476,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.26182986586282503,0.00399740253225687,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),65.5,58291.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c2,7 Panel E,(2) Q: 0.05,37,Living area,living_area,A_structural,level,1000 sqft,0.242,0.006,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.2604866320843753,0.006458346250025833,100*b/92.903 (X per 1000sqft->m2),reported,0.16477308260079432,0.004085283039689116,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.33333333333333,58291.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c3,7 Panel E,(3) Q: 0.25,37,Living area,living_area,A_structural,level,1000 sqft,0.253,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.27232693354275594,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.46410457213618095,0.003668810846926332,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),126.5,58291.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c4,7 Panel E,(4) Q: 0.50,37,Living area,living_area,A_structural,level,1000 sqft,0.267,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.2873964081261496,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.3458769761338051,0.0038862581588067985,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),89.0,58291.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c5,7 Panel E,(5) Q: 0.75,37,Living area,living_area,A_structural,level,1000 sqft,0.287,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.308924228959569,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.2848679086457831,0.003970284441056212,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),71.74999999999999,58291.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c6,7 Panel E,(6) Q: 0.95,37,Living area,living_area,A_structural,level,1000 sqft,0.3,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.32291731250129163,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.38266457888843425,0.003826645788884342,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),100.0,58291.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c1,7 Panel E,(1) 2SLS,37,Lot area,lot_size,A_structural,level,1000 sqft,0.018,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,IV,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.019375038750077497,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.07434779973495277,0.004130433318608488,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,58291.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c2,7 Panel E,(2) Q: 0.05,37,Lot area,lot_size,A_structural,level,1000 sqft,0.009,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.009687519375038749,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.03725119613901589,0.004139021793223988,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.0,58291.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c4,7 Panel E,(4) Q: 0.50,37,Lot area,lot_size,A_structural,level,1000 sqft,0.018,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.019375038750077497,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.07434779973495277,0.004130433318608488,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,58291.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c5,7 Panel E,(5) Q: 0.75,37,Lot area,lot_size,A_structural,level,1000 sqft,0.022,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.023680602916761384,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.09074576411495175,0.0041248074597705344,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,58291.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c6,7 Panel E,(6) Q: 0.95,37,Lot area,lot_size,A_structural,level,1000 sqft,0.034,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.03659729541681306,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.13944853165344473,0.004101427401571905,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.0,58291.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c1,7 Panel E,(1) 2SLS,37,Bedrooms,bedrooms,A_structural,level,count,-0.007,0.001,,,***,,,high,,Log (Sale Price),log,IV,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,-0.7000000000000001,0.1,100*b/1 (per unit count),reported,-0.02898109747697928,0.004140156782425611,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,58291.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c2,7 Panel E,(2) Q: 0.05,37,Bedrooms,bedrooms,A_structural,level,count,0.001,0.003,,,,,,high,,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.1,0.3,100*b/1 (per unit count),reported,0.0013806308660163915,0.004141892598049175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3333333333333333,58291.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c3,7 Panel E,(3) Q: 0.25,37,Bedrooms,bedrooms,A_structural,level,count,-0.001,0.002,,,,,,high,,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,-0.1,0.2,100*b/1 (per unit count),reported,-0.002070943831830954,0.004141887663661908,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5,58291.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c4,7 Panel E,(4) Q: 0.50,37,Bedrooms,bedrooms,A_structural,level,count,-0.001,0.002,,,,,,high,,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,-0.1,0.2,100*b/1 (per unit count),reported,-0.002070943831830954,0.004141887663661908,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5,58291.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c5,7 Panel E,(5) Q: 0.75,37,Bedrooms,bedrooms,A_structural,level,count,-0.002,0.003,,,,,,high,,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,-0.2,0.3,100*b/1 (per unit count),reported,-0.0027612538370329082,0.004141880755549362,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6666666666666666,58291.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c6,7 Panel E,(6) Q: 0.95,37,Bedrooms,bedrooms,A_structural,level,count,-0.008,0.004,,,**,,,high,,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,-0.8,0.4,100*b/1 (per unit count),reported,-0.008283508883743173,0.004141754441871586,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,58291.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c1,7 Panel E,(1) 2SLS,37,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,IV,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.8999999999999999,0.1,100*b/1 (per unit count),reported,0.03725119613901589,0.004139021793223988,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.0,58291.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c2,7 Panel E,(2) Q: 0.05,37,Bathrooms (Full),bathrooms,A_structural,level,count,-0.005,0.006,,,,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.5,0.6,100*b/1 (per unit count),reported,-0.0034515598947843043,0.0041418718737411655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8333333333333334,58291.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c3,7 Panel E,(3) Q: 0.25,37,Bathrooms (Full),bathrooms,A_structural,level,count,0.007,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.7000000000000001,0.1,100*b/1 (per unit count),reported,0.02898109747697928,0.004140156782425611,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,58291.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c4,7 Panel E,(4) Q: 0.50,37,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.8999999999999999,0.2,100*b/1 (per unit count),reported,0.018635297831810595,0.00414117729595791,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,58291.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c5,7 Panel E,(5) Q: 0.75,37,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.8999999999999999,0.1,100*b/1 (per unit count),reported,0.03725119613901589,0.004139021793223988,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.0,58291.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c6,7 Panel E,(6) Q: 0.95,37,Bathrooms (Full),bathrooms,A_structural,level,count,0.015,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,1.5,0.1,100*b/1 (per unit count),reported,0.062008888026408374,0.004133925868427225,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.0,58291.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c1,7 Panel E,(1) 2SLS,37,One story,storeys,A_structural,binary,binary,-0.075,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,IV,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-7.226811039254654,0.46387174316427643,100*(exp(b - se^2/2) - 1),reported,-0.062008888026408374,0.004133925868427225,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.0,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c2,7 Panel E,(2) Q: 0.05,37,One story,storeys,A_structural,binary,binary,-0.05,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-4.8782465792777785,0.47561471225035706,100*(exp(b - se^2/2) - 1),reported,-0.04138348334878986,0.004138348334878986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.0,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c3,7 Panel E,(3) Q: 0.25,37,One story,storeys,A_structural,binary,binary,-0.064,0.004,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-6.200250447925071,0.3752019998122918,100*(exp(b - se^2/2) - 1),reported,-0.06612530062581795,0.004132831289113623,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.0,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c4,7 Panel E,(4) Q: 0.50,37,One story,storeys,A_structural,binary,binary,-0.066,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-6.3873348287792115,0.28083925928748565,100*(exp(b - se^2/2) - 1),reported,-0.09074576411495175,0.0041248074597705344,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.0,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c5,7 Panel E,(5) Q: 0.75,37,One story,storeys,A_structural,binary,binary,-0.071,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,-6.854229944149148,0.2794385676382776,100*(exp(b - se^2/2) - 1),reported,-0.0975572973870148,0.004122139326211893,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-23.666666666666664,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c6,7 Panel E,(6) Q: 0.95,37,One story,storeys,A_structural,binary,binary,-0.083,0.004,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-7.9656215559601895,0.36814045888804986,100*(exp(b - se^2/2) - 1),reported,-0.0856286899127531,0.004126683851217017,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-20.75,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c1,7 Panel E,(1) 2SLS,37,Renovated,renovation,A_structural,binary,binary,-0.027,0.011,,,**,,,high,Previously renovated =1,Log (Sale Price),log,IV,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-2.669764504943861,1.0706973656767704,100*(exp(b - se^2/2) - 1),reported,-0.01016594799084581,0.004141682514789034,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4545454545454546,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c2,7 Panel E,(2) Q: 0.05,37,Renovated,renovation,A_structural,binary,binary,-0.265,0.015,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-23.288035583872347,1.1508089249637834,100*(exp(b - se^2/2) - 1),reported,-0.0729783901127667,0.004130852270533963,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.666666666666668,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c3,7 Panel E,(3) Q: 0.25,37,Renovated,renovation,A_structural,binary,binary,-0.102,0.015,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-9.707203344141636,1.354544327503315,100*(exp(b - se^2/2) - 1),reported,-0.028153732089123,0.004140254718988677,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.8,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c4,7 Panel E,(4) Q: 0.50,37,Renovated,renovation,A_structural,binary,binary,0.022,0.006,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,2.222538424792031,0.6133462706822629,100*(exp(b - se^2/2) - 1),reported,0.015185202916673055,0.00414141897727447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6666666666666665,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c5,7 Panel E,(5) Q: 0.75,37,Renovated,renovation,A_structural,binary,binary,0.049,0.004,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,5.021194901082926,0.4200881402960112,100*(exp(b - se^2/2) - 1),reported,0.05067304906348116,0.004136575433753564,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.25,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c6,7 Panel E,(6) Q: 0.95,37,Renovated,renovation,A_structural,binary,binary,0.072,0.014,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,7.4550033000421845,1.504517481689339,100*(exp(b - se^2/2) - 1),reported,0.021296351275210873,0.004140957192402115,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.142857142857142,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c1,7 Panel E,(1) 2SLS,37,Fireplace,fireplace,B_interior,binary,binary,0.025,0.004,,,***,,,high,,Log (Sale Price),log,IV,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,2.5306918036274606,0.41012604820977155,100*(exp(b - se^2/2) - 1),reported,0.025878183998881536,0.004140509439821046,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.25,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c2,7 Panel E,(2) Q: 0.05,37,Fireplace,fireplace,B_interior,binary,binary,0.043,0.006,,,***,,,high,,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,4.391910413762212,0.6263627369103676,100*(exp(b - se^2/2) - 1),reported,0.029670523207201698,0.004140073005656051,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.166666666666666,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c3,7 Panel E,(3) Q: 0.25,37,Fireplace,fireplace,B_interior,binary,binary,0.024,0.002,,,***,,,high,,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,2.4288269312034316,0.2048580635781243,100*(exp(b - se^2/2) - 1),reported,0.04964148010072049,0.004136790008393374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c4,7 Panel E,(4) Q: 0.50,37,Fireplace,fireplace,B_interior,binary,binary,0.014,0.003,,,***,,,high,,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,1.4093895505694842,0.3042295376815477,100*(exp(b - se^2/2) - 1),reported,0.01932524088499034,0.004141123046783644,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.666666666666667,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c5,7 Panel E,(5) Q: 0.75,37,Fireplace,fireplace,B_interior,binary,binary,0.011,0.002,,,***,,,high,,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,1.1058700325296877,0.2022121444889439,100*(exp(b - se^2/2) - 1),reported,0.02277452237027888,0.004140822249141614,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.5,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c6,7 Panel E,(6) Q: 0.95,37,Fireplace,fireplace,B_interior,binary,binary,0.006,0.003,,,*,,,high,,Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,0.6013508983088611,0.3018054108162195,100*(exp(b - se^2/2) - 1),reported,0.008283508883743173,0.004141754441871586,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c1,7 Panel E,(1) 2SLS,37,Lake/Mountain view,view,E_environment,binary,binary,0.062,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,IV,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,6.394904528184631,0.5319811723640169,100*(exp(b - se^2/2) - 1),reported,0.05129191281352017,0.004136444581735498,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.4,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c2,7 Panel E,(2) Q: 0.05,37,Lake/Mountain view,view,E_environment,binary,binary,0.038,0.008,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,3.8697994010870262,0.8309849863027982,100*(exp(b - se^2/2) - 1),reported,0.019670202120503025,0.004141095183263795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.75,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c3,7 Panel E,(3) Q: 0.25,37,Lake/Mountain view,view,E_environment,binary,binary,0.035,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,3.5606763634170813,0.5178098543998116,100*(exp(b - se^2/2) - 1),reported,0.028981097476979283,0.004140156782425611,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.000000000000001,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c4,7 Panel E,(4) Q: 0.50,37,Lake/Mountain view,view,E_environment,binary,binary,0.047,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,4.811362413712272,0.4192488036318623,100*(exp(b - se^2/2) - 1),reported,0.04860975224640102,0.004137000191183065,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.75,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c5,7 Panel E,(5) Q: 0.75,37,Lake/Mountain view,view,E_environment,binary,binary,0.059,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,6.07619811325224,0.5303876203700795,100*(exp(b - se^2/2) - 1),reported,0.04881611037163148,0.004136958506070465,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.799999999999999,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T7E-c6,7 Panel E,(6) Q: 0.95,37,Lake/Mountain view,view,E_environment,binary,binary,0.103,0.012,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,58301.0,,se,With spatial lag of neighbour prices; lagged crimes instrumented by lagged 911 calls; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,10.84116005676945,1.3301896908912085,100*(exp(b - se^2/2) - 1),reported,0.03552883344334841,0.00413928156621535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.583333333333332,58291.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c1,8 Panel A,(1) 2SLS,41,Living area,living_area,A_structural,level,1000 sqft,0.318,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.34229235125136914,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.3043938972733358,0.0038288540537526517,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),79.5,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c2,8 Panel A,(2) Q: 0.05,41,Living area,living_area,A_structural,level,1000 sqft,0.284,0.006,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.3056950558345561,0.006458346250025833,100*b/92.903 (X per 1000sqft->m2),reported,0.1869081301840186,0.003948763313746872,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.33333333333333,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c3,8 Panel A,(3) Q: 0.25,41,Living area,living_area,A_structural,level,1000 sqft,0.306,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.32937565875131747,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.3793525756781874,0.0037191428988057585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),102.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c4,8 Panel A,(4) Q: 0.50,41,Living area,living_area,A_structural,level,1000 sqft,0.32,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.3444451333347111,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.3940635690280088,0.003694345959637582,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),106.66666666666667,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c5,8 Panel A,(5) Q: 0.75,41,Living area,living_area,A_structural,level,1000 sqft,0.34,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.3659729541681305,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.3233154705538053,0.0038037114182800616,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),85.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c6,8 Panel A,(6) Q: 0.95,41,Living area,living_area,A_structural,level,1000 sqft,0.347,0.006,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.3735076914598273,0.006458346250025833,100*b/92.903 (X per 1000sqft->m2),reported,0.22642910546765005,0.003915200670910376,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),57.83333333333333,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c1,8 Panel A,(1) 2SLS,41,Lot area,lot_size,A_structural,level,1000 sqft,0.021,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.022604211875090416,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.08411244939884005,0.004005354733278097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c2,8 Panel A,(2) Q: 0.05,41,Lot area,lot_size,A_structural,level,1000 sqft,0.007,0.002,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.007534737291696806,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.01406720483080051,0.004019201380228717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c3,8 Panel A,(3) Q: 0.25,41,Lot area,lot_size,A_structural,level,1000 sqft,0.013,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.013993083541722639,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.05218359172933882,0.004014122440718371,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c4,8 Panel A,(4) Q: 0.50,41,Lot area,lot_size,A_structural,level,1000 sqft,0.019,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.02045142979174847,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.0761506225926853,0.004007927504878174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c5,8 Panel A,(5) Q: 0.75,41,Lot area,lot_size,A_structural,level,1000 sqft,0.026,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.027986167083445278,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.10394347012419862,0.003997825774007639,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c6,8 Panel A,(6) Q: 0.95,41,Lot area,lot_size,A_structural,level,1000 sqft,0.038,0.002,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.04090285958349694,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.0761506225926853,0.004007927504878174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c1,8 Panel A,(1) 2SLS,41,Bedrooms,bedrooms,A_structural,level,count,-0.019,0.002,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,-1.9,0.2,100*b/1 (per unit count),reported,-0.03815838070142761,0.004016671652781854,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c2,8 Panel A,(2) Q: 0.05,41,Bedrooms,bedrooms,A_structural,level,count,-0.008,0.004,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.8,0.4,100*b/1 (per unit count),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c3,8 Panel A,(3) Q: 0.25,41,Bedrooms,bedrooms,A_structural,level,count,-0.012,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,-1.2,0.2,100*b/1 (per unit count),reported,-0.024110583627583122,0.0040184306045971865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c4,8 Panel A,(4) Q: 0.50,41,Bedrooms,bedrooms,A_structural,level,count,-0.012,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,-1.2,0.1,100*b/1 (per unit count),reported,-0.04817917426179949,0.004014931188483291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c5,8 Panel A,(5) Q: 0.75,41,Bedrooms,bedrooms,A_structural,level,count,-0.014,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,-1.4000000000000001,0.1,100*b/1 (per unit count),reported,-0.056185493585738,0.004013249541838429,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c6,8 Panel A,(6) Q: 0.95,41,Bedrooms,bedrooms,A_structural,level,count,-0.019,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,-1.9,0.3,100*b/1 (per unit count),reported,-0.02544921578242598,0.004018297228804102,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.333333333333333,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c1,8 Panel A,(1) 2SLS,41,Bathrooms (Full),bathrooms,A_structural,level,count,0.003,0.002,,,,,,high,Number of full bathrooms,Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.3,0.2,100*b/1 (per unit count),reported,0.006029289075079203,0.004019526050052801,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c2,8 Panel A,(2) Q: 0.05,41,Bathrooms (Full),bathrooms,A_structural,level,count,-0.01,0.004,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-1.0,0.4,100*b/1 (per unit count),reported,-0.010048490431704502,0.0040193961726818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c3,8 Panel A,(3) Q: 0.25,41,Bathrooms (Full),bathrooms,A_structural,level,count,0.002,0.003,,,,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.2,0.3,100*b/1 (per unit count),reported,0.0026797231195861745,0.004019584679379263,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6666666666666666,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c4,8 Panel A,(4) Q: 0.50,41,Bathrooms (Full),bathrooms,A_structural,level,count,0.006,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.6,0.2,100*b/1 (per unit count),reported,0.012057920667875593,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c5,8 Panel A,(5) Q: 0.75,41,Bathrooms (Full),bathrooms,A_structural,level,count,0.004,0.002,,,*,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.4,0.2,100*b/1 (per unit count),reported,0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c6,8 Panel A,(6) Q: 0.95,41,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.003,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.8999999999999999,0.3,100*b/1 (per unit count),reported,0.012057920667875591,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9999999999999996,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c1,8 Panel A,(1) 2SLS,41,One story,storeys,A_structural,binary,binary,-0.095,0.008,,,***,,,high,One-story property =1,Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-9.065616500007756,0.7274983475745852,100*(exp(b - se^2/2) - 1),reported,-0.047678454714258044,0.004015027765411204,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.875,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c2,8 Panel A,(2) Q: 0.05,41,One story,storeys,A_structural,binary,binary,-0.064,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-6.200672545848329,0.46900249976536473,100*(exp(b - se^2/2) - 1),reported,-0.051382903375746324,0.004014289326230181,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.8,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c3,8 Panel A,(3) Q: 0.25,41,One story,storeys,A_structural,binary,binary,-0.077,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-7.411199817136005,0.18517797072129907,100*(exp(b - se^2/2) - 1),reported,-0.152934093480691,0.003972314116381585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-38.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c4,8 Panel A,(4) Q: 0.50,41,One story,storeys,A_structural,binary,binary,-0.082,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-7.873218701813767,0.27638158760890463,100*(exp(b - se^2/2) - 1),reported,-0.10921186022302366,0.003995555861817939,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-27.333333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c5,8 Panel A,(5) Q: 0.75,41,One story,storeys,A_structural,binary,binary,-0.088,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,-8.424324419134754,0.2747282630169977,100*(exp(b - se^2/2) - 1),reported,-0.11709708757489604,0.003991946167326002,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-29.333333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c6,8 Panel A,(6) Q: 0.95,41,One story,storeys,A_structural,binary,binary,-0.1,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-9.516665372326017,0.27145122541078787,100*(exp(b - se^2/2) - 1),reported,-0.13279989984554053,0.003983996995366215,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-33.333333333333336,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c1,8 Panel A,(1) 2SLS,41,Renovated,renovation,A_structural,binary,binary,-0.046,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-4.501581610018701,1.0505461584097862,100*(exp(b - se^2/2) - 1),reported,-0.016806858424771982,0.004019031362445475,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.181818181818182,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c2,8 Panel A,(2) Q: 0.05,41,Renovated,renovation,A_structural,binary,binary,-0.269,0.017,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-23.59671550748754,1.2990435346019382,100*(exp(b - se^2/2) - 1),reported,-0.06347597832690245,0.004011493054116511,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.823529411764707,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c3,8 Panel A,(3) Q: 0.25,41,Renovated,renovation,A_structural,binary,binary,-0.107,0.012,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-10.153901852922708,1.0782308075883666,100*(exp(b - se^2/2) - 1),reported,-0.03581842648102667,0.004017019792264673,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.916666666666666,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c4,8 Panel A,(4) Q: 0.50,41,Renovated,renovation,A_structural,binary,binary,-0.007,0.006,,,,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-0.6993431345868717,0.595814665759941,100*(exp(b - se^2/2) - 1),reported,-0.004689480732300701,0.004019554913400601,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1666666666666667,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c5,8 Panel A,(5) Q: 0.75,41,Renovated,renovation,A_structural,binary,binary,0.026,0.004,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,2.6332737778697046,0.4105363793893768,100*(exp(b - se^2/2) - 1),reported,0.026118480976874945,0.004018227842596146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c6,8 Panel A,(6) Q: 0.95,41,Renovated,renovation,A_structural,binary,binary,0.049,0.01,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,5.016784103524463,1.050220350740028,100*(exp(b - se^2/2) - 1),reported,0.0196922163788799,0.004018819669159164,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.9,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c1,8 Panel A,(1) 2SLS,41,Fireplace,fireplace,B_interior,binary,binary,0.04,0.005,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,4.079776413902381,0.5204053870961941,100*(exp(b - se^2/2) - 1),reported,0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c2,8 Panel A,(2) Q: 0.05,41,Fireplace,fireplace,B_interior,binary,binary,0.059,0.008,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,6.0741296475566475,0.8486201925921272,100*(exp(b - se^2/2) - 1),reported,0.029631526230191076,0.004017834065110655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.374999999999999,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c3,8 Panel A,(3) Q: 0.25,41,Fireplace,fireplace,B_interior,binary,binary,0.042,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,4.289239296389158,0.20857889575015265,100*(exp(b - se^2/2) - 1),reported,0.08411244939884005,0.004005354733278097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c4,8 Panel A,(4) Q: 0.50,41,Fireplace,fireplace,B_interior,binary,binary,0.029,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,2.942407976296235,0.10294245944751308,100*(exp(b - se^2/2) - 1),reported,0.11578437869023656,0.00399256478242195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c5,8 Panel A,(5) Q: 0.75,41,Fireplace,fireplace,B_interior,binary,binary,0.021,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,2.122154102663054,0.10212220516375285,100*(exp(b - se^2/2) - 1),reported,0.08411244939884005,0.004005354733278097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c6,8 Panel A,(6) Q: 0.95,41,Fireplace,fireplace,B_interior,binary,binary,0.013,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,1.308030848816344,0.30392546020794275,100*(exp(b - se^2/2) - 1),reported,0.01741562110347812,0.0040189894854180275,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.333333333333333,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c1,8 Panel A,(1) 2SLS,41,Lake/Mountain view,view,E_environment,binary,binary,0.104,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,10.958658499658336,0.5548002274577912,100*(exp(b - se^2/2) - 1),reported,0.0833169658071174,0.004005623356111414,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.799999999999997,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c2,8 Panel A,(2) Q: 0.05,41,Lake/Mountain view,view,E_environment,binary,binary,0.066,0.007,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,6.820054593202163,0.7477587020161953,100*(exp(b - se^2/2) - 1),reported,0.03787188864209804,0.0040167154620407005,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.428571428571429,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c3,8 Panel A,(3) Q: 0.25,41,Lake/Mountain view,view,E_environment,binary,binary,0.069,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,7.142763769295879,0.42857448365933853,100*(exp(b - se^2/2) - 1),reported,0.06917200251825996,0.004009971160478838,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.25,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c4,8 Panel A,(4) Q: 0.50,41,Lake/Mountain view,view,E_environment,binary,binary,0.08,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,8.328219289412232,0.3249861203024876,100*(exp(b - se^2/2) - 1),reported,0.1065787872397259,0.003996704521489721,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.666666666666668,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c5,8 Panel A,(5) Q: 0.75,41,Lake/Mountain view,view,E_environment,binary,binary,0.103,0.006,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,10.84714564102185,0.6650948454456043,100*(exp(b - se^2/2) - 1),reported,0.06883942564001688,0.004010063629515547,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.166666666666664,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8A-c6,8 Panel A,(6) Q: 0.95,41,Lake/Mountain view,view,E_environment,binary,binary,0.173,0.007,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,18.88369782212631,0.8322062735588225,100*(exp(b - se^2/2) - 1),reported,0.09885493175931549,0.003999910533613923,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.71428571428571,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c1,8 Panel B,(1) 2SLS,41,Living area,living_area,A_structural,level,1000 sqft,0.261,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.28093806187612375,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.25369799088088457,0.00388809181426643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),65.25,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c2,8 Panel B,(2) Q: 0.05,41,Living area,living_area,A_structural,level,1000 sqft,0.24,0.006,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.2583338500010333,0.006458346250025833,100*b/92.903 (X per 1000sqft->m2),reported,0.1587451580364743,0.003968628950911857,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),40.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c3,8 Panel B,(3) Q: 0.25,41,Living area,living_area,A_structural,level,1000 sqft,0.252,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.271250542501085,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.31990310072026185,0.003808370246669784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),84.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c4,8 Panel B,(4) Q: 0.50,41,Living area,living_area,A_structural,level,1000 sqft,0.266,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.28632001708447863,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.3357194594671822,0.003786309693238897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),88.66666666666667,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c5,8 Panel B,(5) Q: 0.75,41,Living area,living_area,A_structural,level,1000 sqft,0.285,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.30677144687622704,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.4970311166303093,0.0034879376605635747,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),142.49999999999997,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c6,8 Panel B,(6) Q: 0.95,41,Living area,living_area,A_structural,level,1000 sqft,0.3,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.32291731250129163,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.23445371777087137,0.0039075619628478565,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),60.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c1,8 Panel B,(1) 2SLS,42,Lot area,lot_size,A_structural,level,1000 sqft,0.018,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.019375038750077497,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.07216414361374496,0.0040091190896524975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c2,8 Panel B,(2) Q: 0.05,42,Lot area,lot_size,A_structural,level,1000 sqft,0.007,0.002,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.007534737291696806,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.01406720483080051,0.004019201380228717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c4,8 Panel B,(4) Q: 0.50,42,Lot area,lot_size,A_structural,level,1000 sqft,0.018,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.019375038750077497,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.07216414361374496,0.0040091190896524975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c5,8 Panel B,(5) Q: 0.75,42,Lot area,lot_size,A_structural,level,1000 sqft,0.022,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.023680602916761384,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.08808742611158363,0.004003973914162892,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c6,8 Panel B,(6) Q: 0.95,42,Lot area,lot_size,A_structural,level,1000 sqft,0.033,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.03552090437514208,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.13149497712968528,0.003984696276657129,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),33.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c1,8 Panel B,(1) 2SLS,42,Bedrooms,bedrooms,A_structural,level,count,-0.007,0.001,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,-0.7000000000000001,0.1,100*b/1 (per unit count),reported,-0.028126062258739027,0.004018008894105575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c2,8 Panel B,(2) Q: 0.05,42,Bedrooms,bedrooms,A_structural,level,count,-0.001,0.004,,,,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.1,0.4,100*b/1 (per unit count),reported,-0.0010048992705163852,0.004019597082065541,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.25,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c3,8 Panel B,(3) Q: 0.25,42,Bedrooms,bedrooms,A_structural,level,count,-0.002,0.001,,,*,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,-0.2,0.1,100*b/1 (per unit count),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c4,8 Panel B,(4) Q: 0.50,42,Bedrooms,bedrooms,A_structural,level,count,-0.002,0.001,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,-0.2,0.1,100*b/1 (per unit count),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c5,8 Panel B,(5) Q: 0.75,42,Bedrooms,bedrooms,A_structural,level,count,-0.002,0.001,,,*,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,-0.2,0.1,100*b/1 (per unit count),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c6,8 Panel B,(6) Q: 0.95,42,Bedrooms,bedrooms,A_structural,level,count,-0.009,0.004,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,-0.8999999999999999,0.4,100*b/1 (per unit count),reported,-0.009043728139602736,0.004019434728712327,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.25,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c1,8 Panel B,(1) 2SLS,42,Bathrooms (Full),bathrooms,A_structural,level,count,0.008,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.8,0.1,100*b/1 (per unit count),reported,0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c2,8 Panel B,(2) Q: 0.05,42,Bathrooms (Full),bathrooms,A_structural,level,count,-0.007,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.7000000000000001,0.2,100*b/1 (per unit count),reported,-0.01406720483080051,0.004019201380228717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c3,8 Panel B,(3) Q: 0.25,42,Bathrooms (Full),bathrooms,A_structural,level,count,0.006,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.6,0.2,100*b/1 (per unit count),reported,0.012057920667875593,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c4,8 Panel B,(4) Q: 0.50,42,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.8999999999999999,0.2,100*b/1 (per unit count),reported,0.0180852376545314,0.004018941701006978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c5,8 Panel B,(5) Q: 0.75,42,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.8999999999999999,0.2,100*b/1 (per unit count),reported,0.0180852376545314,0.004018941701006978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c6,8 Panel B,(6) Q: 0.95,42,Bathrooms (Full),bathrooms,A_structural,level,count,0.014,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,1.4000000000000001,0.2,100*b/1 (per unit count),reported,0.028126062258739027,0.004018008894105575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c1,8 Panel B,(1) 2SLS,42,One story,storeys,A_structural,binary,binary,-0.077,0.006,,,***,,,high,One-story property =1,Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-7.412681226087625,0.5555339121638972,100*(exp(b - se^2/2) - 1),reported,-0.05151635835780875,0.004014261690218864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.833333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c2,8 Panel B,(2) Q: 0.05,42,One story,storeys,A_structural,binary,binary,-0.055,0.007,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-5.353804064857948,0.6625396035674387,100*(exp(b - se^2/2) - 1),reported,-0.03156682507514917,0.004017595918655349,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.857142857142857,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c3,8 Panel B,(3) Q: 0.25,42,One story,storeys,A_structural,binary,binary,-0.065,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-6.293441075564921,0.1874134926754807,100*(exp(b - se^2/2) - 1),reported,-0.12953631268868462,0.003985732698113373,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-32.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c4,8 Panel B,(4) Q: 0.50,42,One story,storeys,A_structural,binary,binary,-0.067,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-6.480666905175569,0.18703904026735532,100*(exp(b - se^2/2) - 1),reported,-0.133452102765036,0.003983644858657791,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-33.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c5,8 Panel B,(5) Q: 0.75,42,One story,storeys,A_structural,binary,binary,-0.072,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,-6.947096524872487,0.18610617916224115,100*(exp(b - se^2/2) - 1),reported,-0.14321390805417838,0.003978164112616067,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-36.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c6,8 Panel B,(6) Q: 0.95,42,One story,storeys,A_structural,binary,binary,-0.085,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-8.149184889452254,0.2755536853204372,100*(exp(b - se^2/2) - 1),reported,-0.11315714651535581,0.003993781641718441,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-28.333333333333336,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c1,8 Panel B,(1) 2SLS,42,Renovated,renovation,A_structural,binary,binary,-0.028,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-2.767046091538816,1.0696272034813716,100*(exp(b - se^2/2) - 1),reported,-0.010231171304026659,0.004019388726581901,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.545454545454546,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c2,8 Panel B,(2) Q: 0.05,42,Renovated,renovation,A_structural,binary,binary,-0.264,0.013,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-23.209135136571046,0.9983656015537179,100*(exp(b - se^2/2) - 1),reported,-0.0813581767257305,0.004006273853918546,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-20.30769230769231,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c3,8 Panel B,(3) Q: 0.25,42,Renovated,renovation,A_structural,binary,binary,-0.102,0.013,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-9.704675110440164,1.1739384171695397,100*(exp(b - se^2/2) - 1),reported,-0.03152271957060379,0.004017601513900484,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.846153846153846,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c4,8 Panel B,(4) Q: 0.50,42,Renovated,renovation,A_structural,binary,binary,0.021,0.007,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,2.1197032003755334,0.71485543614627,100*(exp(b - se^2/2) - 1),reported,0.012057920667875593,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c5,8 Panel B,(5) Q: 0.75,42,Renovated,renovation,A_structural,binary,binary,0.048,0.002,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,4.916855698525824,0.20983413106489415,100*(exp(b - se^2/2) - 1),reported,0.09602458544121234,0.004001024393383848,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c6,8 Panel B,(6) Q: 0.95,42,Renovated,renovation,A_structural,binary,binary,0.069,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,7.137138921851527,1.178579830063181,100*(exp(b - se^2/2) - 1),reported,0.025205838088994806,0.004018322014187577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.272727272727273,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c1,8 Panel B,(1) 2SLS,42,Fireplace,fireplace,B_interior,binary,binary,0.025,0.004,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,2.5306918036274606,0.41012604820977155,100*(exp(b - se^2/2) - 1),reported,0.025114570296134366,0.004018331247381499,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.25,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c2,8 Panel B,(2) Q: 0.05,42,Fireplace,fireplace,B_interior,binary,binary,0.045,0.007,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,4.600223254008573,0.7322195019361019,100*(exp(b - se^2/2) - 1),reported,0.02583165728432461,0.0040182577997838285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.428571428571428,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c3,8 Panel B,(3) Q: 0.25,42,Fireplace,fireplace,B_interior,binary,binary,0.025,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,2.5313069896238494,0.20506302410488578,100*(exp(b - se^2/2) - 1),reported,0.05018168551256579,0.004014534841005264,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c4,8 Panel B,(4) Q: 0.50,42,Fireplace,fireplace,B_interior,binary,binary,0.013,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,1.308284119210068,0.20261697347196184,100*(exp(b - se^2/2) - 1),reported,0.026118480976874945,0.004018227842596146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c5,8 Panel B,(5) Q: 0.75,42,Fireplace,fireplace,B_interior,binary,binary,0.01,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,1.004814698585399,0.20201003341683357,100*(exp(b - se^2/2) - 1),reported,0.020093937701409933,0.004018787540281986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c6,8 Panel B,(6) Q: 0.95,42,Fireplace,fireplace,B_interior,binary,binary,0.006,0.002,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,0.6016024020004895,0.20120360721081298,100*(exp(b - se^2/2) - 1),reported,0.012057920667875593,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c1,8 Panel B,(1) 2SLS,42,Lake/Mountain view,view,E_environment,binary,binary,0.062,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,IV,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,6.394904528184631,0.5319811723640169,100*(exp(b - se^2/2) - 1),reported,0.04978123090037987,0.004014615395191924,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.4,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c2,8 Panel B,(2) Q: 0.05,42,Lake/Mountain view,view,E_environment,binary,binary,0.035,0.006,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,3.560106781263417,0.621371825279774,100*(exp(b - se^2/2) - 1),reported,0.023441218462925982,0.004018494593644454,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.833333333333334,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c3,8 Panel B,(3) Q: 0.25,42,Lake/Mountain view,view,E_environment,binary,binary,0.037,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,3.768835123006986,0.31130790625144716,100*(exp(b - se^2/2) - 1),reported,0.04951424780807698,0.0040146687411954304,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.333333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c4,8 Panel B,(4) Q: 0.50,42,Lake/Mountain view,view,E_environment,binary,binary,0.046,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,4.706969913268955,0.3141223232870812,100*(exp(b - se^2/2) - 1),reported,0.06151712027689369,0.004011986105014805,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.333333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c5,8 Panel B,(5) Q: 0.75,42,Lake/Mountain view,view,E_environment,binary,binary,0.059,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,6.077046726231594,0.3182325722220477,100*(exp(b - se^2/2) - 1),reported,0.07880625986810323,0.00400709795939508,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.666666666666664,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T8B-c6,8 Panel B,(6) Q: 0.95,42,Lake/Mountain view,view,E_environment,binary,binary,0.106,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Robustness: high-priority 911 calls as IV; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,11.1812981967097,0.44472875060261235,100*(exp(b - se^2/2) - 1),reported,0.1059201662805985,0.003996987406815038,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c1,9 Panel A,(1) 2SLS,43,Living area,living_area,A_structural,level,1000 sqft,0.318,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.34229235125136914,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.391990818954096,0.0036980265939065655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),106.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c2,9 Panel A,(2) Q: 0.05,43,Living area,living_area,A_structural,level,1000 sqft,0.285,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.30677144687622704,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.22333715494345455,0.003918195700762361,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),56.99999999999999,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c3,9 Panel A,(3) Q: 0.25,43,Living area,living_area,A_structural,level,1000 sqft,0.306,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.32937565875131747,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.5238712347629869,0.003423994998450895,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),153.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c4,9 Panel A,(4) Q: 0.50,43,Living area,living_area,A_structural,level,1000 sqft,0.321,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.34552152437638206,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.39511380832191995,0.0036926524142235516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),107.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c5,9 Panel A,(5) Q: 0.75,43,Living area,living_area,A_structural,level,1000 sqft,0.339,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.3648965631264596,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.4135644276900801,0.003659862191947612,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),113.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c6,9 Panel A,(6) Q: 0.95,43,Living area,living_area,A_structural,level,1000 sqft,0.348,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.37458408250149827,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.2694273306786193,0.0038710823373364843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),69.6,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c1,9 Panel A,(1) 2SLS,43,Lot area,lot_size,A_structural,level,1000 sqft,0.022,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.023680602916761384,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.0880902506486793,0.004004102302212695,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c2,9 Panel A,(2) Q: 0.05,43,Lot area,lot_size,A_structural,level,1000 sqft,0.009,0.002,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.009687519375038749,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.018085821904466885,0.004019071534325974,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c3,9 Panel A,(3) Q: 0.25,43,Lot area,lot_size,A_structural,level,1000 sqft,0.014,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.015069474583393612,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.05618730353962703,0.004013378824259074,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c4,9 Panel A,(4) Q: 0.50,43,Lot area,lot_size,A_structural,level,1000 sqft,0.02,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.021527820833419444,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.080136026148505,0.004006801307425249,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c5,9 Panel A,(5) Q: 0.75,43,Lot area,lot_size,A_structural,level,1000 sqft,0.026,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.027986167083445278,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.10394679285959862,0.003997953571523024,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c6,9 Panel A,(6) Q: 0.95,43,Lot area,lot_size,A_structural,level,1000 sqft,0.038,0.002,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.04090285958349694,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.0761530691990343,0.0040080562736333845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c1,9 Panel A,(1) 2SLS,43,Bedrooms,bedrooms,A_structural,level,count,-0.019,0.002,,,***,,,high,,Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,-1.9,0.2,100*b/1 (per unit count),reported,-0.038159612029031974,0.0040168012662138925,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.5,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c2,9 Panel A,(2) Q: 0.05,43,Bedrooms,bedrooms,A_structural,level,count,-0.008,0.005,,,*,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.8,0.5,100*b/1 (per unit count),reported,-0.006431433396947985,0.00401964587309249,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c3,9 Panel A,(3) Q: 0.25,43,Bedrooms,bedrooms,A_structural,level,count,-0.011,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,-1.0999999999999999,0.2,100*b/1 (per unit count),reported,-0.022103108360402076,0.00401874697461856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.5,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c4,9 Panel A,(4) Q: 0.50,43,Bedrooms,bedrooms,A_structural,level,count,-0.013,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,-1.3,0.2,100*b/1 (per unit count),reported,-0.026119324443815584,0.004018357606740859,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.5,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c5,9 Panel A,(5) Q: 0.75,43,Bedrooms,bedrooms,A_structural,level,count,-0.014,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,-1.4000000000000001,0.2,100*b/1 (per unit count),reported,-0.028126970459270723,0.0040181386370386745,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c6,9 Panel A,(6) Q: 0.95,43,Bedrooms,bedrooms,A_structural,level,count,-0.018,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,-1.7999999999999998,0.3,100*b/1 (per unit count),reported,-0.024111362330324623,0.004018560388387438,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.999999999999999,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c1,9 Panel A,(1) 2SLS,43,Bathrooms (Full),bathrooms,A_structural,level,count,0.004,0.002,,,*,,,high,Number of full bathrooms,Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.4,0.2,100*b/1 (per unit count),reported,0.008039198223213907,0.004019599111606953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c2,9 Panel A,(2) Q: 0.05,43,Bathrooms (Full),bathrooms,A_structural,level,count,-0.009,0.004,,,**,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.8999999999999999,0.4,100*b/1 (per unit count),reported,-0.009044020372097315,0.0040195646098210285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.25,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c3,9 Panel A,(3) Q: 0.25,43,Bathrooms (Full),bathrooms,A_structural,level,count,0.003,0.002,,,,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.3,0.2,100*b/1 (per unit count),reported,0.006029483910021998,0.0040196559400146655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c4,9 Panel A,(4) Q: 0.50,43,Bathrooms (Full),bathrooms,A_structural,level,count,0.006,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.6,0.2,100*b/1 (per unit count),reported,0.012058310274023482,0.004019436758007827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c5,9 Panel A,(5) Q: 0.75,43,Bathrooms (Full),bathrooms,A_structural,level,count,0.005,0.002,,,**,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.5,0.2,100*b/1 (per unit count),reported,0.010048815125132005,0.004019526050052802,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c6,9 Panel A,(6) Q: 0.95,43,Bathrooms (Full),bathrooms,A_structural,level,count,0.011,0.004,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,1.0999999999999999,0.4,100*b/1 (per unit count),reported,0.011053579439794807,0.004019483432652657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.75,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c1,9 Panel A,(1) 2SLS,43,One story,storeys,A_structural,binary,binary,-0.092,0.007,,,***,,,high,One-story property =1,Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-8.791719675733011,0.6384736046815632,100*(exp(b - se^2/2) - 1),reported,-0.05275715055885089,0.004014131020782133,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.142857142857142,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c2,9 Panel A,(2) Q: 0.05,43,One story,storeys,A_structural,binary,binary,-0.063,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-6.106826303093326,0.4694717368445666,100*(exp(b - se^2/2) - 1),reported,-0.05058374634848155,0.004014583043530282,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.6,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c3,9 Panel A,(3) Q: 0.25,43,One story,storeys,A_structural,binary,binary,-0.073,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-7.040335316853019,0.27888024900773783,100*(exp(b - se^2/2) - 1),reported,-0.09734882384531506,0.0040006365963828104,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-24.333333333333332,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c4,9 Panel A,(4) Q: 0.50,43,One story,storeys,A_structural,binary,binary,-0.079,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-7.596423372521732,0.27721197733352604,100*(exp(b - se^2/2) - 1),reported,-0.10526476981695282,0.0039973963221627655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-26.333333333333332,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c5,9 Panel A,(5) Q: 0.75,43,One story,storeys,A_structural,binary,binary,-0.087,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,-8.332702940449666,0.2750031286899457,100*(exp(b - se^2/2) - 1),reported,-0.11578807020557912,0.003992692076054453,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-28.999999999999996,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c6,9 Panel A,(6) Q: 0.95,43,One story,storeys,A_structural,binary,binary,-0.099,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-9.426861368954098,0.45287135401177425,100*(exp(b - se^2/2) - 1),reported,-0.07933973559927165,0.004007057353498569,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-19.8,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c1,9 Panel A,(1) 2SLS,43,Renovated,renovation,A_structural,binary,binary,-0.046,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-4.501581610018701,1.0505461584097862,100*(exp(b - se^2/2) - 1),reported,-0.01680740140044642,0.0040191612044545785,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.181818181818182,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c2,9 Panel A,(2) Q: 0.05,43,Renovated,renovation,A_structural,binary,binary,-0.278,0.023,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-24.290345700695294,1.7417826894829715,100*(exp(b - se^2/2) - 1),reported,-0.04852904402159897,0.004014992850707827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.086956521739133,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,True
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c3,9 Panel A,(3) Q: 0.25,43,Renovated,renovation,A_structural,binary,binary,-0.11,0.014,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-10.425365214707583,1.2541677894151395,100*(exp(b - se^2/2) - 1),reported,-0.031567844169603475,0.004017725621585897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.857142857142857,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c4,9 Panel A,(4) Q: 0.50,43,Renovated,renovation,A_structural,binary,binary,-0.003,0.008,,,,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-0.30274081300222244,0.7976035964026984,100*(exp(b - se^2/2) - 1),reported,-0.0015073966656545604,0.004019724441745494,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.375,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c5,9 Panel A,(5) Q: 0.75,43,Renovated,renovation,A_structural,binary,binary,0.023,0.007,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,2.324146982410391,0.7162865776830524,100*(exp(b - se^2/2) - 1),reported,0.013206529186442002,0.004019378448047566,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2857142857142856,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c6,9 Panel A,(6) Q: 0.95,43,Renovated,renovation,A_structural,binary,binary,0.046,0.013,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,4.698593690729247,1.3611967342440183,100*(exp(b - se^2/2) - 1),reported,0.014222217899364332,0.004019322449820354,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5384615384615388,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c1,9 Panel A,(1) 2SLS,43,Fireplace,fireplace,B_interior,binary,binary,0.039,0.005,,,***,,,high,,Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,3.975748660034384,0.5198852418250789,100*(exp(b - se^2/2) - 1),reported,0.03133848614839422,0.0040177546344095155,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.8,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c2,9 Panel A,(2) Q: 0.05,43,Fireplace,fireplace,B_interior,binary,binary,0.062,0.007,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,6.393627796990686,0.7447736413096236,100*(exp(b - se^2/2) - 1),reported,0.035580770197988686,0.004017183732030981,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.857142857142858,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c3,9 Panel A,(3) Q: 0.25,43,Fireplace,fireplace,B_interior,binary,binary,0.038,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,3.8729155418109507,0.20774624657569954,100*(exp(b - se^2/2) - 1),reported,0.0761530691990343,0.0040080562736333845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.0,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c4,9 Panel A,(4) Q: 0.50,43,Fireplace,fireplace,B_interior,binary,binary,0.027,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,2.736574802993852,0.2054735605526979,100*(exp(b - se^2/2) - 1),reported,0.05418661492651993,0.004013823327890365,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.5,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c5,9 Panel A,(5) Q: 0.75,43,Fireplace,fireplace,B_interior,binary,binary,0.02,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,2.0200829926213304,0.10202013400267558,100*(exp(b - se^2/2) - 1),reported,0.080136026148505,0.004006801307425249,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.0,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c6,9 Panel A,(6) Q: 0.95,43,Fireplace,fireplace,B_interior,binary,binary,0.013,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,1.308284119210068,0.20261697347196184,100*(exp(b - se^2/2) - 1),reported,0.026119324443815584,0.004018357606740859,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.5,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c1,9 Panel A,(1) 2SLS,43,Lake/Mountain view,view,E_environment,binary,binary,0.109,0.006,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,11.51422775997968,0.6690974102048687,100*(exp(b - se^2/2) - 1),reported,0.07283114326220178,0.004009053757552391,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.166666666666668,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c2,9 Panel A,(2) Q: 0.05,43,Lake/Mountain view,view,E_environment,binary,binary,0.066,0.007,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,6.820054593202163,0.7477587020161953,100*(exp(b - se^2/2) - 1),reported,0.03787311075158865,0.004016845079713948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.428571428571429,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c3,9 Panel A,(3) Q: 0.25,43,Lake/Mountain view,view,E_environment,binary,binary,0.074,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,7.679819107623365,0.43072272219848795,100*(exp(b - se^2/2) - 1),reported,0.07416021078925239,0.004008660042662291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.5,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c4,9 Panel A,(4) Q: 0.50,43,Lake/Mountain view,view,E_environment,binary,binary,0.085,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,8.870835699670398,0.4354868266793595,100*(exp(b - se^2/2) - 1),reported,0.0851093079902839,0.004005143905425125,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.25,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c5,9 Panel A,(5) Q: 0.75,43,Lake/Mountain view,view,E_environment,binary,binary,0.106,0.006,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,11.180186389286773,0.6670931259039186,100*(exp(b - se^2/2) - 1),reported,0.07083681640948297,0.004009631117517905,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.666666666666664,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9A-c6,9 Panel A,(6) Q: 0.95,43,Lake/Mountain view,view,E_environment,binary,binary,0.18,0.009,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; no spatial adjustment; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,19.716887680045847,1.077495626809629,100*(exp(b - se^2/2) - 1),reported,0.080136026148505,0.004006801307425249,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.0,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c1,9 Panel B,(1) 2SLS,44,Living area,living_area,A_structural,level,1000 sqft,0.26,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.2798616708344528,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.25279584084198436,0.0038891667821843745,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),65.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c2,9 Panel B,(2) Q: 0.05,44,Living area,living_area,A_structural,level,1000 sqft,0.239,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.25725745895936236,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.1886914695379195,0.003947520283220073,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.8,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c3,9 Panel B,(3) Q: 0.25,44,Living area,living_area,A_structural,level,1000 sqft,0.25,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.269097760417743,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.44897560062781094,0.003591804805022488,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),125.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c4,9 Panel B,(4) Q: 0.50,44,Living area,living_area,A_structural,level,1000 sqft,0.267,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.2873964081261496,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.4728508565532898,0.0035419539816725827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),133.5,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c5,9 Panel B,(5) Q: 0.75,44,Living area,living_area,A_structural,level,1000 sqft,0.285,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.30677144687622704,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.35674728441121906,0.0037552345727496746,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),94.99999999999999,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c6,9 Panel B,(6) Q: 0.95,44,Living area,living_area,A_structural,level,1000 sqft,0.299,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.3218409214596207,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.23372210130125307,0.003908396342830319,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),59.8,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c1,9 Panel B,(1) 2SLS,44,Lot area,lot_size,A_structural,level,1000 sqft,0.019,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.02045142979174847,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.0761530691990343,0.0040080562736333845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c2,9 Panel B,(2) Q: 0.05,44,Lot area,lot_size,A_structural,level,1000 sqft,0.008,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.008611128333367779,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.03214121732666125,0.004017652165832657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c3,9 Panel B,(3) Q: 0.25,44,Lot area,lot_size,A_structural,level,1000 sqft,0.014,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.015069474583393612,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.05618730353962703,0.004013378824259074,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c5,9 Panel B,(5) Q: 0.75,44,Lot area,lot_size,A_structural,level,1000 sqft,0.022,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.023680602916761384,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.0880902506486793,0.004004102302212695,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c6,9 Panel B,(6) Q: 0.95,44,Lot area,lot_size,A_structural,level,1000 sqft,0.034,0.002,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.03659729541681306,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.0681763960061346,0.004010376235654978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.0,61888.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c1,9 Panel B,(1) 2SLS,44,Bedrooms,bedrooms,A_structural,level,count,-0.007,0.001,,,***,,,high,,Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,-0.7000000000000001,0.1,100*b/1 (per unit count),reported,-0.028126970459270723,0.0040181386370386745,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.0,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c2,9 Panel B,(2) Q: 0.05,44,Bedrooms,bedrooms,A_structural,level,count,0.0,0.005,,,,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.0,0.5,100*b/1 (per unit count),reported,0.0,0.004019729008652072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c3,9 Panel B,(3) Q: 0.25,44,Bedrooms,bedrooms,A_structural,level,count,-0.001,0.002,,,,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,-0.1,0.2,100*b/1 (per unit count),reported,-0.0020098604448589032,0.0040197208897178064,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c4,9 Panel B,(4) Q: 0.50,44,Bedrooms,bedrooms,A_structural,level,count,-0.002,0.001,,,,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,-0.2,0.1,100*b/1 (per unit count),reported,-0.008039198223213907,0.004019599111606953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c5,9 Panel B,(5) Q: 0.75,44,Bedrooms,bedrooms,A_structural,level,count,-0.003,0.001,,,*,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,-0.3,0.1,100*b/1 (per unit count),reported,-0.012058310274023482,0.004019436758007827,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c6,9 Panel B,(6) Q: 0.95,44,Bedrooms,bedrooms,A_structural,level,count,-0.008,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,-0.8,0.3,100*b/1 (per unit count),reported,-0.010718661571406801,0.004019498089277551,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6666666666666665,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c1,9 Panel B,(1) 2SLS,44,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.8999999999999999,0.1,100*b/1 (per unit count),reported,0.03615390940805667,0.004017101045339631,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.0,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c2,9 Panel B,(2) Q: 0.05,44,Bathrooms (Full),bathrooms,A_structural,level,count,-0.005,0.004,,,,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.5,0.4,100*b/1 (per unit count),reported,-0.005024597832650012,0.00401967826612001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.25,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c3,9 Panel B,(3) Q: 0.25,44,Bathrooms (Full),bathrooms,A_structural,level,count,0.007,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.7000000000000001,0.2,100*b/1 (per unit count),reported,0.014067659335510333,0.004019331238717238,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c4,9 Panel B,(4) Q: 0.50,44,Bathrooms (Full),bathrooms,A_structural,level,count,0.01,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,1.0,0.1,100*b/1 (per unit count),reported,0.04016485355453171,0.004016485355453171,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.0,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c5,9 Panel B,(5) Q: 0.75,44,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.8999999999999999,0.2,100*b/1 (per unit count),reported,0.018085821904466885,0.004019071534325974,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c6,9 Panel B,(6) Q: 0.95,44,Bathrooms (Full),bathrooms,A_structural,level,count,0.016,0.003,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,1.6,0.3,100*b/1 (per unit count),reported,0.021433629705920238,0.004018805569860045,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.333333333333333,61888.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c1,9 Panel B,(1) 2SLS,44,One story,storeys,A_structural,binary,binary,-0.076,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-7.319537857079251,0.4634081032796911,100*(exp(b - se^2/2) - 1),reported,-0.060986150367709005,0.004012246734717698,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.2,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c2,9 Panel B,(2) Q: 0.05,44,One story,storeys,A_structural,binary,binary,-0.054,0.004,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-5.257547292473596,0.37897284260071934,100*(exp(b - se^2/2) - 1),reported,-0.05418661492651993,0.004013823327890365,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.5,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c3,9 Panel B,(3) Q: 0.25,44,One story,storeys,A_structural,binary,binary,-0.063,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-6.105840419593623,0.18778869473782664,100*(exp(b - se^2/2) - 1),reported,-0.1256184481411094,0.003987887242574902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-31.5,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c4,9 Panel B,(4) Q: 0.50,44,One story,storeys,A_structural,binary,binary,-0.066,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-6.3873348287792115,0.28083925928748565,100*(exp(b - se^2/2) - 1),reported,-0.0880902506486793,0.004004102302212695,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.0,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c5,9 Panel B,(5) Q: 0.75,44,One story,storeys,A_structural,binary,binary,-0.072,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,-6.947329156840376,0.2791592687433617,100*(exp(b - se^2/2) - 1),reported,-0.09602765994967197,0.004001152497902999,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-23.999999999999996,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c6,9 Panel B,(6) Q: 0.95,44,One story,storeys,A_structural,binary,binary,-0.084,0.004,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-8.057609932550235,0.3677725024380499,100*(exp(b - se^2/2) - 1),reported,-0.08411514833833693,0.004005483254206521,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.0,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c1,9 Panel B,(1) 2SLS,44,Renovated,renovation,A_structural,binary,binary,-0.029,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,-2.864230445171767,1.0685581109132651,100*(exp(b - se^2/2) - 1),reported,-0.010596872355309931,0.004019503307186524,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6363636363636367,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c2,9 Panel B,(2) Q: 0.05,44,Renovated,renovation,A_structural,binary,binary,-0.265,0.016,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-23.28922461010582,1.2275295199613692,100*(exp(b - se^2/2) - 1),reported,-0.06642970081765222,0.004010849860688436,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.5625,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c3,9 Panel B,(3) Q: 0.25,44,Renovated,renovation,A_structural,binary,binary,-0.104,0.015,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-9.887608472190268,1.351837946131807,100*(exp(b - se^2/2) - 1),reported,-0.027859303458335576,0.004018168768029169,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.933333333333334,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c4,9 Panel B,(4) Q: 0.50,44,Renovated,renovation,A_structural,binary,binary,0.02,0.007,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,2.0176345400110485,0.714140938018729,100*(exp(b - se^2/2) - 1),reported,0.011484182645757235,0.004019463926015032,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.857142857142857,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c5,9 Panel B,(5) Q: 0.75,44,Renovated,renovation,A_structural,binary,binary,0.048,0.007,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,4.914495095829485,0.7344194587271295,100*(exp(b - se^2/2) - 1),reported,0.02755339097966279,0.004018202851200824,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.857142857142857,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c6,9 Panel B,(6) Q: 0.95,44,Renovated,renovation,A_structural,binary,binary,0.07,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,7.244329647203496,1.1797589993796382,100*(exp(b - se^2/2) - 1),reported,0.025571728741831924,0.004018414516573587,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.363636363636364,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c1,9 Panel B,(1) 2SLS,44,Fireplace,fireplace,B_interior,binary,binary,0.025,0.004,,,***,,,high,,Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,2.5306918036274606,0.41012604820977155,100*(exp(b - se^2/2) - 1),reported,0.02511538138465511,0.004018461021544817,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.25,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c2,9 Panel B,(2) Q: 0.05,44,Fireplace,fireplace,B_interior,binary,binary,0.043,0.006,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,4.391910413762212,0.6263627369103676,100*(exp(b - se^2/2) - 1),reported,0.028796111366565316,0.004018062051148649,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.166666666666666,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c3,9 Panel B,(3) Q: 0.25,44,Fireplace,fireplace,B_interior,binary,binary,0.024,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,2.4285708594562028,0.30728709536718646,100*(exp(b - se^2/2) - 1),reported,0.03214121732666125,0.004017652165832657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c4,9 Panel B,(4) Q: 0.50,44,Fireplace,fireplace,B_interior,binary,binary,0.012,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,1.2070264723524238,0.20241445777321557,100*(exp(b - se^2/2) - 1),reported,0.024111362330324626,0.004018560388387438,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c5,9 Panel B,(5) Q: 0.75,44,Fireplace,fireplace,B_interior,binary,binary,0.01,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,1.004814698585399,0.20201003341683357,100*(exp(b - se^2/2) - 1),reported,0.020094586793302126,0.0040189173586604255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c6,9 Panel B,(6) Q: 0.95,44,Fireplace,fireplace,B_interior,binary,binary,0.007,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,0.7022543219748156,0.20140491145336972,100*(exp(b - se^2/2) - 1),reported,0.014067659335510333,0.004019331238717238,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c1,9 Panel B,(1) 2SLS,44,Lake/Mountain view,view,E_environment,binary,binary,0.065,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,IV,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; 2SLS; SE clustered by year and month,pct_premium,6.714568497975937,0.5335795121920963,100*(exp(b - se^2/2) - 1),reported,0.05218527349774073,0.004014251807518518,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c2,9 Panel B,(2) Q: 0.05,44,Lake/Mountain view,view,E_environment,binary,binary,0.04,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,4.079776413902381,0.5204053870961941,100*(exp(b - se^2/2) - 1),reported,0.03214121732666125,0.004017652165832657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.0,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c3,9 Panel B,(3) Q: 0.25,44,Lake/Mountain view,view,E_environment,binary,binary,0.039,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,3.976580469350899,0.3119311450950473,100*(exp(b - se^2/2) - 1),reported,0.05218527349774073,0.004014251807518518,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.0,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c4,9 Panel B,(4) Q: 0.50,44,Lake/Mountain view,view,E_environment,binary,binary,0.048,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,4.916226199280138,0.4196682621297883,100*(exp(b - se^2/2) - 1),reported,0.04818072760193375,0.004015060633494479,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c5,9 Panel B,(5) Q: 0.75,44,Lake/Mountain view,view,E_environment,binary,binary,0.063,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,6.501831905067235,0.4260107356925221,100*(exp(b - se^2/2) - 1),reported,0.06318422946770427,0.0040116971090605885,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.75,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T9B-c6,9 Panel B,(6) Q: 0.95,44,Lake/Mountain view,view,E_environment,binary,binary,0.11,0.008,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61898.0,,se,Robustness: adds distance to crime coldspot; with spatial lag of neighbour prices; year + month dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,11.624235013214479,0.893022456367097,100*(exp(b - se^2/2) - 1),reported,0.05518704232369077,0.0040136030780866016,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.75,61888.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c1,11 Panel A,(1) 2SLS,47,Living area,living_area,A_structural,level,1000 sqft,0.288,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.31000062000123996,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.27800263889251203,0.003861147762396,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),72.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c2,11 Panel A,(2) Q: 0.05,47,Living area,living_area,A_structural,level,1000 sqft,0.255,0.006,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.2744797156260979,0.006458346250025833,100*b/92.903 (X per 1000sqft->m2),reported,0.16839344410959117,0.003962198684931557,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),42.5,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c3,11 Panel A,(3) Q: 0.25,47,Living area,living_area,A_structural,level,1000 sqft,0.28,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.30138949166787227,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.3512568944782872,0.0037634667265530755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),93.33333333333334,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c4,11 Panel A,(4) Q: 0.50,47,Living area,living_area,A_structural,level,1000 sqft,0.294,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.3164589662512658,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.5087114308842847,0.0034606219788046576,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),147.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c5,11 Panel A,(5) Q: 0.75,47,Living area,living_area,A_structural,level,1000 sqft,0.306,0.003,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.32937565875131747,0.0032291731250129164,100*b/92.903 (X per 1000sqft->m2),reported,0.3793525756781874,0.0037191428988057585,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),102.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c6,11 Panel A,(6) Q: 0.95,47,Living area,living_area,A_structural,level,1000 sqft,0.312,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.3358340050013433,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.2991691448646159,0.0038355018572386653,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),78.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c1,11 Panel A,(1) 2SLS,47,Lot area,lot_size,A_structural,level,1000 sqft,0.026,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.027986167083445278,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.10394347012419862,0.003997825774007639,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c2,11 Panel A,(2) Q: 0.05,47,Lot area,lot_size,A_structural,level,1000 sqft,0.016,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.017222256666735557,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.06418098885674876,0.004011311803546798,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c3,11 Panel A,(3) Q: 0.25,47,Lot area,lot_size,A_structural,level,1000 sqft,0.021,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.022604211875090416,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.08411244939884005,0.004005354733278097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c4,11 Panel A,(4) Q: 0.50,47,Lot area,lot_size,A_structural,level,1000 sqft,0.024,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.02583338500010333,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.09602458544121234,0.004001024393383848,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c5,11 Panel A,(5) Q: 0.75,47,Lot area,lot_size,A_structural,level,1000 sqft,0.03,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.032291731250129165,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.11972065843265513,0.003990688614421837,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),30.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c6,11 Panel A,(6) Q: 0.95,47,Lot area,lot_size,A_structural,level,1000 sqft,0.041,0.002,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.044132032708509863,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.08212344218496902,0.004006021569998489,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),20.5,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c1,11 Panel A,(1) 2SLS,47,Bedrooms,bedrooms,A_structural,level,count,-0.016,0.002,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; 2SLS; SE clustered by year and month,semi_elasticity,-1.6,0.2,100*b/1 (per unit count),reported,-0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c2,11 Panel A,(2) Q: 0.05,47,Bedrooms,bedrooms,A_structural,level,count,-0.003,0.003,,,,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.3,0.3,100*b/1 (per unit count),reported,-0.004019566639313255,0.004019566639313255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c3,11 Panel A,(3) Q: 0.25,47,Bedrooms,bedrooms,A_structural,level,count,-0.009,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,-0.8999999999999999,0.2,100*b/1 (per unit count),reported,-0.0180852376545314,0.004018941701006978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c4,11 Panel A,(4) Q: 0.50,47,Bedrooms,bedrooms,A_structural,level,count,-0.01,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,-1.0,0.2,100*b/1 (per unit count),reported,-0.020093937701409933,0.004018787540281986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c5,11 Panel A,(5) Q: 0.75,47,Bedrooms,bedrooms,A_structural,level,count,-0.011,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,-1.0999999999999999,0.1,100*b/1 (per unit count),reported,-0.04417243235155397,0.0040156756683230885,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c6,11 Panel A,(6) Q: 0.95,47,Bedrooms,bedrooms,A_structural,level,count,-0.017,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,-1.7000000000000002,0.3,100*b/1 (per unit count),reported,-0.02277182177096999,0.004018556783112351,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.666666666666667,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c1,11 Panel A,(1) 2SLS,47,Bathrooms (Full),bathrooms,A_structural,level,count,0.007,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,IV,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.7000000000000001,0.2,100*b/1 (per unit count),reported,0.01406720483080051,0.004019201380228717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c2,11 Panel A,(2) Q: 0.05,47,Bathrooms (Full),bathrooms,A_structural,level,count,0.001,0.004,,,,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.1,0.4,100*b/1 (per unit count),reported,0.0010048992705163852,0.004019597082065541,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.25,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c3,11 Panel A,(3) Q: 0.25,47,Bathrooms (Full),bathrooms,A_structural,level,count,0.006,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.6,0.2,100*b/1 (per unit count),reported,0.012057920667875593,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c4,11 Panel A,(4) Q: 0.50,47,Bathrooms (Full),bathrooms,A_structural,level,count,0.008,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.8,0.2,100*b/1 (per unit count),reported,0.01607631859730484,0.00401907964932621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c5,11 Panel A,(5) Q: 0.75,47,Bathrooms (Full),bathrooms,A_structural,level,count,0.008,0.003,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.8,0.3,100*b/1 (per unit count),reported,0.010718315238978177,0.004019368214616816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6666666666666665,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c6,11 Panel A,(6) Q: 0.95,47,Bathrooms (Full),bathrooms,A_structural,level,count,0.013,0.004,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,1.3,0.4,100*b/1 (per unit count),reported,0.0130625825289168,0.004019256162743631,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.25,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c1,11 Panel A,(1) 2SLS,47,One story,storeys,A_structural,binary,binary,-0.076,0.006,,,***,,,high,One-story property =1,Log (Sale Price),log,IV,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; 2SLS; SE clustered by year and month,pct_premium,-7.320047598219248,0.5560897239356293,100*(exp(b - se^2/2) - 1),reported,-0.050849055990756155,0.00401439915716496,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.666666666666666,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c2,11 Panel A,(2) Q: 0.05,47,One story,storeys,A_structural,binary,binary,-0.053,0.006,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-5.163705820428987,0.5690280074893789,100*(exp(b - se^2/2) - 1),reported,-0.035484098310227835,0.0040170677332333395,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.833333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c3,11 Panel A,(3) Q: 0.25,47,One story,storeys,A_structural,binary,binary,-0.058,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-5.635429897841049,0.28309498423103957,100*(exp(b - se^2/2) - 1),reported,-0.07747864737192982,0.004007516243375681,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-19.333333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c4,11 Panel A,(4) Q: 0.50,47,One story,storeys,A_structural,binary,binary,-0.065,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-6.2936753416694025,0.28112023901322103,100*(exp(b - se^2/2) - 1),reported,-0.08676289187188262,0.004004441163317659,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.666666666666668,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c5,11 Panel A,(5) Q: 0.75,47,One story,storeys,A_structural,binary,binary,-0.075,0.004,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,-7.226393558965006,0.3710973945314211,100*(exp(b - se^2/2) - 1),reported,-0.07515433759809606,0.004008231338565123,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-18.75,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c6,11 Panel A,(6) Q: 0.95,47,One story,storeys,A_structural,binary,binary,-0.086,0.004,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-8.241310950433578,0.3670376924880604,100*(exp(b - se^2/2) - 1),reported,-0.086100451724248,0.004004672173220838,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.499999999999996,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c1,11 Panel A,(1) 2SLS,47,Renovated,renovation,A_structural,binary,binary,-0.033,0.011,,,***,,,high,Previously renovated =1,Log (Sale Price),log,IV,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; 2SLS; SE clustered by year and month,pct_premium,-3.2519974723142275,1.0642924155479352,100*(exp(b - se^2/2) - 1),reported,-0.012057920667875595,0.004019306889291864,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0000000000000004,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c2,11 Panel A,(2) Q: 0.05,47,Renovated,renovation,A_structural,binary,binary,-0.265,0.015,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-23.288035583872347,1.1508089249637834,100*(exp(b - se^2/2) - 1),reported,-0.07083453881226438,0.0040095021969206255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-17.666666666666668,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c3,11 Panel A,(3) Q: 0.25,47,Renovated,renovation,A_structural,binary,binary,-0.106,0.01,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-10.06203220322176,0.899424648075924,100*(exp(b - se^2/2) - 1),reported,-0.04256912767268908,0.004015955440819725,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.6,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c4,11 Panel A,(4) Q: 0.50,47,Renovated,renovation,A_structural,binary,binary,0.018,0.009,,,**,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,1.8121741624259613,0.9163466787508142,100*(exp(b - se^2/2) - 1),reported,0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c5,11 Panel A,(5) Q: 0.75,47,Renovated,renovation,A_structural,binary,binary,0.041,0.004,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,4.184377076197432,0.4167408422181918,100*(exp(b - se^2/2) - 1),reported,0.041165965819615624,0.004016191787279573,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.25,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c6,11 Panel A,(6) Q: 0.95,47,Renovated,renovation,A_structural,binary,binary,0.052,0.009,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,5.333308165968109,0.9480381682620282,100*(exp(b - se^2/2) - 1),reported,0.02321808969094556,0.004018515523432886,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.777777777777778,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c1,11 Panel A,(1) 2SLS,47,Fireplace,fireplace,B_interior,binary,binary,0.02,0.005,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; 2SLS; SE clustered by year and month,pct_premium,2.018858758970832,0.5101006700133779,100*(exp(b - se^2/2) - 1),reported,0.01607631859730484,0.00401907964932621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c2,11 Panel A,(2) Q: 0.05,47,Fireplace,fireplace,B_interior,binary,binary,0.036,0.005,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,3.6642888373831006,0.5183279232454618,100*(exp(b - se^2/2) - 1),reported,0.028929000846614854,0.004017916784252063,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.199999999999999,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c3,11 Panel A,(3) Q: 0.25,47,Fireplace,fireplace,B_interior,binary,binary,0.021,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,2.1220009195467737,0.2042444103275057,100*(exp(b - se^2/2) - 1),reported,0.04216824962463218,0.004016023773774493,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c4,11 Panel A,(4) Q: 0.50,47,Fireplace,fireplace,B_interior,binary,binary,0.014,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,1.4096430743602673,0.20281969178769846,100*(exp(b - se^2/2) - 1),reported,0.028126062258739027,0.004018008894105575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c5,11 Panel A,(5) Q: 0.75,47,Fireplace,fireplace,B_interior,binary,binary,0.006,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,0.6017533045172607,0.10060180360540649,100*(exp(b - se^2/2) - 1),reported,0.024110583627583122,0.0040184306045971865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c6,11 Panel A,(6) Q: 0.95,47,Fireplace,fireplace,B_interior,binary,binary,-0.006,0.003,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-0.5986509016838615,0.29820538921618056,100*(exp(b - se^2/2) - 1),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,True
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c1,11 Panel A,(1) 2SLS,47,Lake/Mountain view,view,E_environment,binary,binary,0.14,0.006,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,IV,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; 2SLS; SE clustered by year and month,pct_premium,15.025309411519117,0.6901642793143364,100*(exp(b - se^2/2) - 1),reported,0.09338082437105044,0.004002035330187876,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.333333333333336,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c2,11 Panel A,(2) Q: 0.05,47,Lake/Mountain view,view,E_environment,binary,binary,0.094,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,9.855095747436016,0.4394238983668695,100*(exp(b - se^2/2) - 1),reported,0.09404195206802067,0.004001785194383859,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c3,11 Panel A,(3) Q: 0.25,47,Lake/Mountain view,view,E_environment,binary,binary,0.107,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,11.292924628644885,0.33388027634379774,100*(exp(b - se^2/2) - 1),reported,0.1419146820560218,0.003978916319327714,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.666666666666664,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c4,11 Panel A,(4) Q: 0.50,47,Lake/Mountain view,view,E_environment,binary,binary,0.114,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,12.07470815109386,0.3362256374652459,100*(exp(b - se^2/2) - 1),reported,0.15099350992814012,0.003973513419161582,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),38.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c5,11 Panel A,(5) Q: 0.75,47,Lake/Mountain view,view,E_environment,binary,binary,0.138,0.006,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,14.795488690024472,0.6887853301645072,100*(exp(b - se^2/2) - 1),reported,0.09205819917863656,0.004002530399071154,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11A-c6,11 Panel A,(6) Q: 0.95,47,Lake/Mountain view,view,E_environment,binary,binary,0.211,0.01,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: baseline with zip code fixed effects; no spatial adjustment; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,23.485061098725613,1.2349123550613943,100*(exp(b - se^2/2) - 1),reported,0.08451013099345056,0.0040052194783625865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.099999999999998,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c1,11 Panel B,(1) 2SLS,48,Living area,living_area,A_structural,level,1000 sqft,0.256,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.2755561066677689,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.2491423124624276,0.0038928486322254313,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),64.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c2,11 Panel B,(2) Q: 0.05,48,Living area,living_area,A_structural,level,1000 sqft,0.231,0.005,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.2486463306259946,0.005381955208354861,100*b/92.903 (X per 1000sqft->m2),reported,0.18258382379806556,0.003952030818139948,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),46.2,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c3,11 Panel B,(3) Q: 0.25,48,Living area,living_area,A_structural,level,1000 sqft,0.249,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.26802136937607207,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.4475284146859931,0.0035946057404497435,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),124.5,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c4,11 Panel B,(4) Q: 0.50,48,Living area,living_area,A_structural,level,1000 sqft,0.265,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.2852436260428076,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.4700820959868574,0.0035477894036743955,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),132.5,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c5,11 Panel B,(5) Q: 0.75,48,Living area,living_area,A_structural,level,1000 sqft,0.281,0.002,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.3024658827095432,0.0021527820833419447,100*b/92.903 (X per 1000sqft->m2),reported,0.49175121401230815,0.0035000086406569977,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),140.5,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c6,11 Panel B,(6) Q: 0.95,48,Living area,living_area,A_structural,level,1000 sqft,0.29,0.004,,,***,,,high,"Total living area; Table 10 says ft2 but summary stats (mean 1.891, max 4.59) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.3121534020845819,0.004305564166683889,100*b/92.903 (X per 1000sqft->m2),reported,0.27978257133473344,0.0038590699494445986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),72.5,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c1,11 Panel B,(1) 2SLS,48,Lot area,lot_size,A_structural,level,1000 sqft,0.023,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,IV,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.02475699395843236,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.09205819917863656,0.004002530399071154,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c2,11 Panel B,(2) Q: 0.05,48,Lot area,lot_size,A_structural,level,1000 sqft,0.012,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.012916692500051665,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.04817917426179949,0.004014931188483291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c3,11 Panel B,(3) Q: 0.25,48,Lot area,lot_size,A_structural,level,1000 sqft,0.018,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.019375038750077497,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.07216414361374496,0.0040091190896524975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c4,11 Panel B,(4) Q: 0.50,48,Lot area,lot_size,A_structural,level,1000 sqft,0.022,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,0.023680602916761384,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.08808742611158363,0.004003973914162892,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c6,11 Panel B,(6) Q: 0.95,48,Lot area,lot_size,A_structural,level,1000 sqft,0.038,0.001,,,***,,,high,"Total lot area; Table 10 says ft2 but summary stats (mean 4.66, max 14.47) imply thousands of sq ft",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,0.04090285958349694,0.0010763910416709723,100*b/92.903 (X per 1000sqft->m2),reported,0.15099350992814012,0.003973513419161582,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),38.0,61892.0,1000sqft,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c1,11 Panel B,(1) 2SLS,48,Bedrooms,bedrooms,A_structural,level,count,-0.008,0.001,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; 2SLS; SE clustered by year and month,semi_elasticity,-0.8,0.1,100*b/1 (per unit count),reported,-0.03214017976012635,0.004017522470015793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c2,11 Panel B,(2) Q: 0.05,48,Bedrooms,bedrooms,A_structural,level,count,-0.001,0.004,,,,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,-0.1,0.4,100*b/1 (per unit count),reported,-0.0010048992705163852,0.004019597082065541,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.25,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c3,11 Panel B,(3) Q: 0.25,48,Bedrooms,bedrooms,A_structural,level,count,-0.002,0.001,,,**,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,-0.2,0.1,100*b/1 (per unit count),reported,-0.008038938454307684,0.004019469227153842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c4,11 Panel B,(4) Q: 0.50,48,Bedrooms,bedrooms,A_structural,level,count,-0.003,0.002,,,*,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,-0.3,0.2,100*b/1 (per unit count),reported,-0.006029289075079203,0.004019526050052801,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c5,11 Panel B,(5) Q: 0.75,48,Bedrooms,bedrooms,A_structural,level,count,-0.004,0.001,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,-0.4,0.1,100*b/1 (per unit count),reported,-0.01607631859730484,0.00401907964932621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c6,11 Panel B,(6) Q: 0.95,48,Bedrooms,bedrooms,A_structural,level,count,-0.008,0.003,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,-0.8,0.3,100*b/1 (per unit count),reported,-0.010718315238978177,0.004019368214616816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6666666666666665,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c1,11 Panel B,(1) 2SLS,48,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.001,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,IV,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; 2SLS; SE clustered by year and month,semi_elasticity,0.8999999999999999,0.1,100*b/1 (per unit count),reported,0.03615274262598033,0.004016971402886703,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c2,11 Panel B,(2) Q: 0.05,48,Bathrooms (Full),bathrooms,A_structural,level,count,0.0,0.004,,,,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,semi_elasticity,0.0,0.4,100*b/1 (per unit count),reported,0.0,0.004019599111606953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c3,11 Panel B,(3) Q: 0.25,48,Bathrooms (Full),bathrooms,A_structural,level,count,0.008,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,semi_elasticity,0.8,0.2,100*b/1 (per unit count),reported,0.01607631859730484,0.00401907964932621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c4,11 Panel B,(4) Q: 0.50,48,Bathrooms (Full),bathrooms,A_structural,level,count,0.01,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,semi_elasticity,1.0,0.2,100*b/1 (per unit count),reported,0.020093937701409933,0.004018787540281986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c5,11 Panel B,(5) Q: 0.75,48,Bathrooms (Full),bathrooms,A_structural,level,count,0.009,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,semi_elasticity,0.8999999999999999,0.2,100*b/1 (per unit count),reported,0.0180852376545314,0.004018941701006978,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c6,11 Panel B,(6) Q: 0.95,48,Bathrooms (Full),bathrooms,A_structural,level,count,0.015,0.002,,,***,,,high,Number of full bathrooms,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,semi_elasticity,1.5,0.2,100*b/1 (per unit count),reported,0.030133303253020185,0.004017773767069358,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.5,61892.0,count,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c1,11 Panel B,(1) 2SLS,48,One story,storeys,A_structural,binary,binary,-0.07,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,IV,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; 2SLS; SE clustered by year and month,pct_premium,-6.761783494395768,0.46619690995297414,100*(exp(b - se^2/2) - 1),reported,-0.05618549358573801,0.004013249541838429,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.000000000000002,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c2,11 Panel B,(2) Q: 0.05,48,One story,storeys,A_structural,binary,binary,-0.054,0.005,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-5.257973632551516,0.47371605325089916,100*(exp(b - se^2/2) - 1),reported,-0.043370821899063806,0.004015816842505908,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.799999999999999,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c3,11 Panel B,(3) Q: 0.25,48,One story,storeys,A_structural,binary,binary,-0.058,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-5.635429897841049,0.28309498423103957,100*(exp(b - se^2/2) - 1),reported,-0.07747864737192982,0.004007516243375681,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-19.333333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c4,11 Panel B,(4) Q: 0.50,48,One story,storeys,A_structural,binary,binary,-0.06,0.003,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,-5.823970434661707,0.2825293600752746,100*(exp(b - se^2/2) - 1),reported,-0.08013345319170002,0.004006672659585001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-20.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c5,11 Panel B,(5) Q: 0.75,48,One story,storeys,A_structural,binary,binary,-0.067,0.002,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,-6.480666905175569,0.18703904026735532,100*(exp(b - se^2/2) - 1),reported,-0.133452102765036,0.003983644858657791,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-33.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c6,11 Panel B,(6) Q: 0.95,48,One story,storeys,A_structural,binary,binary,-0.08,0.004,,,***,,,high,One-story property =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-7.689103851459567,0.36924653855465434,100*(exp(b - se^2/2) - 1),reported,-0.08013345319170002,0.004006672659585001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-20.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c1,11 Panel B,(1) 2SLS,48,Renovated,renovation,A_structural,binary,binary,-0.025,0.011,,,**,,,high,Previously renovated =1,Log (Sale Price),log,IV,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; 2SLS; SE clustered by year and month,pct_premium,-2.4749092436441966,1.0728409032311659,100*(exp(b - se^2/2) - 1),reported,-0.009135071343824115,0.00401943139128261,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.272727272727273,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c2,11 Panel B,(2) Q: 0.05,48,Renovated,renovation,A_structural,binary,binary,-0.258,0.013,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,-22.74700494320011,1.0043738017390065,100*(exp(b - se^2/2) - 1),reported,-0.07952095495207298,0.004006869823166468,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-19.846153846153847,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c3,11 Panel B,(3) Q: 0.25,48,Renovated,renovation,A_structural,binary,binary,-0.102,0.014,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,-9.705894089098043,1.2642413723364274,100*(exp(b - se^2/2) - 1),reported,-0.029273100333129874,0.004017876516311944,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.285714285714285,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c4,11 Panel B,(4) Q: 0.50,48,Renovated,renovation,A_structural,binary,binary,0.028,0.008,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,2.8362776286056546,0.8227165475371401,100*(exp(b - se^2/2) - 1),reported,0.01406720483080051,0.004019201380228717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c5,11 Panel B,(5) Q: 0.75,48,Renovated,renovation,A_structural,binary,binary,0.053,0.003,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,5.4424900196629045,0.3163288935358068,100*(exp(b - se^2/2) - 1),reported,0.07083453881226437,0.0040095021969206255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.666666666666664,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c6,11 Panel B,(6) Q: 0.95,48,Renovated,renovation,A_structural,binary,binary,0.067,0.007,,,***,,,high,Previously renovated =1,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,6.926928075630467,0.7485068347222201,100*(exp(b - se^2/2) - 1),reported,0.03844486335150914,0.0040166275143367755,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.571428571428571,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c1,11 Panel B,(1) 2SLS,48,Fireplace,fireplace,B_interior,binary,binary,0.016,0.004,,,***,,,high,,Log (Sale Price),log,IV,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; 2SLS; SE clustered by year and month,pct_premium,1.6120556409127573,0.406451474162438,100*(exp(b - se^2/2) - 1),reported,0.01607631859730484,0.00401907964932621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c2,11 Panel B,(2) Q: 0.05,48,Fireplace,fireplace,B_interior,binary,binary,0.032,0.005,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,3.250459891696722,0.5162587526525592,100*(exp(b - se^2/2) - 1),reported,0.025716926017020324,0.004018269690159425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.4,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c3,11 Panel B,(3) Q: 0.25,48,Fireplace,fireplace,B_interior,binary,binary,0.015,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,1.511103439161987,0.20302261292314377,100*(exp(b - se^2/2) - 1),reported,0.030133303253020185,0.004017773767069358,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c4,11 Panel B,(4) Q: 0.50,48,Fireplace,fireplace,B_interior,binary,binary,0.008,0.002,,,***,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,0.8030069442118482,0.2016064171008547,100*(exp(b - se^2/2) - 1),reported,0.01607631859730484,0.00401907964932621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c5,11 Panel B,(5) Q: 0.75,48,Fireplace,fireplace,B_interior,binary,binary,0.002,0.002,,,,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,0.1999997332001513,0.20040040026680006,100*(exp(b - se^2/2) - 1),reported,0.004019566639313255,0.004019566639313255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c6,11 Panel B,(6) Q: 0.95,48,Fireplace,fireplace,B_interior,binary,binary,-0.001,0.004,,,,,,high,,Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,-0.10074921386556968,0.39960019993335,100*(exp(b - se^2/2) - 1),reported,-0.0010048992705163852,0.004019597082065541,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.25,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,True
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c1,11 Panel B,(1) 2SLS,48,Lake/Mountain view,view,E_environment,binary,binary,0.095,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,IV,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; 2SLS; SE clustered by year and month,pct_premium,9.964510947632444,0.5498294275630514,100*(exp(b - se^2/2) - 1),reported,0.0761506225926853,0.004007927504878174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,iv,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c2,11 Panel B,(2) Q: 0.05,48,Lake/Mountain view,view,E_environment,binary,binary,0.059,0.005,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.05; SE bootstrap,pct_premium,6.07619811325224,0.5303876203700795,100*(exp(b - se^2/2) - 1),reported,0.04737800570765221,0.004015085229462052,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.799999999999999,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c3,11 Panel B,(3) Q: 0.25,48,Lake/Mountain view,view,E_environment,binary,binary,0.066,0.003,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.25; SE bootstrap,pct_premium,6.822191015658174,0.320468015149798,100*(exp(b - se^2/2) - 1),reported,0.08808742611158363,0.004003973914162892,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c4,11 Panel B,(4) Q: 0.50,48,Lake/Mountain view,view,E_environment,binary,binary,0.076,0.002,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.50; SE bootstrap,pct_premium,7.89604162342934,0.21579251483145678,100*(exp(b - se^2/2) - 1),reported,0.15099350992814012,0.003973513419161582,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),38.0,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c5,11 Panel B,(5) Q: 0.75,48,Lake/Mountain view,view,E_environment,binary,binary,0.094,0.004,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.75; SE bootstrap,pct_premium,9.855095747436016,0.4394238983668695,100*(exp(b - se^2/2) - 1),reported,0.09404195206802067,0.004001785194383859,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.5,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a,d3812508998e06d0728e9af8b9c2c72e4dad465a:T11B-c6,11 Panel B,(6) Q: 0.95,48,Lake/Mountain view,view,E_environment,binary,binary,0.158,0.006,,,***,,,high,"Natural view (Mt Rainier, Cascades, Puget Sound, Lake Washington, Olympics) =1",Log (Sale Price),log,quantile,61902.0,,se,Appendix 2: zip code fixed effects plus spatial lag of neighbour prices; year + month + zip dummies; quantile regression at tau=0.95; SE bootstrap,pct_premium,17.11451139058926,0.7026997168246017,100*(exp(b - se^2/2) - 1),reported,0.10526140588935778,0.003997268578076878,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.333333333333332,61892.0,binary,,2025.0,United States,North America,High income,2008.0,2020.0,single_family,transaction,journal,True,False,clustered,,2014.0,quantile,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c1,2,Model 1,9,Age,age,A_structural,level,years,-0.007867,,-12.55,,***,,,high,Age of house in years; quadratic with Age_2,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7798,t,All sales; neighbourhood fixed effects; coastal specification: log coastal distance,semi_elasticity,-0.7867000000000001,0.06268525896414343,100*b/1 (per year),|b/t|,-0.12611630712227637,0.010049108137233176,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.55,9745.0,years,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,Age,age,A_structural,level,years,-0.007734,,-12.18,,***,,,high,Age of house in years; quadratic with Age_2,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,semi_elasticity,-0.7734000000000001,0.06349753694581281,100*b/1 (per year),|b/t|,-0.12245472543033066,0.010053754140421237,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.18,9745.0,years,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Age,age,A_structural,level,years,-0.007778,,-12.36,,***,,,high,Age of house in years; quadratic with Age_2,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,semi_elasticity,-0.7778,0.06292880258899677,100*b/1 (per year),|b/t|,-0.1242366695759682,0.010051510483492572,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.36,9745.0,years,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c1,2,Model 1,9,Bedrooms,bedrooms,A_structural,level,count,0.002218,,0.63,,,,,high,,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7798,t,All sales; neighbourhood fixed effects; coastal specification: log coastal distance,semi_elasticity,0.2218,0.3520634920634921,100*b/1 (per unit count),|b/t|,0.00638176464692709,0.010129785153852523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.63,9745.0,count,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,Bedrooms,bedrooms,A_structural,level,count,0.00225,,0.64,,,,,high,,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,semi_elasticity,0.22499999999999998,0.35156249999999994,100*b/1 (per unit count),|b/t|,0.006483058274173157,0.010129778553395558,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.64,9745.0,count,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Bedrooms,bedrooms,A_structural,level,count,0.00354,,1.01,,,,,high,,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,semi_elasticity,0.35400000000000004,0.35049504950495053,100*b/1 (per unit count),|b/t|,0.0102307558917183,0.01012946127892901,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.01,9745.0,count,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c1,2,Model 1,9,Bathrooms,bathrooms,A_structural,level,count,0.042084,,8.05,,***,,,high,,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7798,t,All sales; neighbourhood fixed effects; coastal specification: log coastal distance,semi_elasticity,4.2084,0.5227826086956522,100*b/1 (per unit count),|b/t|,0.08127664130856393,0.010096477181188066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.05,9745.0,count,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,Bathrooms,bathrooms,A_structural,level,count,0.045153,,8.55,,***,,,high,,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,semi_elasticity,4.5153,0.5281052631578946,100*b/1 (per unit count),|b/t|,0.08628838364162472,0.010092208613055523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.55,9745.0,count,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Bathrooms,bathrooms,A_structural,level,count,0.041481,,7.92,,***,,,high,,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,semi_elasticity,4.1480999999999995,0.52375,100*b/1 (per unit count),|b/t|,0.07997256222937982,0.010097545736032805,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.92,9745.0,count,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c1,2,Model 1,9,SqftStruc,living_area,A_structural,level,sqft,0.000226,,47.76,,***,,,high,Square footage of house,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7798,t,All sales; neighbourhood fixed effects; coastal specification: log coastal distance,semi_elasticity,0.2432643754176397,0.005093475197186761,100*b/0.092903 (X per sqft->m2),|b/t|,0.43551528380396737,0.009118829225376202,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.76,9745.0,sqft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,SqftStruc,living_area,A_structural,level,sqft,0.000225,,46.92,,***,,,high,Square footage of house,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,semi_elasticity,0.24218798437596872,0.005161721747143408,100*b/0.092903 (X per sqft->m2),|b/t|,0.42927728334424325,0.009149132211087877,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),46.92,9745.0,sqft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,SqftStruc,living_area,A_structural,level,sqft,0.000226,,47.68,,***,,,high,Square footage of house,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,semi_elasticity,0.2432643754176397,0.005102021296510899,100*b/0.092903 (X per sqft->m2),|b/t|,0.43492386382327136,0.009121725331863914,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.68,9745.0,sqft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c1,2,Model 1,9,LotSqft,lot_size,A_structural,level,sqft,4.84e-08,,2.24,,**,,,high,Square footage of lot,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7798,t,All sales; neighbourhood fixed effects; coastal specification: log coastal distance,semi_elasticity,5.2097326416875056e-05,2.3257735007533503e-05,100*b/0.092903 (X per sqft->m2),|b/t|,0.02268534134770862,0.010127384530227062,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.24,9745.0,sqft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,LotSqft,lot_size,A_structural,level,sqft,4.73e-08,,2.16,,**,,,high,Square footage of lot,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,semi_elasticity,5.091329627103698e-05,2.3570970495850454e-05,100*b/0.092903 (X per sqft->m2),|b/t|,0.021875545469783056,0.010127567347121783,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.16,9745.0,sqft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,LotSqft,lot_size,A_structural,level,sqft,4.87e-08,,2.24,,**,,,high,Square footage of lot,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,semi_elasticity,5.2420243729376345e-05,2.3401894522043008e-05,100*b/0.092903 (X per sqft->m2),|b/t|,0.02268534134770862,0.010127384530227062,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.24,9745.0,sqft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c1,2,Model 1,9,LnDtownDist,cbd_distance,D_location,log,feet,0.175223,,7.66,,***,,,high,Log distance in feet to downtown San Diego,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7798,t,All sales; neighbourhood fixed effects; coastal specification: log coastal distance,elasticity,0.175223,0.022875065274151434,b (log-log),|b/t|,0.07736317830859459,0.010099631632975793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.66,9745.0,ft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,LnDtownDist,cbd_distance,D_location,log,feet,0.076875,,3.29,,***,,,high,Log distance in feet to downtown San Diego,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,elasticity,0.076875,0.02336626139817629,b (log-log),|b/t|,0.0333091781502552,0.010124370258436231,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.29,9745.0,ft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,LnDtownDist,cbd_distance,D_location,log,feet,0.075096,,3.25,,***,,,high,Log distance in feet to downtown San Diego,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,elasticity,0.075096,0.023106461538461538,b (log-log),|b/t|,0.03290464450780988,0.01012450600240304,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.25,9745.0,ft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c1,2,Model 1,9,LnFreeDist,highway_distance,D_location,log,feet,0.010732,,3.06,,***,,,high,Log distance in feet to nearest freeway,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7798,t,All sales; neighbourhood fixed effects; coastal specification: log coastal distance,elasticity,0.010732,0.00350718954248366,b (log-log),|b/t|,0.030982892231471992,0.010125128180219605,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.06,9745.0,ft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,LnFreeDist,highway_distance,D_location,log,feet,0.015182,,4.17,,***,,,high,Log distance in feet to nearest freeway,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,elasticity,0.015182,0.003640767386091127,b (log-log),|b/t|,0.04220442645721015,0.01012096557726862,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.17,9745.0,ft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,LnFreeDist,highway_distance,D_location,log,feet,0.009351,,2.57,,***,,,high,Log distance in feet to nearest freeway,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,elasticity,0.009351,0.00363852140077821,b (log-log),|b/t|,0.026025259876567508,0.01012656026325584,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.57,9745.0,ft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c1,2,Model 1,9,LnCoastDist,water_proximity,E_environment,log,feet,-0.146047,,-21.12,,***,,,high,Log distance in feet from house to coast,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7798,t,All sales; neighbourhood fixed effects; coastal specification: log coastal distance,elasticity,-0.146047,0.006915104166666667,b (log-log),|b/t|,-0.2092109222406618,0.009905820181849516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.12,9745.0,ft,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,Coast_0to1miles,water_proximity,E_environment,dummy,binary,0.352211,,13.4,,***,,,high,Distance band dummy: residence within 1 mile of coast of coast; reference beyond 6 miles,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,pct_premium,42.17173824080649,3.7381903394866614,100*(exp(b - se^2/2) - 1),|b/t|,0.13450832592303835,0.010037934770375997,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.4,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,Coast_2miles,water_proximity,E_environment,dummy,binary,0.200634,,7.92,,***,,,high,Distance band dummy: residence 1 to 2 miles of coast; reference beyond 6 miles,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,pct_premium,22.17852762614829,3.0960900891624643,100*(exp(b - se^2/2) - 1),|b/t|,0.07997256222937982,0.010097545736032805,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.92,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,Coast_3miles,water_proximity,E_environment,dummy,binary,0.118684,,5.24,,***,,,high,Distance band dummy: residence 2 to 3 miles of coast; reference beyond 6 miles,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,pct_premium,12.572525312974946,2.550378826646916,100*(exp(b - se^2/2) - 1),|b/t|,0.05300653181966913,0.0101157503472651,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.24,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,Coast_4miles,water_proximity,E_environment,dummy,binary,0.082033,,4.13,,***,,,high,Distance band dummy: residence 3 to 4 miles of coast; reference beyond 6 miles,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,pct_premium,8.527752352742368,2.1560807487097997,100*(exp(b - se^2/2) - 1),|b/t|,0.041800298613892284,0.010121137678908543,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.13,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,Coast_5miles,water_proximity,E_environment,dummy,binary,0.053282,,3.0,,***,,,high,Distance band dummy: residence 4 to 5 miles of coast; reference beyond 6 miles,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,pct_premium,5.456069710394185,1.8732655314437352,100*(exp(b - se^2/2) - 1),|b/t|,0.030375950687208667,0.010125316895736222,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.0,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c2,2,Model 2,9,Coast_6miles,water_proximity,E_environment,dummy,binary,0.035755,,2.59,,***,,,high,Distance band dummy: residence 5 to 6 miles of coast; reference beyond 6 miles,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7749,t,All sales; neighbourhood fixed effects; coastal specification: 1-mile distance bands,pct_premium,3.6303143634247803,1.4307548194720268,100*(exp(b - se^2/2) - 1),|b/t|,0.026227652300238,0.010126506679628573,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.59,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Coast_500ft,water_proximity,E_environment,dummy,binary,0.702698,,15.43,,***,,,high,Distance band dummy: residence within 500 ft of coast of coast; reference beyond 6 miles,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,pct_premium,101.71003454128935,9.195612357772582,100*(exp(b - se^2/2) - 1),|b/t|,0.15443066578674985,0.010008468294669465,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.43,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,True
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Coast_1000ft,water_proximity,E_environment,dummy,binary,0.487333,,11.11,,***,,,high,"Distance band dummy: residence 500 to 1,000 ft of coast; reference beyond 6 miles",Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,pct_premium,62.64032134202948,7.140979636998334,100*(exp(b - se^2/2) - 1),|b/t|,0.11183815150162023,0.010066440279173737,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.11,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Coast_2000ft,water_proximity,E_environment,dummy,binary,0.454806,,13.67,,***,,,high,"Distance band dummy: residence 1,000 to 2,000 ft of coast; reference beyond 6 miles",Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,pct_premium,57.49956984603286,5.242970414260189,100*(exp(b - se^2/2) - 1),|b/t|,0.13716806918622662,0.01003424061347671,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.67,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Coast_3000ft,water_proximity,E_environment,dummy,binary,0.438393,,13.97,,***,,,high,"Distance band dummy: residence 2,000 to 3,000 ft of coast; reference beyond 6 miles",Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,pct_premium,54.945090829135545,4.864731393505186,100*(exp(b - se^2/2) - 1),|b/t|,0.14011986136541743,0.01003005450002988,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.97,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Coast_4000ft,water_proximity,E_environment,dummy,binary,0.293654,,9.38,,***,,,high,"Distance band dummy: residence 3,000 to 4,000 ft of coast; reference beyond 6 miles",Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,pct_premium,34.0662580433472,4.199188731739317,100*(exp(b - se^2/2) - 1),|b/t|,0.09459325353887618,0.010084568607556096,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.38,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Coast_5280ft,water_proximity,E_environment,dummy,binary,0.20111,,6.77,,***,,,high,"Distance band dummy: residence 4,000 to 5,280 ft of coast; reference beyond 6 miles",Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,pct_premium,22.221987513302576,3.632335544704507,100*(exp(b - se^2/2) - 1),|b/t|,0.06841933510448509,0.010106253338919511,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.77,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Coast_2miles,water_proximity,E_environment,dummy,binary,0.193321,,7.71,,***,,,high,Distance band dummy: residence 1 to 2 miles of coast; reference beyond 6 miles,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,pct_premium,21.28908540811516,3.042165931412079,100*(exp(b - se^2/2) - 1),|b/t|,0.07786510806736839,0.010099235806403165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.71,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Coast_3miles,water_proximity,E_environment,dummy,binary,0.115352,,5.15,,***,,,high,Distance band dummy: residence 2 to 3 miles of coast; reference beyond 6 miles,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,pct_premium,12.198692618929297,2.5137068976762715,100*(exp(b - se^2/2) - 1),|b/t|,0.05209860693534219,0.010116234356377124,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.15,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Coast_4miles,water_proximity,E_environment,dummy,binary,0.082574,,4.2,,***,,,high,Distance band dummy: residence 3 to 4 miles of coast; reference beyond 6 miles,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,pct_premium,8.58691571829917,2.1352831113077055,100*(exp(b - se^2/2) - 1),|b/t|,0.042507508756754346,0.010120835418274843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.2,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Coast_5miles,water_proximity,E_environment,dummy,binary,0.053941,,3.07,,***,,,high,Distance band dummy: residence 4 to 5 miles of coast; reference beyond 6 miles,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,pct_premium,5.525942930661798,1.8544148509491238,100*(exp(b - se^2/2) - 1),|b/t|,0.031084045841652815,0.010125096365359224,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.07,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1,d458e3973f160efbbd5c7fd28ec076d63dc933e1:T2-c3,2,Model 3,9,Coast_6miles,water_proximity,E_environment,dummy,binary,0.033207,,2.43,,**,,,high,Distance band dummy: residence 5 to 6 miles of coast; reference beyond 6 miles,Ln_Price (natural log of sales price),log,OLS,9755.0,0.7795,t,All sales; neighbourhood fixed effects; coastal specification: 500/1000-ft and mile bands,pct_premium,3.366798617668043,1.4126838667609076,100*(exp(b - se^2/2) - 1),|b/t|,0.024608424689525562,0.010126923740545498,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.43,9745.0,binary,,2011.0,United States,North America,High income,2006.0,2006.0,single_family,transaction,journal,False,True,unknown,,2006.0,ols,journal,True,True,False
d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3:T2-OLS,2,OLS,9,Age,age,A_structural,level,years,-0.0055,,,0.006,,,,high,Age in years; model also includes Age-squared; p-value printed in parentheses,log monthly rental price (EUR),log,OLS,757.0,0.7504,p,All 757 apartments; RMSE 0.3490,semi_elasticity,-0.5499999999999999,0.2001614840661458,100*b/1 (per year),|b/z(p)| (two-sided normal),-0.10003179876667992,0.0364045696271722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.7477813854449926,747.0,years,,2021.0,Greece,Europe,High income,2014.0,2014.0,condo_apartment,rent,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3:T2-OLS,2,OLS,9,Bedrooms,bedrooms,A_structural,level,count,0.0596,,,0.009,,,,high,p-value printed in parentheses,log monthly rental price (EUR),log,OLS,757.0,0.7504,p,All 757 apartments; RMSE 0.3490,semi_elasticity,5.96,2.281729121125767,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.09513657936908908,0.036422131481668354,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6120541412292777,747.0,count,,2021.0,Greece,Europe,High income,2014.0,2014.0,condo_apartment,rent,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3:T2-RK,2,RK,9,WC,bathrooms,A_structural,level,count,0.0768,,,0.001,,,,high,Number of additional toilets apart from the main bathroom; p-value printed in parentheses,log monthly rental price (EUR),log,other,757.0,0.8434,p,"All 757 apartments; regression-kriging (GLS, exponential variogram); RMSE 0.2768",semi_elasticity,7.68,2.3339728337408028,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.11953090945485606,0.03632576763801638,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,747.0,count,,2021.0,Greece,Europe,High income,2014.0,2014.0,condo_apartment,rent,journal,False,False,unknown,,2014.0,other,journal,True,True,False
d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3:T2-OLS,2,OLS,9,Storage room,storage,B_interior,dummy,binary,0.0811,,,0.008,,,,high,p-value printed in parentheses,log monthly rental price (EUR),log,OLS,757.0,0.7504,p,All 757 apartments; RMSE 0.3490,pct_premium,8.397239323564754,3.3163257670367465,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.09658054200383905,0.03641704366757784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.652069807902196,747.0,binary,,2021.0,Greece,Europe,High income,2014.0,2014.0,condo_apartment,rent,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3:T2-RK,2,RK,9,Storage room,storage,B_interior,dummy,binary,0.0314,,,0.02,,,,high,p-value printed in parentheses,log monthly rental price (EUR),log,other,757.0,0.8434,p,"All 757 apartments; regression-kriging (GLS, exponential variogram); RMSE 0.2768",pct_premium,3.180418728475609,1.3928098730617402,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.08480995483540665,0.036456265110554026,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3263478740408408,747.0,binary,,2021.0,Greece,Europe,High income,2014.0,2014.0,condo_apartment,rent,journal,False,False,unknown,,2014.0,other,journal,True,True,False
d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3:T2-OLS,2,OLS,9,Air conditioned,air_conditioning,A_structural,dummy,binary,0.0789,,,0.005,,,,high,p-value printed in parentheses,log monthly rental price (EUR),log,OLS,757.0,0.7504,p,All 757 apartments; RMSE 0.3490,pct_premium,8.166873236324612,3.041551683809494,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.10216657608391978,0.03639663235836301,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8070337683438042,747.0,binary,,2021.0,Greece,Europe,High income,2014.0,2014.0,condo_apartment,rent,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3:T2-RK,2,RK,9,Air conditioned,air_conditioning,A_structural,dummy,binary,0.0298,,,0.019,,,,high,p-value printed in parentheses,log monthly rental price (EUR),log,other,757.0,0.8434,p,"All 757 apartments; regression-kriging (GLS, exponential variogram); RMSE 0.2768",pct_premium,3.0165317026883853,1.3089319475642474,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.08550420677015254,0.03645409411956984,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3455309708066743,747.0,binary,,2021.0,Greece,Europe,High income,2014.0,2014.0,condo_apartment,rent,journal,False,False,unknown,,2014.0,other,journal,True,True,False
d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3:T2-RK,2,RK,9,View,view,E_environment,dummy,binary,0.0679,,,0.003,,,,high,p-value printed in parentheses,log monthly rental price (EUR),log,other,757.0,0.8434,p,"All 757 apartments; regression-kriging (GLS, exponential variogram); RMSE 0.2768",pct_premium,6.997819206044853,2.4486844477775755,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.10794933148787654,0.03637428041273032,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9677379253417833,747.0,binary,,2021.0,Greece,Europe,High income,2014.0,2014.0,condo_apartment,rent,journal,False,False,unknown,,2014.0,other,journal,True,True,False
d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3:T2-OLS,2,OLS,9,Heat,heating,A_structural,dummy,binary,0.1758,,,0.015,,,,high,Has heating; p-value printed in parentheses,log monthly rental price (EUR),log,OLS,757.0,0.7504,p,All 757 apartments; RMSE 0.3490,pct_premium,18.908983271958178,8.616612942842512,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.08864573751918361,0.03644404732327045,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4323790585844467,747.0,binary,,2021.0,Greece,Europe,High income,2014.0,2014.0,condo_apartment,rent,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3:T2-RK,2,RK,9,Heat,heating,A_structural,dummy,binary,0.0984,,,0.08,,,,high,Has heating; p-value printed in parentheses,log monthly rental price (EUR),log,other,757.0,0.8434,p,"All 757 apartments; regression-kriging (GLS, exponential variogram); RMSE 0.2768",pct_premium,10.166251119874437,6.201852013132323,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.06392325106286231,0.03651325735238272,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7506860712521697,747.0,binary,,2021.0,Greece,Europe,High income,2014.0,2014.0,condo_apartment,rent,journal,False,False,unknown,,2014.0,other,journal,True,True,False
d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3:T2-OLS,2,OLS,9,Elevator,accessibility,B_interior,dummy,binary,0.0761,,,0.005,,,,high,p-value printed in parentheses,log monthly rental price (EUR),log,OLS,757.0,0.7504,p,All 757 apartments; RMSE 0.3490,pct_premium,7.8674002408143595,2.925410593032093,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.10216657608391978,0.03639663235836301,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8070337683438042,747.0,binary,,2021.0,Greece,Europe,High income,2014.0,2014.0,condo_apartment,rent,journal,False,False,unknown,,2014.0,ols,journal,True,True,False
d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3,d66dcd3e24d3aa705a9e17810be910446c18dce3:T2-RK,2,RK,9,Elevator,accessibility,B_interior,dummy,binary,0.0734,,,0.002,,,,high,p-value printed in parentheses,log monthly rental price (EUR),log,other,757.0,0.8434,p,"All 757 apartments; regression-kriging (GLS, exponential variogram); RMSE 0.2768",pct_premium,7.585738924754404,2.556125344297839,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.11234983628649975,0.03635643704269741,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.090232306167813,747.0,binary,,2021.0,Greece,Europe,High income,2014.0,2014.0,condo_apartment,rent,journal,False,False,unknown,,2014.0,other,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,area,living_area,A_structural,level,m2,0.0227,,,0.0001,,,,high,area of the dwelling in m2 (mean 52.86); entered with area2 (squared term); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",semi_elasticity,2.27,0.5834587811503436,100*b/1 (X per m2->m2),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130946,43065.0,m2,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,basement,basement,A_structural,dummy,binary,0.0294,,,0.0001,,,,high,1 if apartment has basement or storage room; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,2.980704342563767,0.7782155624717358,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,cons1960,age,A_structural,dummy,binary,0.0147,,,0.0001,,,,high,construction period dummy: built 1960-1969 (base cons1950 = built 1950-1959); vintage not age; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,1.4801332747850893,0.3834297327551238,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,cons1970,age,A_structural,dummy,binary,0.0341,,,0.0001,,,,high,construction period dummy: built 1970-1979 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,3.464832847252497,0.9068764915322208,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130946,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,cons1980,age,A_structural,dummy,binary,0.0608,,,0.0001,,,,high,construction period dummy: built 1980-1989 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,6.255660057230572,1.660706964660636,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,cons1990,age,A_structural,dummy,binary,0.1354,,,0.0001,,,,high,construction period dummy: built 1990-1999 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,14.430150755350102,3.984799373434541,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,cons2000,age,A_structural,dummy,binary,0.2273,,,0.0001,,,,high,construction period dummy: built after 2000 (base built 1950-1959); Table 3 also lists cons2010 so cons2000 likely 2000-2009; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,25.306603655556014,7.333290589131144,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,cons2010,age,A_structural,dummy,binary,0.2213,,,0.0001,,,,high,construction period dummy: built 2010+ (base built 1950-1959); cons2010 not described in Table 2 but reported; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,24.568089868024856,7.097004915199631,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,floor2,floor_level,A_structural,dummy,binary,0.0269,,,0.0001,,,,high,floor2 = 'other floors' (base floor1 = ground floor); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,2.7240517216530646,0.7102628910944769,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,floor3,floor_level,A_structural,dummy,binary,0.0284,,,0.0001,,,,high,floor3 = first and second floor (base ground floor); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,2.8779715326627153,0.7509942754830428,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,dcc,cbd_distance,D_location,level,km,-0.0268,,,0.0001,,,,high,distance to city centre in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",semi_elasticity,-2.68,0.6888412041774982,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,kindergarten,school_distance,D_location,level,km,-0.0119,,,0.0131,,,,high,distance to nearest kindergarten in km (mapped to school_distance; kindergarten not primary school),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",semi_elasticity,-1.1900000000000002,0.4796377440464775,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.011954745856322333,0.004818443137122201,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.481039106640214,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,school,school_distance,D_location,level,km,-0.0352,,,0.0001,,,,high,distance to nearest primary school in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",semi_elasticity,-3.52,0.9047466562331319,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.8905918864130946,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,subway,transit_distance,D_location,level,km,-0.016,,,0.0001,,,,high,distance to nearest subway station in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",semi_elasticity,-1.6,0.41124848010596904,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.8905918864130946,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,duga100,green_space,E_environment,dummy,binary,0.0452,,,0.0001,,,,high,urban green area within 0-100 m (base >500 m); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,4.616648213109631,1.2154941378083848,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,duga200,green_space,E_environment,dummy,binary,0.0145,,,0.0001,,,,high,urban green area 101-200 m (base >500 m); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,1.4598588500708276,0.3781373666606474,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,duga300,green_space,E_environment,dummy,binary,0.012,,,0.0001,,,,high,urban green area 201-300 m (base >500 m); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,1.2067474804470457,0.31215989291515783,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.018744641570233256,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130937,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,duga400,green_space,E_environment,dummy,binary,0.0074,,,0.0074,,,,high,urban green area 301-400 m (base >500 m),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,0.7423602342445879,0.2783482826634423,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.012905016387180519,0.004818386214406422,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6782860096594163,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c1,4,1 (OLS),9,duga500,green_space,E_environment,dummy,binary,0.0056,,,0.051,,,,high,urban green area 401-500 m (base >500 m),ln(sale price),log,OLS,43075.0,0.8702,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,0.5611568845480974,0.2885732175490396,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.009403350556026174,0.004818574439681478,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9514797734758589,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,area,living_area,A_structural,level,m2,0.0256,,,0.0001,,,,high,area of the dwelling in m2 (mean 52.86); entered with area2 (squared term); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",semi_elasticity,2.56,0.6579975681695506,100*b/1 (X per m2->m2),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,m2,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,basement,basement,A_structural,dummy,binary,0.0204,,,0.0001,,,,high,1 if apartment has basement or storage room; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,2.0595472256402347,0.5351482358604903,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,cons1960,age,A_structural,dummy,binary,0.0154,,,0.0001,,,,high,construction period dummy: built 1960-1969 (base cons1950 = built 1950-1959); vintage not age; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,1.5511235578909321,0.40196957169836794,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.018744641570233256,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130937,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,cons1970,age,A_structural,dummy,binary,0.0245,,,0.0001,,,,high,construction period dummy: built 1970-1979 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,2.4782271901407693,0.6453430278772883,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,cons1980,age,A_structural,dummy,binary,0.0371,,,0.0001,,,,high,construction period dummy: built 1980-1989 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,3.77496119625651,0.9896247725483827,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,cons1990,age,A_structural,dummy,binary,0.131,,,0.0001,,,,high,construction period dummy: built 1990-1999 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,13.93217542194658,3.8383820177435752,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,cons2000,age,A_structural,dummy,binary,0.2079,,,0.0001,,,,high,construction period dummy: built after 2000 (base built 1950-1959); Table 3 also lists cons2010 so cons2000 likely 2000-2009; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,22.93336380813078,6.578526604166228,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,cons2010,age,A_structural,dummy,binary,0.221,,,0.0001,,,,high,construction period dummy: built 2010+ (base built 1950-1959); cons2010 not described in Table 2 but reported; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,24.531270872186404,7.085258135589232,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,floor2,floor_level,A_structural,dummy,binary,0.0256,,,0.0001,,,,high,floor2 = 'other floors' (base floor1 = ground floor); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,2.590828504641429,0.6750597702882567,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,floor3,floor_level,A_structural,dummy,binary,0.0288,,,0.0001,,,,high,floor3 = first and second floor (base ground floor); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,2.9190531685493015,0.7618763492424905,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,dcc,cbd_distance,D_location,level,km,-0.0217,,,0.0001,,,,high,distance to city centre in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",semi_elasticity,-2.17,0.5577557511437206,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,kindergarten,school_distance,D_location,level,km,-0.0029,,,0.5049,,,,high,distance to nearest kindergarten in km (mapped to school_distance; kindergarten not primary school),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",semi_elasticity,-0.29,0.43491312690101536,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.0032131501025058477,0.004818762614769435,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.666799832109926,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,school,school_distance,D_location,level,km,-0.0288,,,0.0001,,,,high,distance to nearest primary school in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",semi_elasticity,-2.88,0.7402472641907443,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,subway,transit_distance,D_location,level,km,-0.0188,,,0.0001,,,,high,distance to nearest subway station in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",semi_elasticity,-1.8800000000000001,0.48321696412451365,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,duga100,green_space,E_environment,dummy,binary,0.0276,,,0.0001,,,,high,urban green area within 0-100 m (base >500 m); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,2.795854189581104,0.7292558690402241,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,duga200,green_space,E_environment,dummy,binary,0.0138,,,0.0001,,,,high,urban green area 101-200 m (base >500 m); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,1.3889281465544467,0.3596306297337358,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,duga300,green_space,E_environment,dummy,binary,0.0069,,,0.0044,,,,high,urban green area 201-300 m (base >500 m),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,0.6920904588038956,0.2439559057331214,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01372243767600837,0.004818333767255975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8479632874879175,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,duga400,green_space,E_environment,dummy,binary,0.0021,,,0.3788,,,,high,urban green area 301-400 m (base >500 m),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,0.20993539067992728,0.23910827729420642,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.004241022447538649,0.004818744154013719,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8801094874493673,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c2,4,2 (WLS),9,duga500,green_space,E_environment,dummy,binary,0.0015,,,0.5372,,,,high,urban green area 401-500 m (base >500 m),ln(sale price),log,WLS,43075.0,0.8495,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted",pct_premium,0.1498166467892581,0.24345599887375519,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0029734324375420384,0.0048187661879972804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6170526482377062,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,area,living_area,A_structural,level,m2,0.0242,,,0.0001,,,,high,area of the dwelling in m2 (mean 52.86); entered with area2 (squared term); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",semi_elasticity,2.42,0.6220133261602782,100*b/1 (X per m2->m2),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,m2,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,basement,basement,A_structural,dummy,binary,0.0216,,,0.0001,,,,high,1 if apartment has basement or storage room; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,2.181922079192544,0.5673079050399757,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130946,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,cons1960,age,A_structural,dummy,binary,0.018,,,0.0001,,,,high,construction period dummy: built 1960-1969 (base cons1950 = built 1950-1959); vintage not age; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,1.8152079598380944,0.47105772360803133,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,cons1970,age,A_structural,dummy,binary,0.0307,,,0.0001,,,,high,construction period dummy: built 1970-1979 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,3.114400195335043,0.8136835560479784,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130946,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,cons1980,age,A_structural,dummy,binary,0.0415,,,0.0001,,,,high,construction period dummy: built 1980-1989 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,4.2313863077830804,1.11187416927243,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,cons1990,age,A_structural,dummy,binary,0.1366,,,0.0001,,,,high,construction period dummy: built 1990-1999 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,14.566314128213165,4.02494220675223,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130946,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,cons2000,age,A_structural,dummy,binary,0.2139,,,0.0001,,,,high,construction period dummy: built after 2000 (base built 1950-1959); Table 3 also lists cons2010 so cons2000 likely 2000-2009; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,23.66284281128932,6.809115445172862,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,cons2010,age,A_structural,dummy,binary,0.2059,,,0.0001,,,,high,construction period dummy: built 2010+ (base built 1950-1959); cons2010 not described in Table 2 but reported; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,22.691096808027122,6.502223654518346,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.018744641570233256,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130937,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,floor2,floor_level,A_structural,dummy,binary,0.0269,,,0.0001,,,,high,floor2 = 'other floors' (base floor1 = ground floor); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,2.7240517216530646,0.7102628910944769,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,floor3,floor_level,A_structural,dummy,binary,0.0302,,,0.0001,,,,high,floor3 = first and second floor (base ground floor); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,3.0629595464792603,0.8000312652148589,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,dcc,cbd_distance,D_location,level,km,-0.0233,,,0.0001,,,,high,distance to city centre in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",semi_elasticity,-2.33,0.5988805991543175,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,kindergarten,school_distance,D_location,level,km,-0.0081,,,0.0718,,,,high,distance to nearest kindergarten in km (mapped to school_distance; kindergarten not primary school),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",semi_elasticity,-0.8099999999999999,0.44990398016112726,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.008675342195857355,0.004818606152069133,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8003841613268434,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,school,school_distance,D_location,level,km,-0.0307,,,0.0001,,,,high,distance to nearest primary school in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",semi_elasticity,-3.0700000000000003,0.7890830212033282,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.8905918864130946,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,subway,transit_distance,D_location,level,km,-0.0186,,,0.0001,,,,high,distance to nearest subway station in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",semi_elasticity,-1.8599999999999999,0.47807635812318905,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.018744641570233256,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.8905918864130937,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,duga100,green_space,E_environment,dummy,binary,0.0304,,,0.0001,,,,high,urban green area within 0-100 m (base >500 m); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,3.0835329301478698,0.8054905675190613,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,duga200,green_space,E_environment,dummy,binary,0.0077,,,0.0042,,,,high,urban green area 101-200 m (base >500 m),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,0.7726075945751587,0.2710525224566353,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01379360529696232,0.004818329048610898,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.862736263505904,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,duga300,green_space,E_environment,dummy,binary,0.0065,,,0.0126,,,,high,urban green area 201-300 m (base >500 m),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,0.6517754829801659,0.26223263570661526,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01202142418122752,0.004818439284969636,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4948792482923805,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,duga400,green_space,E_environment,dummy,binary,0.0028,,,0.2807,,,,high,urban green area 301-400 m (base >500 m),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,0.2800545649090491,0.2602878995422016,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0051981880162170185,0.004818722385167946,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0787481827583738,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T4-c3,4,3 (Median QR),9,duga500,green_space,E_environment,dummy,binary,0.0029,,,0.2778,,,,high,urban green area 401-500 m (base >500 m),ln(sale price),log,quantile,43075.0,,p,"general model, full sample of 43,075 apartment sales 2010-2015 (built after 1950); year dummies (base 2010) and 18 district dummies (base d9 Srodmiescie) included, not extracted; median (0.5) quantile regression",pct_premium,0.2900628554352247,0.2679894923086301,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.005229636719027631,0.00481872159501686,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0852747177665767,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),10,area,living_area,A_structural,level,m2,0.0227,,,0.0001,,,,high,area of the dwelling in m2 (mean 52.86); entered with area2 (squared term); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",semi_elasticity,2.27,0.5834587811503436,100*b/1 (X per m2->m2),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130946,43065.0,m2,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),10,basement,basement,A_structural,dummy,binary,0.0287,,,0.0001,,,,high,1 if apartment has basement or storage room; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,2.908781323855325,0.7591550259535683,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),10,cons1960,age,A_structural,dummy,binary,0.0144,,,0.0002,,,,high,construction period dummy: built 1960-1969 (base cons1950 = built 1950-1959); vintage not age,ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,1.4496574604773826,0.39281514995610456,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0179182729624692,0.00481801385730446,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.7190164854556804,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,cons1970,age,A_structural,dummy,binary,0.0342,,,0.0001,,,,high,construction period dummy: built 1970-1979 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,3.4751565027917097,0.9096269115273912,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,cons1980,age,A_structural,dummy,binary,0.0564,,,0.0001,,,,high,construction period dummy: built 1980-1989 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,5.790964238343044,1.5337608076395182,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,cons1990,age,A_structural,dummy,binary,0.1197,,,0.0001,,,,high,construction period dummy: built 1990-1999 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,12.662530702368159,3.467875704618173,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,cons2000,age,A_structural,dummy,binary,0.2116,,,0.0001,,,,high,construction period dummy: built after 2000 (base built 1950-1959); Table 3 also lists cons2010 so cons2000 likely 2000-2009; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,23.382733645532028,6.720424384820151,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,cons2010,age,A_structural,dummy,binary,0.2074,,,0.0001,,,,high,construction period dummy: built 2010+ (base built 1950-1959); cons2010 not described in Table 2 but reported; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,22.872755290660173,6.559424699447352,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,floor2,floor_level,A_structural,dummy,binary,0.0268,,,0.0001,,,,high,floor2 = 'other floors' (base floor1 = ground floor); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,2.7137980498035175,0.7075517498868367,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,floor3,floor_level,A_structural,dummy,binary,0.0281,,,0.0001,,,,high,floor3 = first and second floor (base ground floor); p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,2.847170354082973,0.7428383524249466,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,dcc,cbd_distance,D_location,level,km,-0.027,,,0.0001,,,,high,distance to city centre in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",semi_elasticity,-2.7,0.6939818101788228,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,kindergarten,school_distance,D_location,level,km,-0.0117,,,0.0145,,,,high,distance to nearest kindergarten in km (mapped to school_distance; kindergarten not primary school),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",semi_elasticity,-1.17,0.47859963757187485,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.011779344913983445,0.004818453168091097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4446320225729226,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,school,school_distance,D_location,level,km,-0.0354,,,0.0001,,,,high,distance to nearest primary school in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",semi_elasticity,-3.54,0.9098872622344566,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,subway,transit_distance,D_location,level,km,-0.0146,,,0.0001,,,,high,distance to nearest subway station in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",semi_elasticity,-1.46,0.3752642380966968,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,period1 x duga100,green_space,E_environment,dummy,binary,-0.0037,,,0.4587,,,,high,interaction: period1 (built 1950-1989) x duga100 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,-0.37055839641697563,0.4974884098189279,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0035706466353106277,0.004818756771513019,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7409891813629549,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,period1 x duga200,green_space,E_environment,dummy,binary,-0.0015,,,0.6965,,,,high,interaction: period1 (built 1950-1989) x duga200 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,-0.1506259026802348,0.38399023103831925,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0018795619677703952,0.004818778978417436,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.39004942459254965,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,period1 x duga300,green_space,E_environment,dummy,binary,0.0009,,,0.807,,,,high,interaction: period1 (built 1950-1989) x duga300 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,0.08936130157128908,0.36873417329736663,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0011772195317214984,0.004818784151168973,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.24429804174480832,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,period1 x duga400,green_space,E_environment,dummy,binary,-0.0009,,,0.8015,,,,high,interaction: period1 (built 1950-1989) x duga400 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,-0.09059970447542476,0.3576642178076368,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0012114726281834507,0.004818783954031988,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.25140629663834246,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,period1 x duga500,green_space,E_environment,dummy,binary,0.0042,,,0.2963,,,,high,interaction: period1 (built 1950-1989) x duga500 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,0.42007123524385737,0.4038370280195846,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.005032681708885172,0.004818726464983845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.044400786277468,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,period2 x duga100,green_space,E_environment,dummy,binary,0.0993,,,0.0001,,,,high,interaction: period2 (built after 1989) x duga100 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,10.40379093654229,2.8187659311750877,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130946,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,period2 x duga200,green_space,E_environment,dummy,binary,0.031,,,0.0001,,,,high,interaction: period2 (built after 1989) x duga200 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,3.145276090113369,0.8218813885915521,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,period2 x duga300,green_space,E_environment,dummy,binary,0.022,,,0.0001,,,,high,interaction: period2 (built after 1989) x duga300 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions; p printed as 0.0001 (likely <0.0001),ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,2.222744134856236,0.5780447786592071,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,period2 x duga400,green_space,E_environment,dummy,binary,0.0139,,,0.0008,,,,high,interaction: period2 (built after 1989) x duga400 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,1.3988340104072572,0.4203823966447002,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01615429730954375,0.004818158690616729,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3527947805048286,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c1,5,1 (OLS),11,period2 x duga500,green_space,E_environment,dummy,binary,0.004,,,0.3152,,,,high,interaction: period2 (built after 1989) x duga500 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,OLS,43075.0,0.8709,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,0.40000483975968226,0.3998555825896838,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.004839791954309844,0.004818731053245919,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0043706321915888,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),10,area,living_area,A_structural,level,m2,0.0257,,,0.0001,,,,high,area of the dwelling in m2 (mean 52.86); entered with area2 (squared term); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",semi_elasticity,2.5700000000000003,0.6605678711702128,100*b/1 (X per m2->m2),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,m2,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),10,basement,basement,A_structural,dummy,binary,0.0198,,,0.0001,,,,high,1 if apartment has basement or storage room; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,1.9984111304066632,0.5190970301903235,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),10,cons1960,age,A_structural,dummy,binary,0.0143,,,0.0001,,,,high,construction period dummy: built 1960-1969 (base cons1950 = built 1950-1959); vintage not age; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,1.439588207863185,0.37284710196680587,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,cons1970,age,A_structural,dummy,binary,0.0238,,,0.0001,,,,high,construction period dummy: built 1970-1979 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,2.406631902295042,0.626465975949075,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,cons1980,age,A_structural,dummy,binary,0.0328,,,0.0001,,,,high,construction period dummy: built 1980-1989 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,3.3307128043722933,0.8711702296996617,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,cons1990,age,A_structural,dummy,binary,0.119,,,0.0001,,,,high,construction period dummy: built 1990-1999 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,12.584315918967338,3.4451832571904495,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,cons2000,age,A_structural,dummy,binary,0.196,,,0.0001,,,,high,construction period dummy: built after 2000 (base built 1950-1959); Table 3 also lists cons2010 so cons2000 likely 2000-2009; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,21.498415024366025,6.128611800127757,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,cons2010,age,A_structural,dummy,binary,0.2098,,,0.0001,,,,high,construction period dummy: built 2010+ (base built 1950-1959); cons2010 not described in Table 2 but reported; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,23.16393039889235,6.6512732401308705,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,floor2,floor_level,A_structural,dummy,binary,0.0254,,,0.0001,,,,high,floor2 = 'other floors' (base floor1 = ground floor); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,2.570346949573077,0.6696519220545372,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,floor3,floor_level,A_structural,dummy,binary,0.0288,,,0.0001,,,,high,floor3 = first and second floor (base ground floor); p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,2.9190531685493015,0.7618763492424905,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,dcc,cbd_distance,D_location,level,km,-0.0219,,,0.0001,,,,high,distance to city centre in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",semi_elasticity,-2.19,0.5628963571450452,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,kindergarten,school_distance,D_location,level,km,-0.0024,,,0.569,,,,high,distance to nearest kindergarten in km (mapped to school_distance; kindergarten not primary school),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",semi_elasticity,-0.24,0.4214038997935905,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.002744408969458219,0.004818769343159177,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5695248670398051,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,school,school_distance,D_location,level,km,-0.029,,,0.0001,,,,high,distance to nearest primary school in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",semi_elasticity,-2.9000000000000004,0.745387870192069,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,subway,transit_distance,D_location,level,km,-0.0176,,,0.0001,,,,high,distance to nearest subway station in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",semi_elasticity,-1.76,0.45237332811656594,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.8905918864130946,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,period1 x duga100,green_space,E_environment,dummy,binary,-0.0057,,,0.1814,,,,high,interaction: period1 (built 1950-1989) x duga100 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,-0.5692829235066865,0.4240767281193459,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.006439967933088295,0.00481868756394502,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3364568355238922,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,period1 x duga200,green_space,E_environment,dummy,binary,0.002,,,0.5545,,,,high,interaction: period1 (built 1950-1989) x duga200 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,0.19962644299345023,0.3390694858440899,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.002848038722589163,0.004818767946804091,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5910304779208226,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,period1 x duga300,green_space,E_environment,dummy,binary,-0.0001,,,0.9685,,,,high,interaction: period1 (built 1950-1989) x duga300 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,-0.010320096804328216,0.25320554634438863,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.00019029225930820953,0.004818787402971489,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.03948965650380559,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,period1 x duga400,green_space,E_environment,dummy,binary,-0.0046,,,0.1672,,,,high,interaction: period1 (built 1950-1989) x duga400 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,-0.45949561880188616,0.33150160216479024,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.006655835805683277,0.0048186807525312835,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.381256851719617,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,period1 x duga500,green_space,E_environment,dummy,binary,0.0015,,,0.6614,,,,high,interaction: period1 (built 1950-1989) x duga500 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,0.14952521300504173,0.34299465503509247,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0021105330401151572,0.004818776757924105,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.43798107821545157,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,period2 x duga100,green_space,E_environment,dummy,binary,0.0768,,,0.0001,,,,high,interaction: period2 (built after 1989) x duga100 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,7.961572500501735,2.131568822962557,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130946,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,period2 x duga200,green_space,E_environment,dummy,binary,0.0273,,,0.0001,,,,high,interaction: period2 (built after 1989) x duga200 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions; p printed as 0.0001 (likely <0.0001),ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,2.7650759671543845,0.7211128085156497,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,period2 x duga300,green_space,E_environment,dummy,binary,0.0136,,,0.0002,,,,high,interaction: period2 (built after 1989) x duga300 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,1.368612274997072,0.37069541108661447,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0179182729624692,0.00481801385730446,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.7190164854556804,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,period2 x duga400,green_space,E_environment,dummy,binary,0.0084,,,0.0191,,,,high,interaction: period2 (built after 1989) x duga400 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,0.8428901332393268,0.36145046394761954,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01129246244936701,0.0048184802352355715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.343573470902684,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c2,5,2 (WLS),11,period2 x duga500,green_space,E_environment,dummy,binary,0.0003,,,0.9339,,,,high,interaction: period2 (built after 1989) x duga500 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,WLS,43075.0,0.8498,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11",pct_premium,0.029350130690053433,0.3618199113810957,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.00039966564636747696,0.004818787105359582,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.08293905450252374,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,ols,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),10,area,living_area,A_structural,level,m2,0.0243,,,0.0001,,,,high,area of the dwelling in m2 (mean 52.86); entered with area2 (squared term); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",semi_elasticity,2.4299999999999997,0.6245836291609405,100*b/1 (X per m2->m2),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,m2,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),10,basement,basement,A_structural,dummy,binary,0.0215,,,0.0001,,,,high,1 if apartment has basement or storage room; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,2.1717189439779183,0.5646250142290375,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),10,cons1960,age,A_structural,dummy,binary,0.0181,,,0.0001,,,,high,construction period dummy: built 1960-1969 (base cons1950 = built 1950-1959); vintage not age; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,1.8253778474005111,0.4737220808009581,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.018744641570233256,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130937,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,cons1970,age,A_structural,dummy,binary,0.0297,,,0.0001,,,,high,construction period dummy: built 1970-1979 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,3.0115428584505333,0.7863924199408604,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,cons1980,age,A_structural,dummy,binary,0.0408,,,0.0001,,,,high,construction period dummy: built 1980-1989 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,4.158648080785965,1.0923547491986034,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,cons1990,age,A_structural,dummy,binary,0.1237,,,0.0001,,,,high,construction period dummy: built 1990-1999 (base built 1950-1959); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,13.110445611332366,3.5981250288223574,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,cons2000,age,A_structural,dummy,binary,0.2026,,,0.0001,,,,high,construction period dummy: built after 2000 (base built 1950-1959); Table 3 also lists cons2010 so cons2000 likely 2000-2009; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,22.292328962638752,6.376932592541299,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,cons2010,age,A_structural,dummy,binary,0.1949,,,0.0001,,,,high,construction period dummy: built 2010+ (base built 1950-1959); cons2010 not described in Table 2 but reported; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,21.366564071658935,6.087516577287586,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,floor2,floor_level,A_structural,dummy,binary,0.0267,,,0.0001,,,,high,floor2 = 'other floors' (base floor1 = ground floor); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,2.703545333600599,0.7048411437784087,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130946,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,floor3,floor_level,A_structural,dummy,binary,0.0305,,,0.0001,,,,high,floor3 = first and second floor (base ground floor); p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,3.093821059836932,0.8082210256053853,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,dcc,cbd_distance,D_location,level,km,-0.0237,,,0.0001,,,,high,distance to city centre in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",semi_elasticity,-2.37,0.6091618111569667,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,kindergarten,school_distance,D_location,level,km,-0.0082,,,0.0596,,,,high,distance to nearest kindergarten in km (mapped to school_distance; kindergarten not primary school),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",semi_elasticity,-0.8200000000000001,0.43530397395740283,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.009076974238617828,0.004818588972657697,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8837411304686185,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,school,school_distance,D_location,level,km,-0.0294,,,0.0001,,,,high,distance to nearest primary school in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",semi_elasticity,-2.94,0.7556690821947181,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,subway,transit_distance,D_location,level,km,-0.0175,,,0.0001,,,,high,distance to nearest subway station in km; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",semi_elasticity,-1.7500000000000002,0.4498030251159037,100*b/1 (X per km->km),|b/z(p)| (two-sided normal),-0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.890591886413094,43065.0,km,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,period1 x duga100,green_space,E_environment,dummy,binary,0.0022,,,0.6303,,,,high,interaction: period1 (built 1950-1989) x duga100 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,0.2191952215190307,0.4580976674699132,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0023192985388399583,0.004818774529720932,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4813046397035462,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,period1 x duga200,green_space,E_environment,dummy,binary,-0.0034,,,0.3284,,,,high,interaction: period1 (built 1950-1989) x duga200 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,-0.34002570967021084,0.3467016217228182,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.004709549875612127,0.004818734049906042,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9773417305949799,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,period1 x duga300,green_space,E_environment,dummy,binary,-0.0017,,,0.6198,,,,high,interaction: period1 (built 1950-1989) x duga300 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,-0.1704416263666353,0.3420674804796843,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.002390756608910239,0.004818773718785535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4961338191893303,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,period1 x duga400,green_space,E_environment,dummy,binary,-0.0043,,,0.194,,,,high,interaction: period1 (built 1950-1989) x duga400 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,-0.4296224925920189,0.32964497527839964,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.006258695133111661,0.004818693110293816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2988366326425052,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,period1 x duga500,green_space,E_environment,dummy,binary,0.0002,,,0.9484,,,,high,interaction: period1 (built 1950-1989) x duga500 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,0.019524371443990773,0.3091036606991046,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0003118533827021776,0.0048187872558987455,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.06471615494550698,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,period2 x duga100,green_space,E_environment,dummy,binary,0.0826,,,0.0001,,,,high,interaction: period2 (built after 1989) x duga100 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,8.586252883163038,2.305882082799255,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,period2 x duga200,green_space,E_environment,dummy,binary,0.0208,,,0.0001,,,,high,interaction: period2 (built after 1989) x duga200 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,2.1003236298003714,0.545859638716959,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.8905918864130946,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,period2 x duga300,green_space,E_environment,dummy,binary,0.0147,,,0.0001,,,,high,interaction: period2 (built after 1989) x duga300 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions; p printed as 0.0001 (likely <0.0001),ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,1.4801332747850893,0.3834297327551238,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01874464157023326,0.004817940847430995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.890591886413094,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,period2 x duga400,green_space,E_environment,dummy,binary,0.0111,,,0.0032,,,,high,interaction: period2 (built after 1989) x duga400 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,1.115466510157903,0.3807495194862094,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.014203593865508306,0.004818301389597884,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9478425521849063,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995,d956659c01d343fed17ef54a0b1e248a34a32995:T5-c3,5,3 (Median QR),11,period2 x duga500,green_space,E_environment,dummy,binary,0.0051,,,0.1665,,,,high,interaction: period2 (built after 1989) x duga500 distance band dummy (base >500 m); Table 5 replaces main duga effects by period interactions,ln(sale price),log,quantile,43075.0,,p,"same sample, duga distance bands interacted with construction period (period1 = 1950-1989, period2 = after 1989); year and district dummies included, not extracted; table spans pages 10-11; median (0.5) quantile regression",pct_premium,0.5106198379491778,0.3705049571187617,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0066668268768206385,0.004818680399715127,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3835378825320666,43065.0,binary,,2018.0,Poland,Europe,High income,2010.0,2015.0,condo_apartment,transaction,journal,True,True,unknown,,2012.5,quantile,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Metro: 0 - 400 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.131,0.025,,,***,,,high,metro station within 0-400 m; reference >1500 m,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,13.961159703702197,2.849919453279976,100*(exp(b - se^2/2) - 1),reported,0.07006338436718308,0.01337087487923341,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.24,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Metro: 0 - 400 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.131,0.02,,,***,,,high,metro station within 0-400 m; reference >1500 m,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,13.973981055356365,2.279935562623981,100*(exp(b - se^2/2) - 1),reported,0.08745856648591326,0.013352452898612713,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.55,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Metro: 0 - 400 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.084,0.014,,,***,,,high,metro station within 0-400 m; reference >1500 m,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,8.752231139985621,1.5226804513323566,100*(exp(b - se^2/2) - 1),reported,0.08016405884111773,0.013360676473519621,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.0,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Metro: 400 - 800 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.132,0.026,,,***,,,high,reference metro >1500 m,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,14.072268983036885,2.966881630094811,100*(exp(b - se^2/2) - 1),reported,0.06789311476144134,0.01337288624088996,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0769230769230775,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Metro: 400 - 800 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.133,0.017,,,***,,,high,reference metro >1500 m,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,14.208495513079388,1.9418249971625203,100*(exp(b - se^2/2) - 1),reported,0.10429326179969203,0.013330717673644845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.823529411764706,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Metro: 400 - 800 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.088,0.012,,,***,,,high,reference metro >1500 m,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,9.190950171377676,1.310385746433837,100*(exp(b - se^2/2) - 1),reported,0.0978231976089037,0.013339526946668685,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.333333333333333,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Metro: 800 - 1500 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.108,0.021,,,***,,,high,reference metro >1500 m,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,11.380212493925935,2.339500265311582,100*(exp(b - se^2/2) - 1),reported,0.06877070007477712,0.013372080570095554,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.142857142857142,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Metro: 800 - 1500 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.11,0.017,,,***,,,high,reference metro >1500 m,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,11.611677993121127,1.8976727197800813,100*(exp(b - se^2/2) - 1),reported,0.08640618939333616,0.013353683815333773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.470588235294117,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Metro: 800 - 1500 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.069,0.013,,,***,,,high,reference metro >1500 m,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,7.134567661372659,1.3928670718928502,100*(exp(b - se^2/2) - 1),reported,0.07096396065922295,0.013370021573476786,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.307692307692308,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Centrum: 0 - 3 km,cbd_distance,D_location,dummy,"binary (distance band, km)",0.25,0.051,,,***,,,high,distance to city centre 0-3 km; reference >10 km,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,28.235662699903607,6.548529625107481,100*(exp(b - se^2/2) - 1),reported,0.0655636002359697,0.013374974448137818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.901960784313726,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Centrum: 0 - 3 km,cbd_distance,D_location,dummy,"binary (distance band, km)",0.251,0.028,,,***,,,high,distance to city centre 0-3 km; reference >10 km,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,28.48063415181794,3.598868236127347,100*(exp(b - se^2/2) - 1),reported,0.11929753463425197,0.013308091512984283,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.964285714285714,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Centrum: 0 - 3 km,cbd_distance,D_location,dummy,"binary (distance band, km)",0.173,0.021,,,***,,,high,distance to city centre 0-3 km; reference >10 km,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,18.860398900722064,2.4966188206764675,100*(exp(b - se^2/2) - 1),reported,0.10975480527750653,0.013322837634841836,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.238095238095237,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Centrum: 3 - 5 km,cbd_distance,D_location,dummy,"binary (distance band, km)",0.212,0.047,,,***,,,high,reference >10 km,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,23.47833134628314,5.809895059868967,100*(exp(b - se^2/2) - 1),reported,0.06034955791052257,0.013379383121672455,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.51063829787234,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Centrum: 3 - 5 km,cbd_distance,D_location,dummy,"binary (distance band, km)",0.209,0.023,,,***,,,high,reference >10 km,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,23.211905993542302,2.834623496619586,100*(exp(b - se^2/2) - 1),reported,0.12090634306888264,0.013305482730068423,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.08695652173913,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Centrum: 3 - 5 km,cbd_distance,D_location,dummy,"binary (distance band, km)",0.152,0.017,,,***,,,high,reference >10 km,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,16.39920274313409,1.9790724019345913,100*(exp(b - se^2/2) - 1),reported,0.1189943549117088,0.013308579167756908,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.941176470588234,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Centrum: 5- 7 km,cbd_distance,D_location,dummy,"binary (distance band, km)",0.126,0.033,,,***,,,high,reference >10 km,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,13.366471975801097,3.743131155333983,100*(exp(b - se^2/2) - 1),reported,0.05111130785303759,0.013386294913890798,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.818181818181818,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Centrum: 5- 7 km,cbd_distance,D_location,dummy,"binary (distance band, km)",0.118,0.02,,,***,,,high,reference >10 km,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,12.501908504845073,2.2504882227346847,100*(exp(b - se^2/2) - 1),reported,0.07883636501178166,0.01336209576470876,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.8999999999999995,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Centrum: 5- 7 km,cbd_distance,D_location,dummy,"binary (distance band, km)",0.092,0.014,,,***,,,high,reference >10 km,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,9.625738359282487,1.5349107509131437,100*(exp(b - se^2/2) - 1),reported,0.08774249124497477,0.013352118232930945,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.571428571428571,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Centrum: 7 - 10 km,cbd_distance,D_location,dummy,"binary (distance band, km)",0.103,0.034,,,***,,,high,reference >10 km,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,10.785088617051342,3.7688707908584247,100*(exp(b - se^2/2) - 1),reported,0.040572238021567335,0.013392777599352328,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.029411764705882,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Centrum: 7 - 10 km,cbd_distance,D_location,dummy,"binary (distance band, km)",0.104,0.016,,,***,,,high,reference >10 km,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,10.945843514681242,1.775360727864932,100*(exp(b - se^2/2) - 1),reported,0.08679599260340812,0.013353229631293557,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.5,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Centrum: 7 - 10 km,cbd_distance,D_location,dummy,"binary (distance band, km)",0.078,0.011,,,***,,,high,reference >10 km,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,8.10572527277833,1.1892349245370912,100*(exp(b - se^2/2) - 1),reported,0.09461881473796693,0.013343679001508155,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.090909090909092,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Tram: 0 - 200 m,transit_distance,D_location,dummy,"binary (distance band, m)",-0.049,0.018,,,***,,,high,tram stop within 0-200 m; reference >800 m,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,-4.797311115066016,1.7139260334573088,100*(exp(b - se^2/2) - 1),reported,-0.036463895183025834,0.013394900271315614,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.7222222222222223,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Tram: 0 - 200 m,transit_distance,D_location,dummy,"binary (distance band, m)",-0.032,0.016,,,*,,,high,tram stop within 0-200 m; reference >800 m,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,-3.1617378829641107,1.5496105313267163,100*(exp(b - se^2/2) - 1),reported,-0.02679800094369162,0.01339900047184581,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Tram: 0 - 200 m,transit_distance,D_location,dummy,"binary (distance band, m)",-0.03,0.012,,,***,,,high,tram stop within 0-200 m; reference >800 m,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,-2.9624336014572816,1.16453464025821,100*(exp(b - se^2/2) - 1),reported,-0.03349073757537233,0.013396295030148931,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Tram: 200 - 400 m,transit_distance,D_location,dummy,"binary (distance band, m)",-0.006,0.018,,,,,,high,reference tram >800 m,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,-0.6143053813442045,1.7892323352970834,100*(exp(b - se^2/2) - 1),reported,-0.004467893470426545,0.013403680411279633,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.33333333333333337,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Tram: 200 - 400 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.003,0.015,,,,,,high,reference tram >800 m,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,0.289167284352021,1.5045067567550656,100*(exp(b - se^2/2) - 1),reported,0.002680753206595003,0.013403766032975013,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Tram: 200 - 400 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.002,0.011,,,,,,high,reference tram >800 m,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,0.19413820466716025,1.1022022014674002,100*(exp(b - se^2/2) - 1),reported,0.002437049889416815,0.013403774391792482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.18181818181818182,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Tram: 400 - 800 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.045,0.019,,,**,,,high,reference tram >800 m,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,4.583906891890277,1.987452933826562,100*(exp(b - se^2/2) - 1),reported,0.03172989105143109,0.013397065110604239,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3684210526315788,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Tram: 400 - 800 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.044,0.014,,,***,,,high,reference tram >800 m,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,4.487995163550607,1.4629752968438214,100*(exp(b - se^2/2) - 1),reported,0.0420889437396518,0.013391936644434665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.142857142857143,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Tram: 400 - 800 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.035,0.01,,,***,,,high,reference tram >800 m,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,3.5567929108686336,1.0356197087996233,100*(exp(b - se^2/2) - 1),reported,0.04686180983096696,0.013389088523133415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5000000000000004,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Bus: 0 -100 m,transit_distance,D_location,dummy,"binary (distance band, m)",-0.044,0.023,,,**,,,high,bus stop within 0-100 m; reference >400 m,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,-4.329912337728703,2.2009941021880075,100*(exp(b - se^2/2) - 1),reported,-0.025633653444480056,0.013399409755069121,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9130434782608694,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Bus: 0 -100 m,transit_distance,D_location,dummy,"binary (distance band, m)",-0.027,0.02,,,,,,high,bus stop within 0-100 m; reference >400 m,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,-2.683341125804095,1.9467224830486738,100*(exp(b - se^2/2) - 1),reported,-0.018092187404415993,0.013401620299567403,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3499999999999999,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Bus: 0 -100 m,transit_distance,D_location,dummy,"binary (distance band, m)",-0.031,0.016,,,**,,,high,bus stop within 0-100 m; reference >400 m,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,-3.0648511855722704,1.5511609169216416,100*(exp(b - se^2/2) - 1),reported,-0.025961136928035256,0.01339929647898594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9375,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Bus: 100 - 250 m,transit_distance,D_location,dummy,"binary (distance band, m)",-0.019,0.02,,,,,,high,reference bus >400 m,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,-1.9016854007363526,1.962358724485612,100*(exp(b - se^2/2) - 1),reported,-0.01273259126387656,0.013402727646185851,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.95,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Bus: 100 - 250 m,transit_distance,D_location,dummy,"binary (distance band, m)",-0.001,0.019,,,,,,high,reference bus >400 m,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,-0.11798034839810567,1.8981009496834125,100*(exp(b - se^2/2) - 1),reported,-0.0007054637295000216,0.01340381086050041,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.052631578947368425,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Bus: 100 - 250 m,transit_distance,D_location,dummy,"binary (distance band, m)",-0.007,0.015,,,,,,high,reference bus >400 m,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,-0.7087266032847706,1.4895366643998524,100*(exp(b - se^2/2) - 1),reported,-0.006254990924846091,0.01340355198181305,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.4666666666666667,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Bus: 250 - 400 m,transit_distance,D_location,dummy,"binary (distance band, m)",-0.006,0.018,,,,,,high,reference bus >400 m,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,-0.6143053813442045,1.7892323352970834,100*(exp(b - se^2/2) - 1),reported,-0.004467893470426545,0.013403680411279633,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.33333333333333337,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Bus: 250 - 400 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.007,0.019,,,,,,high,reference bus >400 m,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,0.6842805737830915,1.9133466588070123,100*(exp(b - se^2/2) - 1),reported,0.004938187123674966,0.013403650764260623,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.368421052631579,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Bus: 250 - 400 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.003,0.016,,,,,,high,reference bus >400 m,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,0.2876128143062928,1.6048072072054034,100*(exp(b - se^2/2) - 1),reported,0.002513207224720603,0.01340377186517655,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.1875,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Square meters: 0-35,living_area,A_structural,dummy,"binary (area band, m2)",0.054,0.011,,,***,,,high,usable area 0-35 m2; reference 35-60 m2; dependent variable is price per m2,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,5.54207472682795,1.161033062370588,100*(exp(b - se^2/2) - 1),reported,0.06565855464605322,0.013374890761233065,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.909090909090909,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Square meters: 0-35,living_area,A_structural,dummy,"binary (area band, m2)",0.055,0.01,,,***,,,high,usable area 0-35 m2; reference 35-60 m2; dependent variable is price per m2,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,5.648778896541429,1.0565406146754943,100*(exp(b - se^2/2) - 1),reported,0.07352146220938077,0.013367538583523778,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.5,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Square meters: 0-35,living_area,A_structural,dummy,"binary (area band, m2)",0.052,0.01,,,***,,,high,usable area 0-35 m2; reference 35-60 m2; dependent variable is price per m2,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,5.332307504293676,1.0533757425133647,100*(exp(b - se^2/2) - 1),reported,0.06953114497121082,0.013371374032925161,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.199999999999999,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Square meters: 60-90,living_area,A_structural,dummy,"binary (area band, m2)",0.0,0.01,,,,,,high,reference 35-60 m2,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,-0.004999875002087428,1.0,100*(exp(b - se^2/2) - 1),reported,0.0,0.01340381419589974,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Square meters: 60-90,living_area,A_structural,dummy,"binary (area band, m2)",-0.009,0.008,,,,,,high,reference 35-60 m2,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,-0.8991334011829832,0.7928323030183069,100*(exp(b - se^2/2) - 1),reported,-0.01507757686029332,0.01340229054248295,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.125,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Square meters: 60-90,living_area,A_structural,dummy,"binary (area band, m2)",-0.005,0.008,,,,,,high,reference 35-60 m2,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,-0.5019360697210873,0.796009983354146,100*(exp(b - se^2/2) - 1),reported,-0.00837708992316135,0.013403343877058162,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.625,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Square meters: >90,living_area,A_structural,dummy,"binary (area band, m2)",0.011,0.043,,,,,,high,reference 35-60 m2,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,1.0126428750624639,4.347561106512293,100*(exp(b - se^2/2) - 1),reported,0.003428862544361859,0.013403735400687268,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2558139534883721,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Square meters: >90,living_area,A_structural,dummy,"binary (area band, m2)",-0.002,0.011,,,,,,high,reference 35-60 m2,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,-0.20583786271547444,1.0978021985340662,100*(exp(b - se^2/2) - 1),reported,-0.002437049889416815,0.013403774391792482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.18181818181818182,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Square meters: >90,living_area,A_structural,dummy,"binary (area band, m2)",0.003,0.01,,,,,,high,reference 35-60 m2,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,0.2954355531886499,1.003004504503377,100*(exp(b - se^2/2) - 1),reported,0.004021111749014758,0.013403705830049194,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Floor 1,floor_level,A_structural,dummy,binary (floor),0.047,0.018,,,***,,,high,reference ground floor (Floor 0),"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,4.795222706689906,1.8866196163433802,100*(exp(b - se^2/2) - 1),reported,0.0349774324669682,0.013395612434158035,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.611111111111111,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Floor 1,floor_level,A_structural,dummy,binary (floor),0.038,0.011,,,***,,,high,reference ground floor (Floor 0),"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,3.866839153987822,1.1426043561663473,100*(exp(b - se^2/2) - 1),reported,0.04625452552320246,0.013389467914611236,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4545454545454546,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Floor 1,floor_level,A_structural,dummy,binary (floor),0.038,0.011,,,***,,,high,reference ground floor (Floor 0),"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,3.866839153987822,1.1426043561663473,100*(exp(b - se^2/2) - 1),reported,0.04625452552320246,0.013389467914611236,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.4545454545454546,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Floor 2,floor_level,A_structural,dummy,binary (floor),0.036,0.022,,,*,,,high,reference ground floor,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,3.64050061289809,2.280642862280032,100*(exp(b - se^2/2) - 1),reported,0.021928240164577607,0.013400591211686316,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6363636363636362,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Floor 2,floor_level,A_structural,dummy,binary (floor),0.02,0.011,,,*,,,high,reference ground floor,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,2.0139619712742585,1.1222214740294312,100*(exp(b - se^2/2) - 1),reported,0.02436333734476866,0.013399835539622764,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8181818181818183,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Floor 2,floor_level,A_structural,dummy,binary (floor),0.025,0.011,,,**,,,high,reference ground floor,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,2.5253090836054204,1.1278466325768717,100*(exp(b - se^2/2) - 1),reported,0.030449088867824405,0.013397599101842739,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.272727272727273,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Floor 3,floor_level,A_structural,dummy,binary (floor),0.034,0.02,,,*,,,high,reference ground floor,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,3.4377710497085046,2.069169213456236,100*(exp(b - se^2/2) - 1),reported,0.022780570792576588,0.01340033576033917,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7000000000000002,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Floor 3,floor_level,A_structural,dummy,binary (floor),0.019,0.011,,,*,,,high,reference ground floor,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,1.911998999285891,1.1210998134791488,100*(exp(b - se^2/2) - 1),reported,0.023145840250185037,0.013400223302738705,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7272727272727273,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Floor 3,floor_level,A_structural,dummy,binary (floor),0.024,0.011,,,**,,,high,reference ground floor,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,2.4228350200930615,1.1267193496796837,100*(exp(b - se^2/2) - 1),reported,0.029232187751812223,0.013398086052913934,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.181818181818182,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Floor 4,floor_level,A_structural,dummy,binary (floor),0.041,0.024,,,*,,,high,reference ground floor,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,4.155209534262538,2.500445053309151,100*(exp(b - se^2/2) - 1),reported,0.022892181879299513,0.013400301587882642,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7083333333333333,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Floor 4,floor_level,A_structural,dummy,binary (floor),0.033,0.012,,,***,,,high,reference ground floor,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,3.347612628137875,1.2402606470895667,100*(exp(b - se^2/2) - 1),reported,0.03683547343418786,0.01339471761243195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.75,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Floor 4,floor_level,A_structural,dummy,binary (floor),0.034,0.012,,,***,,,high,reference ground floor,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,3.45101193180124,1.2415015280737416,100*(exp(b - se^2/2) - 1),reported,0.03795011590807103,0.013394158555789773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8333333333333335,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Floor 5-6,floor_level,A_structural,dummy,binary (floor),0.044,0.022,,,**,,,high,reference ground floor,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,4.472949975526586,2.2989611807545764,100*(exp(b - se^2/2) - 1),reported,0.02679800094369162,0.01339900047184581,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Floor 5-6,floor_level,A_structural,dummy,binary (floor),0.034,0.013,,,***,,,high,reference ground floor,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,3.4497188022341696,1.3449599887465533,100*(exp(b - se^2/2) - 1),reported,0.03503460846593142,0.013395585589914952,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.615384615384616,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Floor 5-6,floor_level,A_structural,dummy,binary (floor),0.035,0.013,,,***,,,high,reference ground floor,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,3.553220263141732,1.3463056214395102,100*(exp(b - se^2/2) - 1),reported,0.036063717079506674,0.013395094915245334,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6923076923076925,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Floor 7-9,floor_level,A_structural,dummy,binary (floor),0.024,0.024,,,,,,high,reference ground floor,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,2.399536475435937,2.4582967629374917,100*(exp(b - se^2/2) - 1),reported,0.01340261027851321,0.01340261027851321,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Floor 7-9,floor_level,A_structural,dummy,binary (floor),0.024,0.017,,,,,,high,reference ground floor,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,2.414231863289018,1.7412935404140566,100*(exp(b - se^2/2) - 1),reported,0.018919644725254352,0.013401415013721834,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4117647058823528,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Floor 7-9,floor_level,A_structural,dummy,binary (floor),0.021,0.017,,,,,,high,reference ground floor,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,2.1074495712239294,1.7360774877837986,100*(exp(b - se^2/2) - 1),reported,0.016555383607973262,0.013401977206454543,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2352941176470589,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Floor >=10,floor_level,A_structural,dummy,binary (floor),0.053,0.033,,,,,,high,reference ground floor,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,5.38556644580046,3.479617828893875,100*(exp(b - se^2/2) - 1),reported,0.021522351516992527,0.013400709435108557,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.606060606060606,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Floor >=10,floor_level,A_structural,dummy,binary (floor),0.068,0.024,,,***,,,high,reference ground floor,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,7.005708765586149,2.5688767403490584,100*(exp(b - se^2/2) - 1),reported,0.03795011590807103,0.013394158555789773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8333333333333335,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Floor >=10,floor_level,A_structural,dummy,binary (floor),0.056,0.024,,,**,,,high,reference ground floor,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,5.729313946017589,2.5382344409678668,100*(exp(b - se^2/2) - 1),reported,0.03126028139904691,0.013397263456734388,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3333333333333335,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Parking,parking,A_structural,binary,binary,0.001,0.011,,,,,,high,parking place,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,0.09399414683672891,1.101100550183379,100*(exp(b - se^2/2) - 1),reported,0.0012185276586217891,0.013403804244839682,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.09090909090909091,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Parking,parking,A_structural,binary,binary,0.007,0.008,,,,,,high,parking place,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,0.6992332996607065,0.8056196458134789,100*(exp(b - se^2/2) - 1),reported,0.011727530865351398,0.013402892417544453,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.875,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Parking,parking,A_structural,binary,binary,0.005,0.008,,,,,,high,parking place,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,0.4980360973294573,0.8040100166875208,100*(exp(b - se^2/2) - 1),reported,0.00837708992316135,0.013403343877058162,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.625,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Age of the building: 0-2,age,A_structural,dummy,"binary (age band, years)",0.129,0.02,,,***,,,high,building age 0-2 years; reference >50 years,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,13.746260889318407,2.275380248331463,100*(exp(b - se^2/2) - 1),reported,0.08613330352178025,0.013354000546012443,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.45,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Age of the building: 0-2,age,A_structural,dummy,"binary (age band, years)",0.135,0.014,,,***,,,high,building age 0-2 years; reference >50 years,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,14.442462524233424,1.6023514980918403,100*(exp(b - se^2/2) - 1),reported,0.12818478319383847,0.01329323677565732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.642857142857144,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Age of the building: 0-2,age,A_structural,dummy,"binary (age band, years)",0.119,0.013,,,***,,,high,building age 0-2 years; reference >50 years,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,12.627474405142557,1.4642808937748588,100*(exp(b - se^2/2) - 1),reported,0.12178318972829749,0.01330404593670477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.153846153846153,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,15,Age of the building: 2-10,age,A_structural,dummy,"binary (age band, years)",0.177,0.02,,,***,,,high,reference >50 years; SEs printed at top of p.16,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,19.339239077954385,2.3872621862542776,100*(exp(b - se^2/2) - 1),reported,0.1177978491037063,0.013310491424147605,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.85,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,15,Age of the building: 2-10,age,A_structural,dummy,"binary (age band, years)",0.171,0.013,,,***,,,high,reference >50 years; SEs printed at top of p.16,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,18.639049478922033,1.5424379737282252,100*(exp(b - se^2/2) - 1),reported,0.17363359218660418,0.013200214610677509,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.153846153846155,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,15,Age of the building: 2-10,age,A_structural,dummy,"binary (age band, years)",0.157,0.013,,,***,,,high,reference >50 years; SEs printed at top of p.16,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,16.98967534484519,1.5209942980711877,100*(exp(b - se^2/2) - 1),reported,0.15979670666160803,0.013231574436948437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.076923076923077,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c1,A.1,OLS,16,Age of the building: 10-50,age,A_structural,dummy,"binary (age band, years)",-0.014,0.016,,,,,,high,reference >50 years,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Full sample; year/quarter FE; OLS,pct_premium,-1.4028668145037337,1.5777560708205791,100*(exp(b - se^2/2) - 1),reported,-0.011727530865351398,0.013402892417544453,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.875,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c2,A.1,SEM,16,Age of the building: 10-50,age,A_structural,dummy,"binary (age band, years)",0.002,0.01,,,,,,high,reference >50 years,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Full sample; year/quarter FE; SEM,pct_premium,0.19519024864151913,1.0020020013340003,100*(exp(b - se^2/2) - 1),reported,0.002680753206595003,0.013403766032975013,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:TA1-c3,A.1,SAR,16,Age of the building: 10-50,age,A_structural,dummy,"binary (age band, years)",-0.005,0.01,,,,,,high,reference >50 years,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Full sample; year/quarter FE; SAR,pct_premium,-0.5037270187532417,0.9950124791926824,100*(exp(b - se^2/2) - 1),reported,-0.006701756593068863,0.013403513186137726,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:T6-c1,6,OLS,11,Metro: 0 - 400 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.13,0.026,,,***,,,high,main effect in interaction model; reference >1500 m,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Model with metro x MOT interactions; same controls as Table 4/A.1 (other coefficients not printed in dump; Appendix Table A.3),pct_premium,13.844352437588437,2.9609537966440165,100*(exp(b - se^2/2) - 1),reported,0.06686906615607269,0.013373813231214537,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.0,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:T6-c2,6,SEM,11,Metro: 0 - 400 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.132,0.021,,,***,,,high,main effect in interaction model; reference >1500 m,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Model with metro x MOT interactions; same controls as Table 4/A.1 (other coefficients not printed in dump; Appendix Table A.3),pct_premium,14.085673262128374,2.396327470461194,100*(exp(b - se^2/2) - 1),reported,0.0839550960322227,0.013356492550580884,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.285714285714286,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:T6-c3,6,SAR,11,Metro: 0 - 400 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.084,0.015,,,***,,,high,main effect in interaction model; reference >1500 m,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Model with metro x MOT interactions; same controls as Table 4/A.1 (other coefficients not printed in dump; Appendix Table A.3),pct_premium,8.750654244066624,1.6314433407132392,100*(exp(b - se^2/2) - 1),reported,0.0748507932166282,0.013366213074397889,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.6000000000000005,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:T6-c1,6,OLS,11,Metro: 400 - 800 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.181,0.034,,,***,,,high,main effect in interaction model; reference >1500 m,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Model with metro x MOT interactions; same controls as Table 4/A.1 (other coefficients not printed in dump; Appendix Table A.3),pct_premium,19.77226954666731,4.074611609596879,100*(exp(b - se^2/2) - 1),reported,0.0711746320190544,0.013369820379269887,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.323529411764706,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:T6-c2,6,SEM,11,Metro: 400 - 800 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.143,0.032,,,***,,,high,main effect in interaction model; reference >1500 m,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Model with metro x MOT interactions; same controls as Table 4/A.1 (other coefficients not printed in dump; Appendix Table A.3),pct_premium,15.313924320342466,3.6919353653312337,100*(exp(b - se^2/2) - 1),reported,0.059791131241338696,0.013379833564495375,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.468749999999999,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:T6-c3,6,SAR,11,Metro: 400 - 800 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.115,0.028,,,***,,,high,main effect in interaction model; reference >1500 m,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Model with metro x MOT interactions; same controls as Table 4/A.1 (other coefficients not printed in dump; Appendix Table A.3),pct_premium,12.143374936892837,3.141245625201427,100*(exp(b - se^2/2) - 1),reported,0.05496814801698132,0.01338354908239545,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.107142857142858,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:T6-c1,6,OLS,11,Metro: 800 - 1500 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.108,0.021,,,***,,,high,reference >1500 m,"ln(price per m2, PLN)",log,OLS,5576.0,,se,Model with metro x MOT interactions; same controls as Table 4/A.1 (other coefficients not printed in dump; Appendix Table A.3),pct_premium,11.380212493925935,2.339500265311582,100*(exp(b - se^2/2) - 1),reported,0.06877070007477712,0.013372080570095554,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.142857142857142,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,ols,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:T6-c2,6,SEM,11,Metro: 800 - 1500 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.11,0.017,,,***,,,high,reference >1500 m,"ln(price per m2, PLN)",log,spatial_error,5576.0,,se,Model with metro x MOT interactions; same controls as Table 4/A.1 (other coefficients not printed in dump; Appendix Table A.3),pct_premium,11.611677993121127,1.8976727197800813,100*(exp(b - se^2/2) - 1),reported,0.08640618939333616,0.013353683815333773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.470588235294117,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa,dde22a8458111f4d97568d09ce7efc13ea6e96aa:T6-c3,6,SAR,11,Metro: 800 - 1500 m,transit_distance,D_location,dummy,"binary (distance band, m)",0.069,0.029,,,***,,,high,reference >1500 m,"ln(price per m2, PLN)",log,spatial_lag,5576.0,,se,Model with metro x MOT interactions; same controls as Table 4/A.1 (other coefficients not printed in dump; Appendix Table A.3),pct_premium,7.098576493493258,3.1071650065302046,100*(exp(b - se^2/2) - 1),reported,0.031875627720011304,0.01339700295478736,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3793103448275863,5566.0,binary,,2020.0,Poland,Europe,High income,2006.0,2013.0,condo_apartment,transaction,journal,True,False,clustered,,2009.5,spatial,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c1,2,1,8,Number of bathrooms,bathrooms,A_structural,level,count,0.1104,,21.19,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,Base Model,semi_elasticity,11.04,0.5210004719207173,100*b/1 (per unit count),|b/t|,0.22078887470063896,0.01041948441248886,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.19,8762.0,count,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c2,2,2,8,Number of bathrooms,bathrooms,A_structural,level,count,0.1103,,21.14,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,CBD Distance,semi_elasticity,11.03,0.5217596972563859,100*b/1 (per unit count),|b/t|,0.22029321133407645,0.01042068170927514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.14,8762.0,count,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c3,2,3,8,Number of bathrooms,bathrooms,A_structural,level,count,0.1132,,22.08,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8627,t,Center Township,semi_elasticity,11.32,0.5126811594202899,100*b/1 (per unit count),|b/t|,0.22958278554681366,0.01039777108454772,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.08,8762.0,count,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c4,2,4,8,Number of bathrooms,bathrooms,A_structural,level,count,0.1121,,21.88,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8631,t,Center Township + CBD,semi_elasticity,11.21,0.5123400365630714,100*b/1 (per unit count),|b/t|,0.2276114333829094,0.010402716333770996,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.88,8762.0,count,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c1,2,1,8,Total number of rooms,bedrooms,A_structural,level,count,0.013,,6.15,,*,,,high,"total number of rooms, not bedrooms; * = p<0.001; t-value in parentheses",log sales price,log,OLS,8772.0,0.8579,t,Base Model,semi_elasticity,1.3,0.21138211382113817,100*b/1 (per unit count),|b/t|,0.06555988146898893,0.010660143328290884,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.15,8762.0,count,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c2,2,2,8,Total number of rooms,bedrooms,A_structural,level,count,0.0131,,6.16,,*,,,high,"total number of rooms, not bedrooms; * = p<0.001; t-value in parentheses",log sales price,log,OLS,8772.0,0.8579,t,CBD Distance,semi_elasticity,1.31,0.2126623376623377,100*b/1 (per unit count),|b/t|,0.06566602360555103,0.010660068767134906,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.16,8762.0,count,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c3,2,3,8,Total number of rooms,bedrooms,A_structural,level,count,0.011,,5.28,,*,,,high,"total number of rooms, not bedrooms; * = p<0.001; t-value in parentheses",log sales price,log,OLS,8772.0,0.8627,t,Center Township,semi_elasticity,1.0999999999999999,0.20833333333333334,100*b/1 (per unit count),|b/t|,0.05631738605289554,0.010666171600927185,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.28,8762.0,count,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c4,2,4,8,Total number of rooms,bedrooms,A_structural,level,count,0.0114,,5.48,,*,,,high,"total number of rooms, not bedrooms; * = p<0.001; t-value in parentheses",log sales price,log,OLS,8772.0,0.8631,t,Center Township + CBD,semi_elasticity,1.1400000000000001,0.20802919708029197,100*b/1 (per unit count),|b/t|,0.058443466540159854,0.010664866156963475,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.48,8762.0,count,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c1,2,1,8,Floor space (100s sq ft),living_area,A_structural,level,100 sqft,0.0211,,34.06,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,Base Model,semi_elasticity,0.2271185097925751,0.00666818877840796,100*b/9.2903 (X per 100sqft->m2),|b/t|,0.34193472112611656,0.010039187349563022,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.06,8762.0,100sqft,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c2,2,2,8,Floor space (100s sq ft),living_area,A_structural,level,100 sqft,0.021,,34.04,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,CBD Distance,semi_elasticity,0.22604211875090416,0.0066404852747034135,100*b/9.2903 (X per 100sqft->m2),|b/t|,0.3417573946268759,0.010039876457898823,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.04,8762.0,100sqft,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c3,2,3,8,Floor space (100s sq ft),living_area,A_structural,level,100 sqft,0.0214,,35.23,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8627,t,Center Township,semi_elasticity,0.230347682917588,0.006538395768310759,100*b/9.2903 (X per 100sqft->m2),|b/t|,0.3522444747960612,0.009998423922681273,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.23,8762.0,100sqft,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c4,2,4,8,Floor space (100s sq ft),living_area,A_structural,level,100 sqft,0.0214,,35.21,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8631,t,Center Township + CBD,semi_elasticity,0.230347682917588,0.006542109710809089,100*b/9.2903 (X per 100sqft->m2),|b/t|,0.35206929913534496,0.009999128064054104,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),35.21,8762.0,100sqft,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c1,2,1,8,Has basement,basement,A_structural,binary,binary,0.0974,,15.44,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,Base Model,pct_premium,10.227927337296784,0.6953635845704899,100*(exp(b - se^2/2) - 1),|b/t|,0.162748331518725,0.010540695046549546,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.44,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c2,2,2,8,Has basement,basement,A_structural,binary,binary,0.097,,15.13,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,CBD Distance,pct_premium,10.183772938258784,0.7064141192414939,100*(exp(b - se^2/2) - 1),|b/t|,0.15956474268227508,0.010546248690170198,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.13,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c3,2,3,8,Has basement,basement,A_structural,binary,binary,0.1087,,17.43,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8627,t,Center Township,pct_premium,11.480617288050187,0.6952483504999537,100*(exp(b - se^2/2) - 1),|b/t|,0.18306031393080896,0.010502599766540962,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.43,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c4,2,4,8,Has basement,basement,A_structural,binary,binary,0.1036,,16.43,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8631,t,Center Township + CBD,pct_premium,10.913465377485299,0.6993830461445232,100*(exp(b - se^2/2) - 1),|b/t|,0.17288086374399667,0.010522268030675392,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.43,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c1,2,1,8,Age,age,A_structural,level,years,-0.0024,,15.71,,*,,,high,t-values printed as absolute values; * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,Base Model,semi_elasticity,-0.24,0.015276893698281347,100*b/1 (per year),|b/t|,0.16551700280185855,0.010535773571092205,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.71,8762.0,years,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c2,2,2,8,Age,age,A_structural,level,years,-0.0024,,14.65,,*,,,high,t-values printed as absolute values; * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,CBD Distance,semi_elasticity,-0.24,0.016382252559726963,100*b/1 (per year),|b/t|,0.15462550952910878,0.010554642288676367,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.65,8762.0,years,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c3,2,3,8,Age,age,A_structural,level,years,-0.0021,,14.17,,*,,,high,t-values printed as absolute values; * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8627,t,Center Township,semi_elasticity,-0.21,0.014820042342978122,100*b/1 (per year),|b/t|,0.14967465522767434,0.010562784419737075,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.17,8762.0,years,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c4,2,4,8,Age,age,A_structural,level,years,-0.0024,,15.07,,*,,,high,t-values printed as absolute values; * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8631,t,Center Township + CBD,semi_elasticity,-0.24,0.0159256801592568,100*b/1 (per year),|b/t|,0.15894798549663772,0.010547311579073506,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.07,8762.0,years,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c1,2,1,8,Lot area <= 0.5 acre,lot_size,A_structural,dummy,binary,-0.0492,,6.23,,*,,,high,dummy for lot <= 0.5 acre (reference 0.5-1.0 acre); * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,Base Model,pct_premium,-4.80389733739065,0.7518128901401923,100*(exp(b - se^2/2) - 1),|b/t|,0.06640895595195097,0.010659543491484907,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.23,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c2,2,2,8,Lot area <= 0.5 acre,lot_size,A_structural,dummy,binary,-0.0493,,6.24,,*,,,high,dummy for lot <= 0.5 acre (reference 0.5-1.0 acre); * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,CBD Distance,pct_premium,-4.813419005327524,0.7520584783242094,100*(exp(b - se^2/2) - 1),|b/t|,0.06651508015760503,0.010659467973975163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.24,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c3,2,3,8,Lot area <= 0.5 acre,lot_size,A_structural,dummy,binary,-0.0416,,5.35,,*,,,high,dummy for lot <= 0.5 acre (reference 0.5-1.0 acre); * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8627,t,Center Township,pct_premium,-4.077559331903069,0.7458867599347334,100*(exp(b - se^2/2) - 1),|b/t|,0.057061602864305616,0.010665720161552452,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.35,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c4,2,4,8,Lot area <= 0.5 acre,lot_size,A_structural,dummy,binary,-0.0426,,5.49,,*,,,high,dummy for lot <= 0.5 acre (reference 0.5-1.0 acre); * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8631,t,Center Township + CBD,pct_premium,-4.173421815016354,0.7435947412010854,100*(exp(b - se^2/2) - 1),|b/t|,0.05854974993413822,0.010664799623704596,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.49,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c1,2,1,8,Lot area >= 1.0 acre,lot_size,A_structural,dummy,binary,0.0956,,6.1,,*,,,high,dummy for lot >= 1.0 acre (reference 0.5-1.0 acre); * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,Base Model,pct_premium,10.018372892522699,1.7244341296508234,100*(exp(b - se^2/2) - 1),|b/t|,0.0650291374754857,0.010660514340243557,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.1,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c2,2,2,8,Lot area >= 1.0 acre,lot_size,A_structural,dummy,binary,0.0959,,6.11,,*,,,high,dummy for lot >= 1.0 acre (reference 0.5-1.0 acre); * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,CBD Distance,pct_premium,10.05134288054419,1.727532544769153,100*(exp(b - se^2/2) - 1),|b/t|,0.0651352907038068,0.010660440377055122,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.11,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c3,2,3,8,Lot area >= 1.0 acre,lot_size,A_structural,dummy,binary,0.0951,,6.18,,*,,,high,dummy for lot >= 1.0 acre (reference 0.5-1.0 acre); * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8627,t,Center Township,pct_premium,9.963862087412245,1.692362708755823,100*(exp(b - se^2/2) - 1),|b/t|,0.06587830118820924,0.010659919286118001,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.18,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c4,2,4,8,Lot area >= 1.0 acre,lot_size,A_structural,dummy,binary,0.0996,,6.47,,*,,,high,dummy for lot >= 1.0 acre (reference 0.5-1.0 acre); * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8631,t,Center Township + CBD,pct_premium,10.459804700930553,1.7006337285283808,100*(exp(b - se^2/2) - 1),|b/t|,0.06895530672122023,0.010657698102197874,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.47,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,True
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c1,2,1,8,Has garage,garage,A_structural,binary,binary,0.0855,,19.81,,*,,,high,"Table 1 and Table 5 label this variable 'Garage bays' (mean 1.622), so it may be a count of bays; Table 2 prints 'Has garage'; * = p<0.001; t-value in parentheses",log sales price,log,OLS,8772.0,0.8579,t,Base Model,pct_premium,8.925141607806374,0.4701255098178578,100*(exp(b - se^2/2) - 1),|b/t|,0.20704687345963874,0.010451634197861622,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.81,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c2,2,2,8,Has garage,garage,A_structural,binary,binary,0.0855,,19.81,,*,,,high,"Table 1 and Table 5 label this variable 'Garage bays' (mean 1.622), so it may be a count of bays; Table 2 prints 'Has garage'; * = p<0.001; t-value in parentheses",log sales price,log,OLS,8772.0,0.8579,t,CBD Distance,pct_premium,8.925141607806374,0.4701255098178578,100*(exp(b - se^2/2) - 1),|b/t|,0.20704687345963874,0.010451634197861622,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.81,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c3,2,3,8,Has garage,garage,A_structural,binary,binary,0.0842,,19.83,,*,,,high,"Table 1 and Table 5 label this variable 'Garage bays' (mean 1.622), so it may be a count of bays; Table 2 prints 'Has garage'; * = p<0.001; t-value in parentheses",log sales price,log,OLS,8772.0,0.8627,t,Center Township,pct_premium,8.783663483339389,0.46190958326255205,100*(exp(b - se^2/2) - 1),|b/t|,0.20724693225329172,0.010451181656746935,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.83,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c4,2,4,8,Has garage,garage,A_structural,binary,binary,0.0843,,19.88,,*,,,high,"Table 1 and Table 5 label this variable 'Garage bays' (mean 1.622), so it may be a count of bays; Table 2 prints 'Has garage'; * = p<0.001; t-value in parentheses",log sales price,log,OLS,8772.0,0.8631,t,Center Township + CBD,pct_premium,8.794545001510269,0.46134117710835665,100*(exp(b - se^2/2) - 1),|b/t|,0.20774696545266655,0.010450048564017433,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.88,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c1,2,1,8,Has porch or deck,terrace_balcony,C_exterior,binary,binary,0.0477,,8.66,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,Base Model,pct_premium,4.8840040846703126,0.577718578276203,100*(exp(b - se^2/2) - 1),|b/t|,0.09212246975172794,0.010637698585649877,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.66,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c2,2,2,8,Has porch or deck,terrace_balcony,C_exterior,binary,binary,0.0478,,8.67,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,CBD Distance,pct_premium,4.8944900147013914,0.5783198184081324,100*(exp(b - se^2/2) - 1),|b/t|,0.09222794241303883,0.010637594280627317,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.67,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c3,2,3,8,Has porch or deck,terrace_balcony,C_exterior,binary,binary,0.0456,,8.42,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8627,t,Center Township,pct_premium,4.664031608642771,0.5668348969311007,100*(exp(b - se^2/2) - 1),|b/t|,0.08959020351833574,0.01064016668863845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.42,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c4,2,4,8,Has porch or deck,terrace_balcony,C_exterior,binary,binary,0.047,,8.68,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8631,t,Center Township + CBD,pct_premium,4.810664399606868,0.567531502612256,100*(exp(b - se^2/2) - 1),|b/t|,0.09233341197007104,0.010637489858303114,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.68,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c1,2,1,8,Exterior brick or stone,roof_materials,A_structural,binary,binary,0.084,,13.95,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,Base Model,pct_premium,8.760917607675612,0.6549163231537019,100*(exp(b - se^2/2) - 1),|b/t|,0.14740172209873026,0.010566431691665252,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.95,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c2,2,2,8,Exterior brick or stone,roof_materials,A_structural,binary,binary,0.0841,,13.96,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,CBD Distance,pct_premium,8.77179237620247,0.6552918150836846,100*(exp(b - se^2/2) - 1),|b/t|,0.14750508820327207,0.010566267063271637,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.96,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c3,2,3,8,Exterior brick or stone,roof_materials,A_structural,binary,binary,0.0777,,13.12,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8627,t,Center Township,pct_premium,8.077941720032022,0.6400764740035004,100*(exp(b - se^2/2) - 1),|b/t|,0.13880579386876996,0.010579709898534295,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.12,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c4,2,4,8,Exterior brick or stone,roof_materials,A_structural,binary,binary,0.0784,,13.25,,*,,,high,* = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8631,t,Center Township + CBD,pct_premium,8.153626141692992,0.6399541677586107,100*(exp(b - se^2/2) - 1),|b/t|,0.1401542695681686,0.010577680722125931,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.25,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c1,2,1,8,No air conditioning,air_conditioning,A_structural,binary,binary,-0.2511,,29.12,,*,,,high,reverse-coded: dummy = 1 if NO air conditioning; * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,Base Model,pct_premium,-22.20843483186774,0.6708169036177157,100*(exp(b - se^2/2) - 1),|b/t|,0.29705047779769483,0.01020090926503073,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.12,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c2,2,2,8,No air conditioning,air_conditioning,A_structural,binary,binary,-0.2512,,29.11,,*,,,high,reverse-coded: dummy = 1 if NO air conditioning; * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8579,t,CBD Distance,pct_premium,-22.21621789195164,0.6712474606670792,100*(exp(b - se^2/2) - 1),|b/t|,0.2969574656567822,0.010201218332421236,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.11,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,True
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c3,2,3,8,No air conditioning,air_conditioning,A_structural,binary,binary,-0.2444,,28.8,,*,,,high,reverse-coded: dummy = 1 if NO air conditioning; * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8627,t,Center Township,pct_premium,-21.685389740161465,0.6646104145118957,100*(exp(b - se^2/2) - 1),|b/t|,0.2940699045385413,0.010210760574254909,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.8,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c4,2,4,8,No air conditioning,air_conditioning,A_structural,binary,binary,-0.2451,,28.91,,*,,,high,reverse-coded: dummy = 1 if NO air conditioning; * = p<0.001; t-value in parentheses,log sales price,log,OLS,8772.0,0.8631,t,Center Township + CBD,pct_premium,-21.74018542396058,0.6635133144033968,100*(exp(b - se^2/2) - 1),|b/t|,0.29509544980919195,0.010207383251788028,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.91,8762.0,binary,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c2,2,2,8,Distance to CBD,cbd_distance,D_location,level,km,-0.0004,,0.35,,,,,high,"not significant; t printed as absolute value; Table 3 reports SE 0.0011, p 0.7285",log sales price,log,OLS,8772.0,0.8579,t,CBD Distance,semi_elasticity,-0.04,0.1142857142857143,100*b/1 (X per km->km),|b/t|,0.003739068177313053,0.010683051935180151,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.35,8762.0,km,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T2-c4,2,4,8,Distance to CBD,cbd_distance,D_location,level,km,-0.0055,,5.1,,*,,,high,model includes Center Township dummy; * = p<0.001,log sales price,log,OLS,8772.0,0.8631,t,Center Township + CBD,semi_elasticity,-0.5499999999999999,0.10784313725490195,100*b/1 (X per km->km),|b/t|,0.05440325752279412,0.010667305396626298,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.1,8762.0,km,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23,ddfcdefd81b294b9edfe4b97744d2d4725aeed23:T3-m4,3,Distance to 3 TAZ employment centers,9,Distance to CBD,cbd_distance,D_location,level,km,0.0005,0.0012,0.4542,0.6497,,,,high,jointly with distances to 2 other employment centres,log sales price,log,OLS,8772.0,0.8605,none,"Base model (Table 2 Model 1 covariates) + Distance to 3 TAZ employment centers; only location coefficients reported with SE, t and p in columns",semi_elasticity,0.05,0.12,100*b/1 (X per km->km),reported,0.0048522189866167156,0.010683000851203689,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.4542,8762.0,km,,2008.0,United States,North America,High income,1999.0,1999.0,single_family,transaction,journal,False,False,unknown,,1999.0,ols,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T4-DS,4,Coefficient,15,PT (Villa),dwelling_type,A_structural,dummy,binary,0.381,0.038,9.903,0.0,,,,high,"Villa vs other property types (condominium, detached); z-value column","log total listing price (logTLP), EUR",log,spatial_error,1154.0,0.664,se,DS: Ivrea + 31 municipalities of the Eporediese area,pct_premium,46.2691161060925,5.562240900556969,100*(exp(b - se^2/2) - 1),reported,0.2809919293154019,0.028374424852610505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.903,1144.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T4-DS,4,Coefficient,15,BC (Building Class-Economic),condition,A_structural,dummy,binary,-0.114,0.035,-3.281,0.001,,,,high,Building category dummy (economic/medium/noble; Italian cadastral building class),"log total listing price (logTLP), EUR",log,spatial_error,1154.0,0.664,se,DS: Ivrea + 31 municipalities of the Eporediese area,pct_premium,-10.828838478166103,3.1229028455884293,100*(exp(b - se^2/2) - 1),reported,-0.09655159033136701,0.02942748867155349,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.281,1144.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T4-DS,4,Coefficient,15,BC (Building Class-Medium),condition,A_structural,dummy,binary,-0.065,0.031,-2.079,0.037,,,,high,Building category dummy,"log total listing price (logTLP), EUR",log,spatial_error,1154.0,0.664,se,DS: Ivrea + 31 municipalities of the Eporediese area,pct_premium,-6.338268938088831,2.9049091364699504,100*(exp(b - se^2/2) - 1),reported,-0.06135113492953777,0.029509925411033075,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.079,1144.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T4-DS,4,Coefficient,15,BC (Building Class-Noble),condition,A_structural,dummy,binary,0.135,0.047,2.862,0.004,,,,high,Building category dummy,"log total listing price (logTLP), EUR",log,spatial_error,1154.0,0.664,se,DS: Ivrea + 31 municipalities of the Eporediese area,pct_premium,14.327334133784419,5.379322886451178,100*(exp(b - se^2/2) - 1),reported,0.08431549264034657,0.02946033984638245,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.862,1144.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T4-DS,4,Coefficient,15,FA (Floor area),living_area,A_structural,level,m2,0.004,0.001,22.816,0.0,,,,high,"Floor area, m2 (mean 139)","log total listing price (logTLP), EUR",log,spatial_error,1154.0,0.664,se,DS: Ivrea + 31 municipalities of the Eporediese area,semi_elasticity,0.4,0.1,100*b/1 (X per m2->m2),reported,0.5592274686613316,0.024510320330528208,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),22.816,1144.0,m2,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T4-DS,4,Coefficient,15,TR (Terrace),terrace_balcony,C_exterior,binary,binary,0.105,0.025,4.126,0.0,,,,high,,"log total listing price (logTLP), EUR",log,spatial_error,1154.0,0.664,se,DS: Ivrea + 31 municipalities of the Eporediese area,pct_premium,11.03635675182366,2.776776525889263,100*(exp(b - se^2/2) - 1),reported,0.12109010287891078,0.029348061773851374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.126,1144.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T4-DS,4,Coefficient,15,US (Unit Status-Partially renovated),renovation,A_structural,dummy,binary,0.271,0.038,7.105,0.0,,,,high,"Unit status dummy, ref. not renovated","log total listing price (logTLP), EUR",log,spatial_error,1154.0,0.664,se,DS: Ivrea + 31 municipalities of the Eporediese area,pct_premium,31.03286714748885,4.982845267461434,100*(exp(b - se^2/2) - 1),reported,0.20557696715827797,0.02893412627139732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.105,1144.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T4-DS,4,Coefficient,15,US (Unit Status-Renovated),renovation,A_structural,dummy,binary,0.466,0.042,10.962,0.0,,,,high,"Unit status dummy, ref. not renovated","log total listing price (logTLP), EUR",log,spatial_error,1154.0,0.664,se,DS: Ivrea + 31 municipalities of the Eporediese area,pct_premium,59.220205764542875,6.693149397263636,100*(exp(b - se^2/2) - 1),reported,0.3083101626674636,0.028125356930073314,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.962,1144.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,True
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T4-DS,4,Coefficient,15,EPC (Energy Performance Certification -B and over),energy_efficiency,A_structural,dummy,binary,0.162,0.066,2.45,0.014,,,,high,EPC class B or better dummy,"log total listing price (logTLP), EUR",log,spatial_error,1154.0,0.664,se,DS: Ivrea + 31 municipalities of the Eporediese area,pct_premium,17.330200464643,7.760677592718599,100*(exp(b - se^2/2) - 1),reported,0.07224647998715969,0.02948835917843252,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.45,1144.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T4-DS,4,Coefficient,15,HT (Heating Type-independent),heating,A_structural,dummy,binary,0.106,0.021,5.013,0.0,,,,high,Independent (autonomous) heating vs central,"log total listing price (logTLP), EUR",log,spatial_error,1154.0,0.664,se,DS: Ivrea + 31 municipalities of the Eporediese area,pct_premium,11.157674680930342,2.334825940663715,100*(exp(b - se^2/2) - 1),reported,0.1466109037527516,0.029246140784510592,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.013,1144.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T4-DS,4,Coefficient,15,E (Elevator),accessibility,B_interior,binary,binary,0.101,0.033,3.054,0.002,,,,high,,"log total listing price (logTLP), EUR",log,spatial_error,1154.0,0.664,se,DS: Ivrea + 31 municipalities of the Eporediese area,pct_premium,10.567443809680999,3.650712917819298,100*(exp(b - se^2/2) - 1),reported,0.08992756187328262,0.02944582903512856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.054,1144.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T4-DS,4,Coefficient,15,HD (Distance from the nearest highway exit),highway_distance,D_location,level,m,-1.42e-05,5.628e-05,-2.517,0.011,,,,medium,Distance unit not stated; sample mean 6151 implies metres. Printed SE 5.628e-05 inconsistent with z=-2.517 (implies SE 5.6e-06); recorded as printed,"log total listing price (logTLP), EUR",log,spatial_error,1154.0,0.664,se,DS: Ivrea + 31 municipalities of the Eporediese area,semi_elasticity,-1.42,5.628,100*b/0.001 (X per m->km),reported,-0.07421146313103469,0.029484093417177074,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.517,1144.0,m,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T5-SS,5,Coefficient,16,BC (Building Class-Noble),condition,A_structural,dummy,binary,0.35,0.078,4.454,0.0,,,,high,Building category dummy,"log total listing price (logTLP), EUR",log,spatial_error,248.0,0.62,se,SS: city of Ivrea only,pct_premium,41.47573043158139,11.068726879027405,100*(exp(b - se^2/2) - 1),reported,0.27738096397411,0.062276821727460706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.454,238.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T5-SS,5,Coefficient,16,FA,living_area,A_structural,level,m2,0.005,0.001,12.813,0.0,,,,high,"Floor area, m2 (mean 112)","log total listing price (logTLP), EUR",log,spatial_error,248.0,0.62,se,SS: city of Ivrea only,semi_elasticity,0.5,0.1,100*b/1 (X per m2->m2),reported,0.6389169172032393,0.04986474027965654,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.813,238.0,m2,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T5-SS,5,Coefficient,16,US1 (Unit Status-Partially renovated),renovation,A_structural,dummy,binary,0.237,0.073,3.248,0.001,,,,high,ref. not renovated,"log total listing price (logTLP), EUR",log,spatial_error,248.0,0.62,se,SS: city of Ivrea only,pct_premium,26.406851606093753,9.25232015975957,100*(exp(b - se^2/2) - 1),reported,0.20602008886547743,0.0634298303157258,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.248,238.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T5-SS,5,Coefficient,16,US2 (Unit Status-Renovated),renovation,A_structural,dummy,binary,0.398,0.085,4.68,0.0,,,,high,ref. not renovated,"log total listing price (logTLP), EUR",log,spatial_error,248.0,0.62,se,SS: city of Ivrea only,pct_premium,48.34752839851393,12.65517425421186,100*(exp(b - se^2/2) - 1),reported,0.2902957703360835,0.062029010755573405,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.68,238.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,True
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T5-SS,5,Coefficient,16,HT (Heating Type-independent),heating,A_structural,dummy,binary,0.135,0.046,2.933,0.003,,,,high,,"log total listing price (logTLP), EUR",log,spatial_error,248.0,0.62,se,SS: city of Ivrea only,pct_premium,14.332650478425712,5.264869208016047,100*(exp(b - se^2/2) - 1),reported,0.1867726733847835,0.06367973862420168,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.933,238.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T5-SS,5,Coefficient,16,PG (Private Garden),garden,C_exterior,binary,binary,0.152,0.065,2.343,0.019,,,,high,,"log total listing price (logTLP), EUR",log,spatial_error,248.0,0.62,se,SS: city of Ivrea only,pct_premium,16.170354372793284,7.567041536808731,100*(exp(b - se^2/2) - 1),reported,0.15015231651540714,0.06408549573854339,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.343,238.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb,ddfdca9d11843f81e9f91bacfe723acfa0d83bbb:T5-SS,5,Coefficient,16,EPC (Energy Performance Certification-B and over),energy_efficiency,A_structural,dummy,binary,0.311,0.14,2.219,0.027,,,,high,,"log total listing price (logTLP), EUR",log,spatial_error,248.0,0.62,se,SS: city of Ivrea only,pct_premium,35.14796104323117,19.10704909660626,100*(exp(b - se^2/2) - 1),reported,0.14237119334591083,0.06416006910586337,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.219,238.0,binary,,2022.0,Italy,Europe,High income,2019.0,2020.0,mixed,listing,journal,False,False,unknown,,2019.5,spatial,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c1,5,1,20,Near,transit_distance,D_location,dummy,binary (within 100 m of bus route vs 100-200 m),-0.0097,0.0038,,,**,,,high,pre-launch proximity to bus route,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,binary closeness indicator (Near = within 100 m of bus route; control 100-200 m); block and time FE,pct_premium,-0.966025702276585,0.37633181943727656,100*(exp(b - se^2/2) - 1),reported,-0.06711607142878724,0.026292893961792935,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5526315789473686,1440.0,binary,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c2,5,2,20,Distance,transit_distance,D_location,level,100 m (distance to bus route),0.0104,0.0037,,,***,,,high,pre-launch distance to bus route,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,continuous distance to bus route; block and time FE,semi_elasticity,10.4,3.6999999999999997,100*b/0.1 (X per 100m->km),reported,0.07386900217237996,0.02628031808055826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8108108108108105,1440.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c1,5,1,20,Floor,floor_level,A_structural,level,count,0.007,0.0003,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,binary closeness indicator (Near = within 100 m of bus route; control 100-200 m); block and time FE,semi_elasticity,0.7000000000000001,0.03,100*b/1 (per unit count),reported,0.5237901326137371,0.02244814854058873,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.333333333333336,1440.0,count,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c2,5,2,20,Floor,floor_level,A_structural,level,count,0.007,0.0003,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,continuous distance to bus route; block and time FE,semi_elasticity,0.7000000000000001,0.03,100*b/1 (per unit count),reported,0.5237901326137371,0.02244814854058873,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.333333333333336,1440.0,count,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c1,5,1,20,Area,living_area,A_structural,level,m2,0.003,0.0008,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,binary closeness indicator (Near = within 100 m of bus route; control 100-200 m); block and time FE,semi_elasticity,0.3,0.08,100*b/1 (X per m2->m2),reported,0.09834215720608248,0.02622457525495533,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.75,1440.0,m2,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c2,5,2,20,Area,living_area,A_structural,level,m2,0.003,0.0008,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,continuous distance to bus route; block and time FE,semi_elasticity,0.3,0.08,100*b/1 (X per m2->m2),reported,0.09834215720608248,0.02622457525495533,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.75,1440.0,m2,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c1,5,1,20,Building age,age,A_structural,level,years,-0.0009,0.0006,,,,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,binary closeness indicator (Near = within 100 m of bus route; control 100-200 m); block and time FE,semi_elasticity,-0.09,0.06,100*b/1 (per year),reported,-0.03949762527666821,0.026331750184445477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5,1440.0,years,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c2,5,2,20,Building age,age,A_structural,level,years,-0.0009,0.0006,,,,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,continuous distance to bus route; block and time FE,semi_elasticity,-0.09,0.06,100*b/1 (per year),reported,-0.03949762527666821,0.026331750184445477,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5,1440.0,years,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c1,5,1,20,Distance to train station,transit_distance,D_location,level,100 m,-0.0035,0.0015,,,**,,,high,distance to MRT train station,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,binary closeness indicator (Near = within 100 m of bus route; control 100-200 m); block and time FE,semi_elasticity,-3.5,1.4999999999999998,100*b/0.1 (X per 100m->km),reported,-0.06137282058924549,0.026302637395390918,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3333333333333335,1440.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c2,5,2,20,Distance to train station,transit_distance,D_location,level,100 m,-0.0036,0.0015,,,**,,,high,distance to MRT train station,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,continuous distance to bus route; block and time FE,semi_elasticity,-3.5999999999999996,1.4999999999999998,100*b/0.1 (X per 100m->km),reported,-0.06311944030978031,0.026299766795741798,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4,1440.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c1,5,1,20,Distance to bus stop,transit_distance,D_location,level,100 m,-0.0042,0.0031,,,,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,binary closeness indicator (Near = within 100 m of bus route; control 100-200 m); block and time FE,semi_elasticity,-4.199999999999999,3.0999999999999996,100*b/0.1 (X per 100m->km),reported,-0.035680400964909376,0.02633553404552835,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3548387096774193,1440.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c2,5,2,20,Distance to bus stop,transit_distance,D_location,level,100 m,-0.0046,0.0032,,,,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,continuous distance to bus route; block and time FE,semi_elasticity,-4.6,3.1999999999999997,100*b/0.1 (X per 100m->km),reported,-0.03785430033168579,0.026333426317694465,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4375,1440.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c1,5,1,20,Distance to expressway,highway_distance,D_location,level,100 m,0.0025,0.0008,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,binary closeness indicator (Near = within 100 m of bus route; control 100-200 m); block and time FE,semi_elasticity,2.5,0.7999999999999999,100*b/0.1 (X per 100m->km),reported,0.08207315387277983,0.02626340923928954,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.125,1440.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c2,5,2,20,Distance to expressway,highway_distance,D_location,level,100 m,0.0024,0.0008,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,continuous distance to bus route; block and time FE,semi_elasticity,2.4,0.7999999999999999,100*b/0.1 (X per 100m->km),reported,0.07881104062391006,0.02627034687463669,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9999999999999996,1440.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c1,5,1,20,Distance to major road,highway_distance,D_location,level,100 m,-0.0014,0.0016,,,,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,binary closeness indicator (Near = within 100 m of bus route; control 100-200 m); block and time FE,semi_elasticity,-1.3999999999999997,1.5999999999999999,100*b/0.1 (X per 100m->km),reported,-0.023052147190514766,0.02634531107487402,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.875,1440.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c2,5,2,20,Distance to major road,highway_distance,D_location,level,100 m,-0.001,0.0017,,,,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,continuous distance to bus route; block and time FE,semi_elasticity,-1.0,1.6999999999999997,100*b/0.1 (X per 100m->km),reported,-0.015499498986792747,0.026349148277547668,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5882352941176471,1440.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c1,5,1,20,Distance to shopping center,commercial_distance,D_location,level,100 m,0.0037,0.0009,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,binary closeness indicator (Near = within 100 m of bus route; control 100-200 m); block and time FE,semi_elasticity,3.6999999999999997,0.8999999999999999,100*b/0.1 (X per 100m->km),reported,0.10770705690763097,0.026199013842396715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.111111111111112,1440.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T5-c2,5,2,20,Distance to shopping center,commercial_distance,D_location,level,100 m,0.0037,0.0009,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,1450.0,0.941,se,continuous distance to bus route; block and time FE,semi_elasticity,3.6999999999999997,0.8999999999999999,100*b/0.1 (X per 100m->km),reported,0.10770705690763097,0.026199013842396715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.111111111111112,1440.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T6-c1,6,1,21,Distance to nearest bus stop connecting CBD,transit_distance,D_location,level,100 m,-0.0027,0.0016,,,*,,,high,,"log(price), HDB resale price (SGD)",log,OLS,893.0,0.919,se,transactions matched with 12-month lagged noise sentiment; block and time FE,semi_elasticity,-2.7,1.5999999999999999,100*b/0.1 (X per 100m->km),reported,-0.056697545899837436,0.03359854571842218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6875,883.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T6-c2,6,2,21,Distance to nearest bus stop connecting CBD,transit_distance,D_location,level,100 m,-0.0027,0.0016,,,*,,,high,,"log(price), HDB resale price (SGD)",log,OLS,893.0,0.919,se,as column 1 plus interaction of noise sentiment with low/high floor dummy,semi_elasticity,-2.7,1.5999999999999999,100*b/0.1 (X per 100m->km),reported,-0.056697545899837436,0.03359854571842218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6875,883.0,100m,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T6-c1,6,1,21,Floor,floor_level,A_structural,level,count,0.0064,0.0005,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,893.0,0.919,se,transactions matched with 12-month lagged noise sentiment; block and time FE,semi_elasticity,0.64,0.05,100*b/1 (per unit count),reported,0.39561232683082437,0.030907213033658155,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.8,883.0,count,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T6-c2,6,2,21,Floor,floor_level,A_structural,level,count,0.0065,0.0006,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,893.0,0.919,se,as column 1 plus interaction of noise sentiment with low/high floor dummy,semi_elasticity,0.65,0.06,100*b/1 (per unit count),reported,0.34251824186221946,0.031617068479589484,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.833333333333334,883.0,count,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T6-c1,6,1,21,Area,living_area,A_structural,level,m2,0.0075,0.0002,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,893.0,0.919,se,transactions matched with 12-month lagged noise sentiment; block and time FE,semi_elasticity,0.75,0.02,100*b/1 (X per m2->m2),reported,0.7837628175659862,0.020900341801759634,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.5,883.0,m2,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T6-c2,6,2,21,Area,living_area,A_structural,level,m2,0.0075,0.0002,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,893.0,0.919,se,as column 1 plus interaction of noise sentiment with low/high floor dummy,semi_elasticity,0.75,0.02,100*b/1 (X per m2->m2),reported,0.7837628175659862,0.020900341801759634,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),37.5,883.0,m2,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T6-c1,6,1,21,Building age,age,A_structural,level,years,-0.0035,0.0009,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,893.0,0.919,se,transactions matched with 12-month lagged noise sentiment; block and time FE,semi_elasticity,-0.35000000000000003,0.09,100*b/1 (per year),reported,-0.12976498333138178,0.03336813857092674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.8888888888888893,883.0,years,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6,de48aa9a311d709ef0a33453d7042001c2e721a6:T6-c2,6,2,21,Building age,age,A_structural,level,years,-0.0035,0.0009,,,***,,,high,,"log(price), HDB resale price (SGD)",log,OLS,893.0,0.919,se,as column 1 plus interaction of noise sentiment with low/high floor dummy,semi_elasticity,-0.35000000000000003,0.09,100*b/1 (per year),reported,-0.12976498333138178,0.03336813857092674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.8888888888888893,883.0,years,,2021.0,Singapore,Asia,High income,2010.0,2018.0,condo_apartment,transaction,journal,True,True,clustered,NLP sentiment analysis of noise complaint texts (noise sentiment score 0-1),2014.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,13,NO2,air_pollution,E_environment,level,ug/m3,-0.0079,0.0008,,,***,,,high,nitrogen dioxide concentration near the property (mean 24.36),"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,semi_elasticity,-0.79,0.08,100*b/1 (per ug/m3),reported,-0.03096760057205867,0.003135959551600878,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.875,101588.0,ug/m3,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,13,NO2,air_pollution,E_environment,level,ug/m3,-0.0014,0.0008,,,*,,,high,nitrogen dioxide concentration near the property (mean 24.36),"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,semi_elasticity,-0.13999999999999999,0.08,100*b/1 (per ug/m3),reported,-0.006513228758737801,0.003721845004993029,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.75,72188.0,ug/m3,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,13,NO2,air_pollution,E_environment,level,ug/m3,-0.0243,0.0017,,,***,,,high,nitrogen dioxide concentration near the property (mean 24.36),"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,semi_elasticity,-2.4299999999999997,0.16999999999999998,100*b/1 (per ug/m3),reported,-0.08366816207904579,0.005853328211291269,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.294117647058824,28983.0,ug/m3,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,True
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,13,Ruido,noise,E_environment,level,db,-0.0013,0.0006,,,**,,,high,day/night noise level in decibels,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,semi_elasticity,-0.13,0.06,100*b/1 (per dB),reported,-0.00679768228731536,0.003137391824914781,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.166666666666667,101588.0,db,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,13,Ruido,noise,E_environment,level,db,0.0,0.0006,,,,,,high,day/night noise level in decibels,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,semi_elasticity,0.0,0.06,100*b/1 (per dB),reported,0.0,0.0037219239518362836,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.0,72188.0,db,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,13,Ruido,noise,E_environment,level,db,-0.0094,0.0015,,,***,,,high,day/night noise level in decibels,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,semi_elasticity,-0.9400000000000001,0.15,100*b/1 (per dB),reported,-0.03678501158638858,0.0058699486574024335,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.266666666666667,28983.0,db,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,13,antigüedad,age,A_structural,log,years,-0.3089,0.0021,,,***,,,high,Table 1 defines as logarithm of building age,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,elasticity,-0.3089,0.0021,b (log-log),reported,-0.41903392431072367,0.0028487252866705066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-147.0952380952381,101588.0,years,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,13,antigüedad,age,A_structural,log,years,-0.2807,0.0024,,,***,,,high,Table 1 defines as logarithm of building age,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,elasticity,-0.2807,0.0024,b (log-log),reported,-0.3991327729760523,0.0034126065377361073,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-116.95833333333334,72188.0,years,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,13,antigüedad,age,A_structural,log,years,-0.37,0.0038,,,***,,,high,Table 1 defines as logarithm of building age,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,elasticity,-0.37,0.0038,b (log-log),reported,-0.4964701129493348,0.005098882241101276,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-97.36842105263158,28983.0,years,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,True
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,13,distancia al centro,cbd_distance,D_location,level,km,-0.0126,0.0011,,,***,,,high,distance to historic centre in thousands of metres,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,semi_elasticity,-1.26,0.11,100*b/1 (X per km->km),reported,-0.03591504193869332,0.0031354401692510045,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.454545454545453,101588.0,km,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,13,distancia al centro,cbd_distance,D_location,level,km,0.0029,0.001,,,***,,,high,distance to historic centre in thousands of metres,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,semi_elasticity,0.29,0.1,100*b/1 (X per km->km),reported,0.01079295078192604,0.003721707166181393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9,72188.0,km,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,13,distancia al centro,cbd_distance,D_location,level,km,-0.0149,0.0027,,,***,,,high,distance to historic centre in thousands of metres,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,semi_elasticity,-1.49,0.27,100*b/1 (X per km->km),reported,-0.03239834210561633,0.005870840515782825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.518518518518518,28983.0,km,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,13,río,waterfront,C_exterior,binary,binary,0.0442,0.0038,,,***,,,high,= 1 if property fronts the river,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,4.518382600599624,0.39717272145897553,100*(exp(b - se^2/2) - 1),reported,0.03646938721160598,0.0031353771810882967,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.631578947368421,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,13,río,waterfront,C_exterior,binary,binary,0.0184,0.0041,,,***,,,high,= 1 if property fronts the river,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,1.856176199666204,0.41761383244814226,100*(exp(b - se^2/2) - 1),reported,0.016700938855154255,0.003721404853594155,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.48780487804878,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,13,río,waterfront,C_exterior,binary,binary,0.0694,0.0068,,,***,,,high,= 1 if property fronts the river,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,7.184008812902465,0.7288681111636658,100*(exp(b - se^2/2) - 1),reported,0.059841145391382806,0.005863397531144136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.205882352941178,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,13,edificio,dwelling_type,A_structural,binary,binary,0.0304,0.0051,,,***,,,high,= 1 if the property is a building (apartment) vs villa,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,3.085339187891778,0.5257420670893713,100*(exp(b - se^2/2) - 1),reported,0.018698478409823156,0.0031369157858584904,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.9607843137254894,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,13,Zona industrial,hazard_site,E_environment,binary,binary,-0.1084,0.0142,,,***,,,high,= 1 if located in an industrial zone,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-10.282184086942115,1.2741214364133453,100*(exp(b - se^2/2) - 1),reported,-0.023943917311496116,0.0031365648138675724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-7.633802816901408,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,13,Zona industrial,hazard_site,E_environment,binary,binary,-0.1337,0.0138,,,***,,,high,= 1 if located in an industrial zone,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-12.52308185040838,1.2072964237568213,100*(exp(b - se^2/2) - 1),reported,-0.03603608855145888,0.003719506522140108,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.688405797101451,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,Terreno,lot_size,A_structural,log,m2,-0.0234,0.0022,,,***,,,high,ln land area; full sample only,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,elasticity,-0.0234,0.0022,b (log-log),reported,-0.03335264513029345,0.0031357187729335726,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.636363636363637,101588.0,m2,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,Número-pisos,storeys,A_structural,log,count,-0.0132,0.0037,,,***,,,high,ln number of floors,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,elasticity,-0.0132,0.0037,b (log-log),reported,-0.011192414829155246,0.0031372677930207884,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5675675675675675,101588.0,count,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,Número-pisos,storeys,A_structural,log,count,0.102,0.0041,,,***,,,high,ln number of floors,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,elasticity,0.102,0.0041,b (log-log),reported,0.09219980307513505,0.0037060705157652327,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.878048780487802,72188.0,count,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,Número-pisos,storeys,A_structural,log,count,-0.1596,0.0071,,,***,,,high,ln number of floors,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,elasticity,-0.1596,0.0071,b (log-log),reported,-0.13090302181732968,0.005823380043252136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.478873239436616,28983.0,count,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,Baños,bathrooms,A_structural,log,count,0.0074,0.0006,,,***,,,high,ln number of bathrooms,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,elasticity,0.0074,0.0006,b (log-log),reported,0.03866645575131317,0.003135118033890256,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.333333333333336,101588.0,count,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,Baños,bathrooms,A_structural,log,count,0.0196,0.0008,,,***,,,high,ln number of bathrooms,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,elasticity,0.0196,0.0008,b (log-log),reported,0.09081037003347109,0.003706545715651882,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.499999999999996,72188.0,count,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,Baños,bathrooms,A_structural,log,count,0.0118,0.001,,,***,,,high,ln number of bathrooms,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,elasticity,0.0118,0.001,b (log-log),reported,0.0691464071373723,0.005859865011641721,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.799999999999999,28983.0,count,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,Tipo-piso: 1. Mezanine,floor_level,A_structural,dummy,binary,0.0803,0.0198,,,***,,,high,floor type mezzanine vs normal (reference),"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,8.339971372062172,2.145551963045148,100*(exp(b - se^2/2) - 1),reported,0.012723130908060001,0.0031372103608915073,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.055555555555555,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,Tipo-piso: 1. Mezanine,floor_level,A_structural,dummy,binary,0.0256,0.0183,,,,,,high,floor type mezzanine vs normal (reference),"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,2.575872164041093,1.8774528043683996,100*(exp(b - se^2/2) - 1),reported,0.005206555284468237,0.003721873504131591,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3989071038251366,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,Tipo-piso: 1. Mezanine,floor_level,A_structural,dummy,binary,0.1643,0.0446,,,***,,,high,floor type mezzanine vs normal (reference),"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,17.739623513762236,5.256412532558397,100*(exp(b - se^2/2) - 1),reported,0.021633629347046754,0.005872549414962174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6838565022421523,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,Tipo-piso: 2. Subsuelo,floor_level,A_structural,dummy,binary,-0.0353,0.0076,,,***,,,high,floor type basement vs normal,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-3.47120998365239,0.7336399913412469,100*(exp(b - se^2/2) - 1),reported,-0.01457114898453436,0.0031371312261320432,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.644736842105263,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,Tipo-piso: 2. Subsuelo,floor_level,A_structural,dummy,binary,-0.016,0.0075,,,**,,,high,floor type basement vs normal,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-1.5900358136365034,0.7380954900414638,100*(exp(b - se^2/2) - 1),reported,-0.007939854149450639,0.003721806632554987,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1333333333333333,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,Tipo-piso: 2. Subsuelo,floor_level,A_structural,dummy,binary,-0.0994,0.0151,,,***,,,high,floor type basement vs normal,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-9.472272862845854,1.3671245299190442,100*(exp(b - se^2/2) - 1),reported,-0.038637885428182875,0.005869537927218928,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.582781456953643,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,Tipo-piso: 3. Ático,floor_level,A_structural,dummy,binary,-0.1202,0.0488,,,**,,,high,floor type attic vs normal,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-11.43121639727135,4.3273061833911575,100*(exp(b - se^2/2) - 1),reported,-0.007727703893915846,0.003137370632471658,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4631147540983607,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,Tipo-piso: 3. Ático,floor_level,A_structural,dummy,binary,-0.0956,0.0597,,,,,,high,floor type attic vs normal,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-9.279065487682125,5.425700021940819,100*(exp(b - se^2/2) - 1),reported,-0.005959959970665851,0.003721857847790286,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6013400335008374,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,Tipo-piso: 3. Ático,floor_level,A_structural,dummy,binary,-0.1507,0.0805,,,*,,,high,floor type attic vs normal,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-14.267664828958704,6.9238508179098455,100*(exp(b - se^2/2) - 1),reported,-0.010995613050821048,0.005873569015203015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8720496894409937,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,Estado construcción: 1. Regular,condition,A_structural,dummy,binary,-0.1481,0.0096,,,***,,,high,construction state regular vs good (reference),"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-13.769485979380658,0.8278510810968605,100*(exp(b - se^2/2) - 1),reported,-0.04834532614946513,0.0031337956180612094,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.427083333333336,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,Estado construcción: 1. Regular,condition,A_structural,dummy,binary,-0.1368,0.009,,,***,,,high,construction state regular vs good (reference),"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-12.789068352466249,0.7849301738561127,100*(exp(b - se^2/2) - 1),reported,-0.056482928566001504,0.003715982142500098,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.200000000000001,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,Estado construcción: 1. Regular,condition,A_structural,dummy,binary,-0.3479,0.0535,,,***,,,high,construction state regular vs good (reference),"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-29.48404043635947,3.778006769534506,100*(exp(b - se^2/2) - 1),reported,-0.03816914128282438,0.005869643744268766,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.502803738317757,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,Estado construcción: 2. Malo,condition,A_structural,dummy,binary,-0.1847,0.0301,,,***,,,high,construction state bad vs good,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-16.90228695310254,2.50237449414755,100*(exp(b - se^2/2) - 1),reported,-0.019248581269021046,0.003136883033013176,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.136212624584718,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,Estado construcción: 2. Malo,condition,A_structural,dummy,binary,-0.1208,0.0278,,,***,,,high,construction state bad vs good,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-11.413119946291783,2.4636670918165002,100*(exp(b - se^2/2) - 1),reported,-0.01617084978602101,0.003721437285193577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.345323741007195,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,Estado construcción: 2. Malo,condition,A_structural,dummy,binary,-0.2844,0.1636,,,*,,,high,construction state bad vs good,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-25.753717730255477,12.310337187560046,100*(exp(b - se^2/2) - 1),reported,-0.010210616951828325,0.005873617908998291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7383863080684596,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,Columnas: 1. Madera,roof_materials,A_structural,dummy,binary,0.2212,0.0244,,,***,,,high,wooden columns vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,24.720159796176855,3.044077925283875,100*(exp(b - se^2/2) - 1),reported,0.028431416021512543,0.003136195980673174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.065573770491802,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,Columnas: 1. Madera,roof_materials,A_structural,dummy,binary,0.1627,0.0236,,,***,,,high,wooden columns vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,17.63559944075015,2.77697337067728,100*(exp(b - se^2/2) - 1),reported,0.025650753291803326,0.0037206993096899716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.89406779661017,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,Columnas: 1. Madera,roof_materials,A_structural,dummy,binary,0.7823,0.3472,,,**,,,high,wooden columns vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,105.85998762568951,75.9151211952057,100*(exp(b - se^2/2) - 1),reported,0.013233780053651154,0.005873409733641417,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.253168202764977,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,"Columnas: 2. Hierro, hormigón armado",roof_materials,A_structural,dummy,binary,0.7626,0.0053,,,***,,,high,iron/reinforced-concrete columns vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,114.38128622484349,1.1362367753251124,100*(exp(b - se^2/2) - 1),reported,0.41145558039752667,0.0028595785157446776,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),143.88679245283018,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,"Columnas: 2. Hierro, hormigón armado",roof_materials,A_structural,dummy,binary,0.7326,0.0053,,,***,,,high,iron/reinforced-concrete columns vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,108.04536169328371,1.1026559036678152,100*(exp(b - se^2/2) - 1),reported,0.4574763401108892,0.0033096158921481207,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),138.22641509433961,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,"Columnas: 2. Hierro, hormigón armado",roof_materials,A_structural,dummy,binary,0.8373,0.022,,,***,,,high,iron/reinforced-concrete columns vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,130.95622398116063,5.0822666873169355,100*(exp(b - se^2/2) - 1),reported,0.2181708735235273,0.00573242471935698,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),38.05909090909091,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,Vigas (Beams): 1. Madera,roof_materials,A_structural,dummy,binary,-0.135,0.0631,,,**,,,high,wooden beams vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-12.802175606479949,5.513147402751498,100*(exp(b - se^2/2) - 1),reported,-0.006712331863203884,0.0031373936338382597,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.13946117274168,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,Vigas (Beams): 1. Madera,roof_materials,A_structural,dummy,binary,-0.1612,0.0583,,,***,,,high,wooden beams vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-15.03233766480756,4.962040267253818,100*(exp(b - se^2/2) - 1),reported,-0.010290606733928755,0.003721726877097062,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.7650085763293313,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,Vigas (Beams): 1. Madera,roof_materials,A_structural,dummy,binary,0.2148,0.1883,,,,,,high,wooden beams vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,21.783117949831208,23.341930666867835,100*(exp(b - se^2/2) - 1),reported,0.006700427916487337,0.005873792256399281,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1407328730748805,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,"Vigas (Beams): 2. Hierro, hormigón armado",roof_materials,A_structural,dummy,binary,0.1275,0.0626,,,**,,,high,iron/reinforced-concrete beams vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,13.376122140600867,7.111265275189674,100*(exp(b - se^2/2) - 1),reported,0.0063900724099618025,0.003137400257753795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.036741214057508,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,"Vigas (Beams): 2. Hierro, hormigón armado",roof_materials,A_structural,dummy,binary,0.0015,0.0577,,,,,,high,iron/reinforced-concrete beams vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-0.01646314467558252,5.778661494496843,100*(exp(b - se^2/2) - 1),reported,9.675712134525305e-05,0.003721923934414068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.025996533795493933,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,"Vigas (Beams): 2. Hierro, hormigón armado",roof_materials,A_structural,dummy,binary,0.2526,0.119,,,**,,,high,iron/reinforced-concrete beams vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,27.82852099093345,15.319681895835789,100*(exp(b - se^2/2) - 1),reported,0.012467545461202533,0.005873467576734369,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.122689075630252,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,Mezanines: 1. Madera,roof_materials,A_structural,dummy,binary,0.2027,0.0205,,,***,,,high,wooden mezzanine vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,22.444768752631596,2.510645253341036,100*(exp(b - se^2/2) - 1),reported,0.031007717567929877,0.0031359556494453015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.88780487804878,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,Mezanines: 1. Madera,roof_materials,A_structural,dummy,binary,0.1018,0.0167,,,***,,,high,wooden mezzanine vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,10.70076397361266,1.8489605686902337,100*(exp(b - se^2/2) - 1),reported,0.022682298105170685,0.0037209663885692575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.095808383233533,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,Mezanines: 1. Madera,roof_materials,A_structural,dummy,binary,0.3019,0.0894,,,***,,,high,wooden mezzanine vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,34.70322240896184,12.090688237503564,100*(exp(b - se^2/2) - 1),reported,0.019832090812781644,0.005872768859432523,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.376957494407159,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,19,"Mezanines: 2. Hormigón armado, simple",roof_materials,A_structural,dummy,binary,0.5772,0.0214,,,***,,,high,concrete mezzanine vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,78.06367409991262,3.8114352682732022,100*(exp(b - se^2/2) - 1),reported,0.08432218694510615,0.003126290368373651,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.971962616822434,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,19,"Mezanines: 2. Hormigón armado, simple",roof_materials,A_structural,dummy,binary,0.2919,0.0175,,,***,,,high,concrete mezzanine vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,33.87641000840165,2.343195949557438,100*(exp(b - se^2/2) - 1),reported,0.06196240057457273,0.003714772216701003,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.68,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,19,"Mezanines: 2. Hormigón armado, simple",roof_materials,A_structural,dummy,binary,0.7122,0.0889,,,***,,,high,concrete mezzanine vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,103.04316278318302,18.122006881394874,100*(exp(b - se^2/2) - 1),reported,0.047005450531255176,0.005867431272435531,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.011248593925758,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Paredes: 1. Madera, bahareque",roof_materials,A_structural,dummy,binary,-0.2604,0.0521,,,***,,,high,walls wood/bahareque vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-23.030212018047614,4.015572211863221,100*(exp(b - se^2/2) - 1),reported,-0.015679371882978806,0.003137078629428555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.998080614203455,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Paredes: 1. Madera, bahareque",roof_materials,A_structural,dummy,binary,-0.159,0.0511,,,***,,,high,walls wood/bahareque vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-14.81165906477332,4.358811394332261,100*(exp(b - se^2/2) - 1),reported,-0.01158016101229521,0.0037216743882282086,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.111545988258317,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,"Paredes: 1. Madera, bahareque",roof_materials,A_structural,dummy,binary,0.4258,0.1666,,,**,,,high,walls wood/bahareque vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,50.9717005973213,25.50337092943259,100*(exp(b - se^2/2) - 1),reported,0.015011014905304564,0.00587326229033288,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5558223289315727,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Paredes: 2. Adobe, Tierra apisonada",roof_materials,A_structural,dummy,binary,-0.1672,0.0447,,,***,,,high,walls adobe/rammed earth vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-15.481441202447744,3.781755835869898,100*(exp(b - se^2/2) - 1),reported,-0.011734852634302814,0.003137248282017558,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.7404921700223714,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Paredes: 2. Adobe, Tierra apisonada",roof_materials,A_structural,dummy,binary,-0.1346,0.0442,,,***,,,high,walls adobe/rammed earth vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-12.678791980013637,3.8633693683801207,100*(exp(b - se^2/2) - 1),reported,-0.011333456758248532,0.003721684908726487,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.0452488687782804,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,"Paredes: 2. Adobe, Tierra apisonada",roof_materials,A_structural,dummy,binary,-1.007,0.231,,,***,,,high,walls adobe/rammed earth vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-64.43045884905416,8.438736701838398,100*(exp(b - se^2/2) - 1),reported,-0.025597850003968265,0.00587199935542867,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.359307359307358,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,True
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Paredes: 3. Hormigón armado, bloque, ladrillo",roof_materials,A_structural,dummy,binary,0.0834,0.0363,,,**,,,high,walls concrete/block/brick vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,8.626059903021343,3.9457247393099326,100*(exp(b - se^2/2) - 1),reported,0.007208201816380732,0.0031373828049714694,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.297520661157025,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Paredes: 3. Hormigón armado, bloque, ladrillo",roof_materials,A_structural,dummy,binary,0.2119,0.0355,,,***,,,high,walls concrete/block/brick vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,23.524567200814907,4.387886181470378,100*(exp(b - se^2/2) - 1),reported,0.022210735997644882,0.0037210057947918507,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.969014084507043,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,"Paredes: 3. Hormigón armado, bloque, ladrillo",roof_materials,A_structural,dummy,binary,-0.1391,0.0424,,,***,,,high,walls concrete/block/brick vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-13.064079091942526,3.6893978824271394,100*(exp(b - se^2/2) - 1),reported,-0.019266773112212112,0.00587283378833784,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2806603773584904,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,Cubierta: 1. Teja,roof_materials,A_structural,dummy,binary,0.0148,0.006,,,**,,,high,roof cover tile vs none/straw (reference),"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,1.489179408699659,0.6089460373822223,100*(exp(b - se^2/2) - 1),reported,0.007738846893185842,0.003137370362102368,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.466666666666667,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,Cubierta: 1. Teja,roof_materials,A_structural,dummy,binary,0.0856,0.0075,,,***,,,high,roof cover tile vs none/straw (reference),"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,8.93398548324258,0.817027869710017,100*(exp(b - se^2/2) - 1),reported,0.0424412830415407,0.003718570359948075,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.413333333333334,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,Cubierta: 1. Teja,roof_materials,A_structural,dummy,binary,0.1007,0.0117,,,***,,,high,roof cover tile vs none/straw (reference),"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,10.586911474640504,1.2939554260015877,100*(exp(b - se^2/2) - 1),reported,0.05049142662778283,0.005866431892205156,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.606837606837606,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Cubierta: 2. Zinc, madera, ladrillo",roof_materials,A_structural,dummy,binary,-0.0763,0.0189,,,***,,,high,roof cover zinc/wood/brick vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-7.362726617855797,1.7511572044259498,100*(exp(b - se^2/2) - 1),reported,-0.01266504376013582,0.003137212674529056,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.037037037037037,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Cubierta: 2. Zinc, madera, ladrillo",roof_materials,A_structural,dummy,binary,0.0528,0.0183,,,***,,,high,roof cover zinc/wood/brick vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,5.404227139203321,1.9292203679078601,100*(exp(b - se^2/2) - 1),reported,0.010738046695996283,0.003721709366225984,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8852459016393444,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,"Cubierta: 2. Zinc, madera, ladrillo",roof_materials,A_structural,dummy,binary,-0.1581,0.1007,,,,,,high,roof cover zinc/wood/brick vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-15.055343792597641,8.597407520682072,100*(exp(b - se^2/2) - 1),reported,-0.00922172705739462,0.0058736743496498305,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5700099304865938,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Cubierta: 3. Hormigón armado, asbesto",roof_materials,A_structural,dummy,binary,0.1344,0.0031,,,***,,,high,roof cover reinforced concrete/asbestos vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,14.384477206879343,0.3545935831593996,100*(exp(b - se^2/2) - 1),reported,0.13478305594315065,0.003108835367736362,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),43.354838709677416,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Cubierta: 3. Hormigón armado, asbesto",roof_materials,A_structural,dummy,binary,0.0758,0.0029,,,***,,,high,roof cover reinforced concrete/asbestos vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,7.874226709949506,0.31283657293387696,100*(exp(b - se^2/2) - 1),reported,0.09682628573551331,0.0037044357339444402,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),26.13793103448276,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,"Cubierta: 3. Hormigón armado, asbesto",roof_materials,A_structural,dummy,binary,0.3149,0.0096,,,***,,,high,roof cover reinforced concrete/asbestos vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,37.00591580963728,1.3153174002018901,100*(exp(b - se^2/2) - 1),reported,0.18919703754361988,0.00576783601276199,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),32.802083333333336,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Piso: 1. Ladrillo, madera, piedra",flooring,B_interior,dummy,binary,-0.0564,0.0132,,,***,,,high,flooring brick/wood/stone vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-5.492134297014195,1.247612514547194,100*(exp(b - se^2/2) - 1),reported,-0.013404324964157532,0.0031371824384198482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.2727272727272725,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Piso: 1. Ladrillo, madera, piedra",flooring,B_interior,dummy,binary,0.0703,0.0122,,,***,,,high,flooring brick/wood/stone vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,7.275014493980181,1.3088525780110711,100*(exp(b - se^2/2) - 1),reported,0.02144189337626004,0.0037210682672883717,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.7622950819672125,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,"Piso: 1. Ladrillo, madera, piedra",flooring,B_interior,dummy,binary,-0.5387,0.0388,,,***,,,high,flooring brick/wood/stone vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-41.69327338754909,2.26400451282267,100*(exp(b - se^2/2) - 1),reported,-0.08128382200853994,0.005854487272937349,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.884020618556699,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,True
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Piso: 2. Cerámica, parquet, vinilo, moqueta, baldosa, mármol",flooring,B_interior,dummy,binary,0.0013,0.0132,,,,,,high,flooring ceramic/parquet/vinyl/carpet/tile/marble vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,0.12136158364108862,1.321717115883497,100*(exp(b - se^2/2) - 1),reported,0.00030899268288817636,0.003137464164710714,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.09848484848484848,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Piso: 2. Cerámica, parquet, vinilo, moqueta, baldosa, mármol",flooring,B_interior,dummy,binary,0.1249,0.0122,,,***,,,high,flooring ceramic/parquet/vinyl/carpet/tile/marble vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,13.295082654915191,1.382302875542229,100*(exp(b - se^2/2) - 1),reported,0.03807632743961881,0.0037192249380572414,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.237704918032787,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,"Piso: 2. Cerámica, parquet, vinilo, moqueta, baldosa, mármol",flooring,B_interior,dummy,binary,-0.4724,0.0373,,,***,,,high,flooring ceramic/parquet/vinyl/carpet/tile/marble vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-37.69295252479045,2.325670149045176,100*(exp(b - se^2/2) - 1),reported,-0.07418753731754685,0.005857737387689453,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.664879356568365,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,Puerta: 1. Madera,roof_materials,A_structural,dummy,binary,0.1995,0.019,,,***,,,high,wooden doors vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,22.05718763228508,2.3195051979188843,100*(exp(b - se^2/2) - 1),reported,0.0329255136770877,0.0031357632073416857,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.5,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,Puerta: 1. Madera,roof_materials,A_structural,dummy,binary,0.3527,0.0255,,,***,,,high,wooden doors vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,42.24416616001947,3.6284057307418753,100*(exp(b - se^2/2) - 1),reported,0.05141123887316226,0.003717001959925256,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.831372549019608,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,Puerta: 1. Madera,roof_materials,A_structural,dummy,binary,0.5784,0.0351,,,***,,,high,wooden doors vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,78.20849427497858,6.258972520141204,100*(exp(b - se^2/2) - 1),reported,0.09634395964943113,0.005846599211090996,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),16.47863247863248,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Puerta: 2. Hierro, aluminio",roof_materials,A_structural,dummy,binary,0.163,0.0192,,,***,,,high,iron/aluminium doors vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,17.681975827883644,2.2599104442018563,100*(exp(b - se^2/2) - 1),reported,0.026626321220168184,0.0031363519474063135,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.489583333333334,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Puerta: 2. Hierro, aluminio",roof_materials,A_structural,dummy,binary,0.3292,0.0252,,,***,,,high,iron/aluminium doors vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,38.941456199334155,3.502436613359388,100*(exp(b - se^2/2) - 1),reported,0.048563954492466296,0.0037175323609056816,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.063492063492063,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,"Puerta: 2. Hierro, aluminio",roof_materials,A_structural,dummy,binary,0.5806,0.0485,,,***,,,high,iron/aluminium doors vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,78.50097457131943,8.667485320494777,100*(exp(b - se^2/2) - 1),reported,0.07014433038073369,0.005859455775862183,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.971134020618557,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,Ventana: 1. Madera,roof_materials,A_structural,dummy,binary,-0.019,0.0192,,,,,,high,wooden windows vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-1.9001472071040304,1.8838643755061872,100*(exp(b - se^2/2) - 1),reported,-0.003104767430108724,0.003137449192530921,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9895833333333334,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,Ventana: 1. Madera,roof_materials,A_structural,dummy,binary,0.1068,0.0252,,,***,,,high,wooden windows vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,11.235843775513455,2.8040334585117903,100*(exp(b - se^2/2) - 1),reported,0.01577190615610475,0.003721461003125839,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.238095238095238,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,Ventana: 1. Madera,roof_materials,A_structural,dummy,binary,-0.2119,0.0572,,,***,,,high,wooden windows vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-19.22768537859364,4.627740821024548,100*(exp(b - se^2/2) - 1),reported,-0.02175506889986676,0.0058725339361603525,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.7045454545454546,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Ventana: 2. Hierro, aluminio",roof_materials,A_structural,dummy,binary,-0.0057,0.016,,,,,,high,iron/aluminium windows vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-0.5811050151890651,1.590905942685493,100*(exp(b - se^2/2) - 1),reported,-0.0011177209638511172,0.003137462354669803,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.35625,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Ventana: 2. Hierro, aluminio",roof_materials,A_structural,dummy,binary,0.1266,0.023,,,***,,,high,iron/aluminium windows vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,13.466278379516595,2.610414766129938,100*(exp(b - se^2/2) - 1),reported,0.020482466141739594,0.0037211431379147765,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.504347826086956,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,"Ventana: 2. Hierro, aluminio",roof_materials,A_structural,dummy,binary,-0.0052,0.027,,,,,,high,iron/aluminium windows vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-0.5549046846186179,2.6859964408085704,100*(exp(b - se^2/2) - 1),reported,-0.00113127355009862,0.005873920356281296,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.1925925925925926,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,Enlucido: 1. Barro,roof_materials,A_structural,dummy,binary,0.0872,0.0259,,,***,,,high,mud plaster vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,9.074897685343931,2.8259875414626485,100*(exp(b - se^2/2) - 1),reported,0.010562611039528283,0.003137289288116772,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3667953667953667,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,Enlucido: 1. Barro,roof_materials,A_structural,dummy,binary,0.1161,0.0244,,,***,,,high,mud plaster vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,12.277390024967527,2.7403839526989486,100*(exp(b - se^2/2) - 1),reported,0.017706869845553384,0.003721340432657214,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.758196721311475,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,Enlucido: 1. Barro,roof_materials,A_structural,dummy,binary,1.0755,0.193,,,***,,,high,mud plaster vs none (reference),"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,187.73665975484008,56.5771444815767,100*(exp(b - se^2/2) - 1),reported,0.03271514912510937,0.005870779898787642,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.572538860103626,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,True
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Enlucido: 2. Arena, cal, cemento, granito",roof_materials,A_structural,dummy,binary,-0.0011,0.0102,,,,,,high,sand/lime/cement/granite plaster vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-0.11513566797036745,1.0188786168737922,100*(exp(b - se^2/2) - 1),reported,-0.00033835397533169757,0.003137464134893923,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.10784313725490197,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Enlucido: 2. Arena, cal, cemento, granito",roof_materials,A_structural,dummy,binary,0.0747,0.0097,,,***,,,high,sand/lime/cement/granite plaster vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,7.7510141482288075,1.0452340091151238,100*(exp(b - se^2/2) - 1),reported,0.028650884847669953,0.0037203960243962324,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.701030927835052,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,"Enlucido: 2. Arena, cal, cemento, granito",roof_materials,A_structural,dummy,binary,-0.0132,0.0452,,,,,,high,sand/lime/cement/granite plaster vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,-1.4120871872478902,4.460728055460099,100*(exp(b - se^2/2) - 1),reported,-0.0017153912442494609,0.0058739154727330024,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2920353982300885,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Techo: 1. barro, latón, cartón",roof_materials,A_structural,dummy,binary,0.4513,0.2123,,,**,,,high,ceiling mud/tin/cardboard vs none (reference); blank for edificios,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,53.535919204904324,33.33857969266041,100*(exp(b - se^2/2) - 1),reported,0.006669364832889325,0.0031373945358351514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.125765426283561,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Techo: 1. barro, latón, cartón",roof_materials,A_structural,dummy,binary,0.4456,0.1971,,,**,,,high,ceiling mud/tin/cardboard vs none (reference); blank for edificios,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,53.13899621700864,30.775721654332322,100*(exp(b - se^2/2) - 1),reported,0.0084141583104317,0.003721792197006481,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.26078132927448,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Techo: 2. Fundición, madera, fibra mineral",roof_materials,A_structural,dummy,binary,0.1235,0.0102,,,***,,,high,ceiling cast/wood/mineral fibre vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,13.139114804371332,1.1540790046329203,100*(exp(b - se^2/2) - 1),reported,0.03796054554341064,0.00313520295176347,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.107843137254902,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Techo: 2. Fundición, madera, fibra mineral",roof_materials,A_structural,dummy,binary,0.0894,0.01,,,***,,,high,ceiling cast/wood/mineral fibre vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,9.346330151504635,1.093517976046974,100*(exp(b - se^2/2) - 1),reported,0.03325559560479727,0.0037198652801786656,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.94,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,"Techo: 2. Fundición, madera, fibra mineral",roof_materials,A_structural,dummy,binary,0.1116,0.0469,,,**,,,high,ceiling cast/wood/mineral fibre vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,11.68365668352276,5.243727405908767,100*(exp(b - se^2/2) - 1),reported,0.013975818931695945,0.005873350429180463,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.37953091684435,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c1,3,Muestra total,20,"Techo: 3. Arena, cal, cemento",roof_materials,A_structural,dummy,binary,0.2264,0.0128,,,***,,,high,ceiling sand/lime/cement vs none,"ln(cadastral value per m2 built, USD)",log,OLS,101598.0,0.7385,se,Full sample; robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,25.397446604771055,1.6052188106799672,100*(exp(b - se^2/2) - 1),reported,0.055408648160038064,0.0031326444189420815,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),17.6875,101588.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c2,3,Villas,20,"Techo: 3. Arena, cal, cemento",roof_materials,A_structural,dummy,binary,0.1841,0.015,,,***,,,high,ceiling sand/lime/cement vs none,"ln(cadastral value per m2 built, USD)",log,OLS,72198.0,0.758,se,Villas (detached houses); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,20.200079799241987,1.8032040460333358,100*(exp(b - se^2/2) - 1),reported,0.04563282710000797,0.003718046749050079,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.273333333333335,72188.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82,dfd836c56fd33dc021acfdf9971e3bbd78377b82:T3-c3,3,Edificios,20,"Techo: 3. Arena, cal, cemento",roof_materials,A_structural,dummy,binary,0.3722,0.0454,,,***,,,high,ceiling sand/lime/cement vs none,"ln(cadastral value per m2 built, USD)",log,OLS,28993.0,0.5837,se,Edificios (buildings/apartments); robust SE in parentheses; Table A1 (pp.19-20) continues the same model,pct_premium,44.9428614782162,6.5871910415442105,100*(exp(b - se^2/2) - 1),reported,0.04810008785172625,0.005867125170522225,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.198237885462554,28983.0,binary,,2025.0,Ecuador,South America,Upper middle income,2018.0,2018.0,mixed,appraisal,journal,False,False,robust,,2018.0,ols,journal,True,True,False
e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f:T2-c1,2,1,6,LF,floor_level,A_structural,dummy,count,0.004,,,0.277,,,,high,Low floor dummy (floors 1-2 vs middle floors 3-4 reference); p-value printed in adjacent column,"ln housing price (total transaction price, CNY)",log,OLS,17095.0,0.82,p,Without-elevator sample (adj. R2); year FE + district FE,pct_premium,0.40012139468215135,0.36943186074858003,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.00831649462161826,0.00765028279230872,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0870832944867503,17085.0,count,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,journal,True,True,unknown,,2019.0,ols,journal,True,True,False
e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f:T2-c1,2,1,6,S,sunlight,E_environment,binary,binary,0.032,,,0.003,***,,,high,South-facing orientation dummy; p-value printed in adjacent column,"ln housing price (total transaction price, CNY)",log,OLS,17095.0,0.82,p,Without-elevator sample (adj. R2); year FE + district FE,pct_premium,3.245748424417827,1.1133247274844402,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.02269896956910266,0.007648576168156257,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9677379253417833,17085.0,binary,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,journal,True,True,unknown,,2019.0,ols,journal,True,True,False
e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f:T2-c2,2,2,6,LF,floor_level,A_structural,dummy,count,-0.055,,,0.048,**,,,high,Low floor dummy (floors 1-2 vs middle floors 3-4 reference); p-value printed in adjacent column,"ln housing price (total transaction price, CNY)",log,OLS,857.0,0.713,p,Installed (retrofitted) elevator sample (adj. R2); year FE + district FE,pct_premium,-5.38809101278831,2.6326243706290042,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.06778690188642908,0.03428137160496409,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9773684281819468,847.0,count,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,journal,True,True,unknown,,2019.0,ols,journal,True,True,False
e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f:T2-c2,2,2,6,HF,floor_level,A_structural,dummy,count,0.014,,,0.477,,,,high,High floor dummy (floors 5-7 vs middle floors 3-4 reference); p-value printed in adjacent column,"ln housing price (total transaction price, CNY)",log,OLS,857.0,0.713,p,Installed (retrofitted) elevator sample (adj. R2); year FE + district FE,pct_premium,1.390196060919635,1.996436631671782,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.024427628746899476,0.03435015352470729,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7111359409013772,847.0,count,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,journal,True,True,unknown,,2019.0,ols,journal,True,True,False
e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f:T2-c2,2,2,6,lnAG,age,A_structural,log,years,-0.034,,,0.083,*,,,high,Log building age (years); p-value printed in adjacent column,"ln housing price (total transaction price, CNY)",log,OLS,857.0,0.713,p,Installed (retrofitted) elevator sample (adj. R2); year FE + district FE,elasticity,-0.034,0.019613063064160757,b (log-log),|b/z(p)| (two-sided normal),-0.0594596998112308,0.03429961300510991,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7335385038417948,847.0,years,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,journal,True,True,unknown,,2019.0,ols,journal,True,True,False
e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f:T2-c2,2,2,6,S,sunlight,E_environment,binary,binary,0.027,,,0.282,,,,high,South-facing orientation dummy; p-value printed in adjacent column,"ln housing price (total transaction price, CNY)",log,OLS,857.0,0.713,p,Installed (retrofitted) elevator sample (adj. R2); year FE + district FE,pct_premium,2.7044312021136996,2.578357257251985,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.03694097788291456,0.03433695391205722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0758373610404317,847.0,binary,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,journal,True,True,unknown,,2019.0,ols,journal,True,True,False
e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f:T2-c2,2,2,6,D,condition,A_structural,binary,binary,0.064,,,0.001,***,,,high,Well-decorated (fit-out) dummy; p-value printed in adjacent column,"ln housing price (total transaction price, CNY)",log,OLS,857.0,0.713,p,Installed (retrofitted) elevator sample (adj. R2); year FE + district FE,pct_premium,6.589076981519337,2.0735255808057675,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.11234802033629712,0.03414286814967146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.290526731491894,847.0,binary,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,journal,True,True,unknown,,2019.0,ols,journal,True,True,False
e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f,e1b44941a0d59a0ba33dc85660a7305568feae7f:T2-c2,2,2,6,BN,bedrooms,A_structural,level,count,0.058,,,0.001,***,,,high,Number of bedrooms; p-value printed in adjacent column,"ln housing price (total transaction price, CNY)",log,OLS,857.0,0.713,p,Installed (retrofitted) elevator sample (adj. R2); year FE + district FE,semi_elasticity,5.800000000000001,1.7626357338146694,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.11234802033629712,0.03414286814967146,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.290526731491894,847.0,count,,2024.0,China,Asia,Upper middle income,2017.0,2021.0,condo_apartment,transaction,journal,True,True,unknown,,2019.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c2,3,Model 2 Semi-log,12,DIST_TO_ST,transit_distance,D_location,level,m,1e-05,,-0.355,,,,,medium,Distance to nearest urban rail station; semi-log column prints positive coefficient with negative t (as printed),ln(Price per sq.m),log,OLS,55.0,0.861,t,Dependent variable is log of price per sq.m,semi_elasticity,1.0,2.816901408450705,100*b/0.001 (X per m->km),|b/t|,-0.05284632766675901,0.14886289483594087,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.355,45.0,m,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c3,3,Model 3 Double-log,12,DIST_TO_ST,transit_distance,D_location,log,m,-0.00781,,-0.267,,,,,high,Distance to nearest urban rail station; semi-log column prints positive coefficient with negative t (as printed),ln(Price per sq.m),log,OLS,55.0,0.83,t,Continuous regressors in logs; dummies unchanged,elasticity,-0.00781,0.029250936329588015,b (log-log),|b/t|,-0.039770520237001526,0.14895325931461245,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.267,45.0,m,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c2,3,Model 2 Semi-log,12,CORE_CBD,cbd_distance,D_location,binary,binary,-0.04,,-0.258,,,,,high,Dummy = 1 if located in core CBD,ln(Price per sq.m),log,OLS,55.0,0.861,t,Dependent variable is log of price per sq.m,pct_premium,-5.068870365077805,14.895960296935243,100*(exp(b - se^2/2) - 1),|b/t|,-0.03843195544228092,0.14896106760573996,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.258,45.0,binary,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c3,3,Model 3 Double-log,12,CORE_CBD,cbd_distance,D_location,binary,binary,-0.00833,,-0.216,,,,,high,Dummy = 1 if located in core CBD,ln(Price per sq.m),log,OLS,55.0,0.83,t,Continuous regressors in logs; dummies unchanged,pct_premium,-0.9032581382727778,3.82449041850322,100*(exp(b - se^2/2) - 1),|b/t|,-0.032182699686605316,0.1489939800305802,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.216,45.0,binary,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c2,3,Model 2 Semi-log,12,FLOORS,storeys,A_structural,level,count,-0.00038,,-0.6,,,,,high,Number of floors of the building,ln(Price per sq.m),log,OLS,55.0,0.861,t,Dependent variable is log of price per sq.m,semi_elasticity,-0.038,0.06333333333333334,100*b/1 (per unit count),|b/t|,-0.0890870806374748,0.14847846772912465,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6,45.0,count,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c3,3,Model 3 Double-log,12,FLOORS,storeys,A_structural,log,count,-0.04395,,-0.935,,,,,high,Number of floors of the building,ln(Price per sq.m),log,OLS,55.0,0.83,t,Continuous regressors in logs; dummies unchanged,elasticity,-0.04395,0.04700534759358289,b (log-log),|b/t|,-0.1380470850585011,0.14764394123903862,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.935,45.0,count,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c2,3,Model 2 Semi-log,12,AREA,lot_size,A_structural,level,m2,-1e-05,,-1.522,,,,,high,"Project (site) area in sq.m, not unit size",ln(Price per sq.m),log,OLS,55.0,0.861,t,Dependent variable is log of price per sq.m,semi_elasticity,-0.001,0.000657030223390276,100*b/1 (X per m2->m2),|b/t|,-0.22126280801747927,0.14537635217968414,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.522,45.0,m2,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c3,3,Model 3 Double-log,12,AREA,lot_size,A_structural,log,m2,-0.01511,,-0.329,,,,,high,"Project (site) area in sq.m, not unit size",ln(Price per sq.m),log,OLS,55.0,0.83,t,Continuous regressors in logs; dummies unchanged,elasticity,-0.01511,0.04592705167173252,b (log-log),|b/t|,-0.04898554586368482,0.14889223666773502,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.329,45.0,m2,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c2,3,Model 2 Semi-log,12,FACILITY,recreation_private,C_exterior,binary,binary,-0.01804,,-1.089,,,,,high,"Common facilities (pool, exercise room, sauna)",ln(Price per sq.m),log,OLS,55.0,0.861,t,Dependent variable is log of price per sq.m,pct_premium,-1.8013001457486522,1.626949156154009,100*(exp(b - se^2/2) - 1),|b/t|,-0.1602407893254032,0.1471448937790663,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.089,45.0,binary,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,True
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c3,3,Model 3 Double-log,12,FACILITY,recreation_private,C_exterior,binary,binary,-0.00618,,-0.136,,,,,high,"Common facilities (pool, exercise room, sauna)",ln(Price per sq.m),log,OLS,55.0,0.83,t,Continuous regressors in logs; dummies unchanged,pct_premium,-0.7186502958823171,4.516121596897968,100*(exp(b - se^2/2) - 1),|b/t|,-0.020269517812822435,0.14904057215310612,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.136,45.0,binary,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c3,3,Model 3 Double-log,12,CAR_PARK,parking,A_structural,log,share,0.10543,,1.447,,,,,high,Percentage of car parking lots per unit,ln(Price per sq.m),log,OLS,55.0,0.83,t,Continuous regressors in logs; dummies unchanged,elasticity,0.10543,0.07286109191430545,b (log-log),|b/t|,0.2108563197153313,0.14571964043906793,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.447,45.0,share,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c2,3,Model 2 Semi-log,12,PARK,green_space,E_environment,binary,binary,0.069,,4.076,,***,,,high,Private recreation park inside the project,ln(Price per sq.m),log,OLS,55.0,0.861,t,Dependent variable is log of price per sq.m,pct_premium,7.128269972478574,1.813765908519036,100*(exp(b - se^2/2) - 1),|b/t|,0.5192724272222081,0.12739755329298533,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.076,45.0,binary,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c3,3,Model 3 Double-log,12,PARK,green_space,E_environment,binary,binary,0.1503,,3.525,,***,,,high,Private recreation park inside the project,ln(Price per sq.m),log,OLS,55.0,0.83,t,Continuous regressors in logs; dummies unchanged,pct_premium,16.112688688971954,4.9553498339551005,100*(exp(b - se^2/2) - 1),|b/t|,0.46516417096089224,0.1319614669392602,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.525,45.0,binary,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c2,3,Model 2 Semi-log,12,MAIN_RD,highway_distance,D_location,level,m,1e-05,,0.288,,,,,high,Distance to nearest main road,ln(Price per sq.m),log,OLS,55.0,0.861,t,Dependent variable is log of price per sq.m,semi_elasticity,1.0,3.4722222222222228,100*b/0.001 (X per m->km),|b/t|,0.04289299318421739,0.14893400411186594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.288,45.0,m,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c3,3,Model 3 Double-log,12,MAIN_RD,highway_distance,D_location,log,m,-0.00219,,-0.193,,,,,high,Distance to nearest main road,ln(Price per sq.m),log,OLS,55.0,0.83,t,Continuous regressors in logs; dummies unchanged,elasticity,-0.00219,0.011347150259067358,b (log-log),|b/t|,-0.028758841127341325,0.14900953951990326,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.193,45.0,m,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c2,3,Model 2 Semi-log,12,EXPWAY,highway_distance,D_location,level,m,-3e-05,,-2.76,,***,,,high,Distance to nearest expressway,ln(Price per sq.m),log,OLS,55.0,0.861,t,Dependent variable is log of price per sq.m,semi_elasticity,-3.0,1.0869565217391304,100*b/0.001 (X per m->km),|b/t|,-0.38049027802218993,0.13785879638485143,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.76,45.0,m,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,True
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c3,3,Model 3 Double-log,12,EXPWAY,highway_distance,D_location,log,m,-0.08183,,-2.855,,***,,,high,Distance to nearest expressway,ln(Price per sq.m),log,OLS,55.0,0.83,t,Continuous regressors in logs; dummies unchanged,elasticity,-0.08183,0.02866199649737303,b (log-log),|b/t|,-0.39160685956517555,0.1371652748039144,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.855,45.0,m,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c2,3,Model 2 Semi-log,12,DEPART,commercial_distance,D_location,level,m,1e-05,,0.361,,,,,high,Distance to nearest department store/mall,ln(Price per sq.m),log,OLS,55.0,0.861,t,Dependent variable is log of price per sq.m,semi_elasticity,1.0,2.770083102493075,100*b/0.001 (X per m->km),|b/t|,0.05373694721652093,0.14885580946404692,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.361,45.0,m,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c3,3,Model 3 Double-log,12,DEPART,commercial_distance,D_location,log,m,0.00861,,0.35,,,,,high,Distance to nearest department store/mall,ln(Price per sq.m),log,OLS,55.0,0.83,t,Continuous regressors in logs; dummies unchanged,elasticity,0.00861,0.0246,b (log-log),|b/t|,0.05210404827496326,0.14886870935703791,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.35,45.0,m,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c2,3,Model 2 Semi-log,12,SCHOOL,school_distance,D_location,level,m,1e-05,,0.298,,,,,high,Distance to nearest school/university,ln(Price per sq.m),log,OLS,55.0,0.861,t,Dependent variable is log of price per sq.m,semi_elasticity,1.0,3.3557046979865777,100*b/0.001 (X per m->km),|b/t|,0.044379449040121935,0.1489243256379931,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.298,45.0,m,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c3,3,Model 3 Double-log,12,SCHOOL,school_distance,D_location,log,m,0.00813,,0.308,,,,,high,Distance to nearest school/university,ln(Price per sq.m),log,OLS,55.0,0.83,t,Continuous regressors in logs; dummies unchanged,elasticity,0.00813,0.026396103896103897,b (log-log),|b/t|,0.04586561019812378,0.14891431882507722,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.308,45.0,m,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c2,3,Model 2 Semi-log,12,HOSP,hospital_distance,D_location,level,m,2e-05,,0.961,,,,,high,Distance to nearest hospital,ln(Price per sq.m),log,OLS,55.0,0.861,t,Dependent variable is log of price per sq.m,semi_elasticity,2.0,2.081165452653486,100*b/0.001 (X per m->km),|b/t|,0.14180965434514142,0.14756467673792031,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.961,45.0,m,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139,e2aec14baa7ef3008564e4685e54665957939139:T3-c3,3,Model 3 Double-log,12,HOSP,hospital_distance,D_location,log,m,0.03615,,1.176,,,,,high,Distance to nearest hospital,ln(Price per sq.m),log,OLS,55.0,0.83,t,Continuous regressors in logs; dummies unchanged,elasticity,0.03615,0.03073979591836735,b (log-log),|b/t|,0.17267442426880303,0.14683199342585293,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.176,45.0,m,,2022.0,Thailand,Asia,Upper middle income,2014.0,2018.0,condo_apartment,listing,journal,False,False,unknown,,2016.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Number of Bedrooms,bedrooms,A_structural,level,count,0.19084,0.01905,,,***,,,medium,,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",semi_elasticity,19.084,1.905,100*b/1 (per unit count),reported,0.4180068176221759,0.04172620978674519,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),10.01784776902887,474.0,count,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Number of Restrooms,bathrooms,A_structural,level,count,0.22406,0.01556,,,***,,,medium,Restrooms = bathrooms/washrooms,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),semi_elasticity,22.406000000000002,1.5559999999999998,100*b/1 (per unit count),reported,0.5516565529114305,0.03831016675578798,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.39974293059126,474.0,count,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Grocery Store within 1 km,commercial_distance,D_location,binary,binary (<=1 km),0.17134,0.07043,,,**,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,18.395414585635848,8.359296022895144,100*(exp(b - se^2/2) - 1),reported,0.11104969932612374,0.04564742805847378,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.432770126366605,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Grocery Store within 1 km,commercial_distance,D_location,binary,binary (<=1 km),0.12619,0.06453,,,*,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,13.213806687764906,7.320913673394182,100*(exp(b - se^2/2) - 1),reported,0.08946007558597584,0.045747354604667737,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9555245622191226,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,School within 1 km,school_distance,D_location,binary,binary (<=1 km),-0.19937,0.07551,,,***,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,-18.308553209555722,6.18613195224163,100*(exp(b - se^2/2) - 1),reported,-0.12039148733627232,0.0455974379734259,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.640312541385247,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,School within 1 km,school_distance,D_location,binary,binary (<=1 km),-0.22155,0.06892,,,***,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,-20.062490131792565,5.5223932088800165,100*(exp(b - se^2/2) - 1),reported,-0.14606769369331193,0.045438887155689715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.214596633778294,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,True
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,College within 1 km,university_distance,D_location,binary,binary (<=1 km),0.17704,0.11147,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,18.62857643253588,13.305938021964486,100*(exp(b - se^2/2) - 1),reported,0.07275648437230786,0.045809790516161075,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5882300170449448,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,College within 1 km,university_distance,D_location,binary,binary (<=1 km),0.10853,0.1022,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,10.883241130365494,11.391603908252925,100*(exp(b - se^2/2) - 1),reported,0.048718479652541724,0.04587697982576029,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0619373776908023,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,University within 1 km,university_distance,D_location,binary,binary (<=1 km),-0.06739,0.13293,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,-7.3392481954451805,12.426702452239805,100*(exp(b - se^2/2) - 1),reported,-0.023279067175615138,0.045919074041467875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5069585496125781,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,University within 1 km,university_distance,D_location,binary,binary (<=1 km),-0.04698,0.12162,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,-5.292378843806422,11.603843004033422,100*(exp(b - se^2/2) - 1),reported,-0.017739872529485463,0.04592429325321461,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3862851504686729,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Hospital within 1 km,hospital_distance,D_location,binary,binary (<=1 km),0.08957,0.08688,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,8.958395726925827,9.502099395495787,100*(exp(b - se^2/2) - 1),reported,0.04730066122813825,0.045880109941952116,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.030962246777164,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Hospital within 1 km,hospital_distance,D_location,binary,binary (<=1 km),0.04538,0.0795,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,4.312381038550117,8.319082136924674,100*(exp(b - se^2/2) - 1),reported,0.026209514363180454,0.045915742438802254,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.570817610062893,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Bus stop within1 km,transit_distance,D_location,binary,binary (<=1 km),-0.06862,0.07352,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,-6.883854454547134,6.864425738166677,100*(exp(b - se^2/2) - 1),reported,-0.04283091228873309,0.045889371487433064,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9333514689880305,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Bus stop within1 km,transit_distance,D_location,binary,binary (<=1 km),-0.03853,0.06703,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,-3.995633429951573,6.44964562459989,100*(exp(b - se^2/2) - 1),reported,-0.02639303313534961,0.04591552066084828,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5748172460092495,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Police Station within 1 km,public_services,F_neighbourhood,binary,binary (<=1 km),0.02213,0.09772,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,1.7506880831796856,9.990664963872964,100*(exp(b - se^2/2) - 1),reported,0.010401244161875706,0.045929036579236054,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2264633647155137,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Police Station within 1 km,public_services,F_neighbourhood,binary,binary (<=1 km),0.14729,0.0887,,,*,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,15.41407814854372,10.2775797180626,100*(exp(b - se^2/2) - 1),reported,0.07605029839353732,0.04579850273275009,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6605411499436302,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Railway Station within 1 km,transit_distance,D_location,binary,binary (<=1 km),-0.2292,0.27549,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,-23.443975749944222,21.90612410655883,100*(exp(b - se^2/2) - 1),reported,-0.03818587413239564,0.04589802122484151,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.831972122400087,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,True
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Railway Station within 1 km,transit_distance,D_location,binary,binary (<=1 km),-0.28402,0.25189,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,-27.075409532209537,18.96105978851637,100*(exp(b - se^2/2) - 1),reported,-0.05172102993706297,0.0458700451758566,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.127555679066259,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,True
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Airport within 1 km,airport_distance,D_location,binary,binary (<=1 km),-0.08662,0.3611,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,-14.085417065675864,33.11379077329409,100*(exp(b - se^2/2) - 1),reported,-0.011017299635081504,0.045928733528376016,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2398781500969261,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Airport within 1 km,airport_distance,D_location,binary,binary (<=1 km),-0.17339,0.33029,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,-20.382458120799672,27.771101438875046,100*(exp(b - se^2/2) - 1),reported,-0.024105338636273215,0.045918174624688154,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5249629113809077,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Post office within 1 km,public_services,F_neighbourhood,binary,binary (<=1 km),0.04187,0.11913,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,3.53857075036601,12.422386910085812,100*(exp(b - se^2/2) - 1),reported,0.016141209176986495,0.045925537359789846,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.35146478636783346,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Post office within 1 km,public_services,F_neighbourhood,binary,binary (<=1 km),0.02894,0.10902,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,2.326379699191339,11.22211358195275,100*(exp(b - se^2/2) - 1),reported,0.012191886153944103,0.04592810741198985,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.26545587965510914,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Bank within 1 km,neighbourhood_amenities,F_neighbourhood,binary,binary (<=1 km),0.04841,0.06972,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,4.705300981234872,7.317817499118337,100*(exp(b - se^2/2) - 1),reported,0.03187629066762934,0.04590817982538975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6943488238668961,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Bank within 1 km,neighbourhood_amenities,F_neighbourhood,binary,binary (<=1 km),0.02741,0.06369,,,,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,2.5706652320746315,6.545988841110343,100*(exp(b - se^2/2) - 1),reported,0.019763496558696237,0.04592255001179728,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.43036583451091226,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Trees,green_space,E_environment,binary,binary,0.09482,0.07637,,,,,,medium,Respondent agrees there are more than 6 trees in the neighbourhood,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,9.625936951968693,8.39658315559723,100*(exp(b - se^2/2) - 1),reported,0.056935472770513376,0.045857013873487715,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2415870106062592,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Trees,green_space,E_environment,binary,binary,0.06448,0.06997,,,,,,medium,Respondent agrees there are more than 6 trees in the neighbourhood,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,6.399649798866558,7.463029908887014,100*(exp(b - se^2/2) - 1),reported,0.04228976627881883,0.0458904303121736,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9215378019151064,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Availability of Park within 1 km,green_space,E_environment,binary,binary (<=1 km),0.34378,0.06762,,,***,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,40.704782427528244,9.53623453091232,100*(exp(b - se^2/2) - 1),reported,0.22739812361772652,0.04472820152141098,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.083998816918071,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,True
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Availability of Park within 1 km,green_space,E_environment,binary,binary (<=1 km),0.2976,0.06208,,,***,,,medium,Dummy = 1 if amenity within 1 km of residence (vs. access but > 1 km),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,34.403063642468545,8.359835775969842,100*(exp(b - se^2/2) - 1),reported,0.2150361499590412,0.044857003324789244,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.79381443298969,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,True
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Open Air Waste Dump within 1 km,hazard_site,E_environment,binary,binary (<=1 km),0.02968,0.0753,,,,,,medium,Open-air dumping site (kachra) within 1 km,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,2.7208526870294403,7.756840054659914,100*(exp(b - se^2/2) - 1),reported,0.018101250913743407,0.04592399574814281,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3941567065073041,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Open Air Waste Dump within 1 km,hazard_site,E_environment,binary,binary (<=1 km),0.03656,0.06888,,,,,,medium,Open-air dumping site (kachra) within 1 km,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,3.4778891816716895,7.144485262330184,100*(exp(b - se^2/2) - 1),reported,0.024372206717829435,0.04591787742680775,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5307781649245065,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,16,Open Air Burning of Waste,hazard_site,E_environment,binary,binary,-0.10674,0.06896,,,,,,medium,Respondent often witnesses open-air burning of waste in neighbourhood,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,-10.337515804310883,6.19784427098262,100*(exp(b - se^2/2) - 1),reported,-0.07091628230378887,0.04581587809321042,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5478538283062646,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,16,Open Air Burning of Waste,hazard_site,E_environment,binary,binary,-0.07552,0.06306,,,,,,medium,Respondent often witnesses open-air burning of waste in neighbourhood,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,-7.458063977315721,5.84730903339726,100*(exp(b - se^2/2) - 1),reported,-0.05492408059793317,0.045862189122161896,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1975895972090072,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,17,Choked Sewer pipes,public_services,F_neighbourhood,binary,binary,-0.0482,0.06954,,,,,,medium,Respondent often witnesses choking of sewer pipes in neighbourhood,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,-4.9358164121911186,6.626766869418911,100*(exp(b - se^2/2) - 1),reported,-0.031820221785184656,0.04590826188675812,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6931262582686223,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,17,Choked Sewer pipes,public_services,F_neighbourhood,binary,binary,-0.05673,0.06356,,,,,,medium,Respondent often witnesses choking of sewer pipes in neighbourhood,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,-5.705746509460297,6.005461160527606,100*(exp(b - se^2/2) - 1),reported,-0.0409614272039856,0.04589297220316103,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8925424795468848,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,17,Poor roads,public_services,F_neighbourhood,binary,binary,0.02837,0.07313,,,,,,medium,Poor road quality in neighbourhood (perceived),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,2.602898983580837,7.523440798353258,100*(exp(b - se^2/2) - 1),reported,0.017815813483862304,0.04592423123281108,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3879392862026528,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,17,Poor roads,public_services,F_neighbourhood,binary,binary,0.0243,0.06693,,,,,,medium,Poor road quality in neighbourhood (perceived),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,2.2305312670925392,6.857632078702955,100*(exp(b - se^2/2) - 1),reported,0.01667385032502369,0.04592513589521958,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.36306588973554454,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,17,Streetlight,public_services,F_neighbourhood,binary,binary,-0.02707,0.08168,,,,,,medium,Access to streetlights in neighbourhood,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,-2.994820422099398,7.9498581112253905,100*(exp(b - se^2/2) - 1),reported,-0.015220644550831604,0.04592620047698285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.33141527913809987,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,17,Streetlight,public_services,F_neighbourhood,binary,binary,-0.00476,0.07479,,,,,,medium,Access to streetlights in neighbourhood,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,-0.7528291433754886,7.443484553819781,100*(exp(b - se^2/2) - 1),reported,-0.002923293312057878,0.04593132495983376,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.06364487230913224,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,17,No garbage Collection,public_services,F_neighbourhood,binary,binary,-0.17426,0.23352,,,,,,medium,No garbage collection in neighbourhood,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,-18.251750983620717,19.617511937886466,100*(exp(b - se^2/2) - 1),reported,-0.03425543596559503,0.04590456448230088,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7462315861596437,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,True
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,17,No garbage Collection,public_services,F_neighbourhood,binary,binary,-0.17237,0.2137,,,,,,medium,No garbage collection in neighbourhood,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,-17.733305558047917,17.986438716961977,100*(exp(b - se^2/2) - 1),reported,-0.03702287512406565,0.04590003140925237,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8065980346279831,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,17,Crime,crime,F_neighbourhood,binary,binary,-0.11143,0.06979,,,,,,medium,Respondent hears about crime incidents in neighbourhood (perceived),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,-10.762186855290457,6.243092421777712,100*(exp(b - se^2/2) - 1),reported,-0.07314001119217357,0.04580850202909265,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.596647084109471,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,17,Crime,crime,F_neighbourhood,binary,binary,-0.09445,0.06385,,,,,,medium,Respondent hears about crime incidents in neighbourhood (perceived),"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,-9.19795796395767,5.8095405553531645,100*(exp(b - se^2/2) - 1),reported,-0.06778783399296014,0.0458258676596136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4792482380579484,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,17,Hear Traffic often,noise,E_environment,binary,binary,0.0363,0.06815,,,,,,medium,Perceived traffic noise: often hears traffic at home,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,3.4561627565970587,7.066929354662022,100*(exp(b - se^2/2) - 1),reported,0.024458040432276246,0.04591778114213847,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.532648569332355,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,17,Hear Traffic often,noise,E_environment,binary,binary,0.02107,0.06227,,,,,,medium,Perceived traffic noise: often hears traffic at home,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,1.9315398026778619,6.359594871607259,100*(exp(b - se^2/2) - 1),reported,0.015539750983061063,0.04592597502207938,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.3383651838766661,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,17,Hear Construction often,noise,E_environment,binary,binary,0.04938,0.06699,,,,,,medium,Perceived construction noise: often hears construction at home,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,4.826474151893989,7.038100099558813,100*(exp(b - se^2/2) - 1),reported,0.033837881130267006,0.04590521783954205,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7371249440214959,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,17,Hear Construction often,noise,E_environment,binary,binary,0.0364,0.06132,,,,,,medium,Perceived construction noise: often hears construction at home,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,3.51226569229679,6.3593168687523205,100*(exp(b - se^2/2) - 1),reported,0.027255157763913167,0.04591445807920756,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5936073059360731,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c1,3 (Appendix 1),1,17,Chowks,noise,E_environment,binary,binary,-0.12687,0.0691,,,*,,,medium,Noisy places/intersections (chowks) near residence,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.4625,se,"Model 1: number of bedrooms as structural size variable; full results (abridged duplicate in Table 2 p.11-12, which prints R-squared 0.4572)",pct_premium,-12.125225763128055,6.086660892132275,100*(exp(b - se^2/2) - 1),reported,-0.0840335799719065,0.04576905790225221,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8360347322720698,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,e8f48e7e91bb043c222f2cfbe026c67e0e422a5f:T3-c2,3 (Appendix 1),2,17,Chowks,noise,E_environment,binary,binary,-0.11883,0.06324,,,*,,,medium,Noisy places/intersections (chowks) near residence,"Log (house value), self-reported approximate market value of the dwelling in PKR",log,OLS,484.0,0.5498,se,Model 2: number of restrooms replaces number of bedrooms; full results (abridged duplicate in Table 2 p.11-12),pct_premium,-11.38150906019918,5.615451077563088,100*(exp(b - se^2/2) - 1),reported,-0.08598715084089546,0.04576140216425338,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.879032258064516,474.0,binary,,2026.0,Pakistan,Asia,Lower middle income,,,unknown,appraisal,journal,False,False,unknown,,2023.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,AREA,living_area,A_structural,level,m2,0.008,,36.788,,***,,,high,House size (m2) per Table IV,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,semi_elasticity,0.8,0.021746221593998045,100*b/1 (X per m2->m2),|b/t|,0.5933272919223892,0.0161282834598888,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),36.788,2491.0,m2,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,APP,dwelling_type,A_structural,binary,binary,0.232,,11.815,,***,,,high,Apartment,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,26.087662433870527,2.4763417442926148,100*(exp(b - se^2/2) - 1),|b/t|,0.2303598540957193,0.019497236910344416,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),11.815,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,DET,dwelling_type,A_structural,binary,binary,0.349,,18.017,,***,,,high,Detached,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,41.738325017507314,2.746070752230411,100*(exp(b - se^2/2) - 1),|b/t|,0.339543993715126,0.018845756436428156,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),18.017,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,SDT,dwelling_type,A_structural,binary,binary,0.165,,14.084,,***,,,high,Semi-detached,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,17.931218498297554,1.3817087800864774,100*(exp(b - se^2/2) - 1),|b/t|,0.27158240009183343,0.01928304459612563,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),14.084,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,PRE1919,age,A_structural,binary,binary,-0.082,,-6.332,,***,,,high,Built before 1919 (age cohort dummy),ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-7.88052890007247,1.1930559161892074,100*(exp(b - se^2/2) - 1),|b/t|,-0.12585971668813212,0.019876771428953274,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.332,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,POST1980,age,A_structural,binary,binary,0.092,,4.663,,***,,,high,Built after 1980,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,9.615145488119081,2.163104517079887,100*(exp(b - se^2/2) - 1),|b/t|,0.09302321182538091,0.019949219778121575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.663,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,EARLYMODER,age,A_structural,binary,binary,0.008,,0.47,,,,,high,Early modern cohort,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,0.7886070608658313,1.715799294475359,100*(exp(b - se^2/2) - 1),|b/t|,0.009416548304542775,0.020035209158601647,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.47,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,ELECHEAT,heating,A_structural,binary,binary,-0.024,,-1.453,,,,,high,Electric heating,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-2.3847460907523876,1.6125847924425207,100*(exp(b - se^2/2) - 1),|b/t|,-0.029100120587059394,0.020027612241610045,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.453,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,GASHEAT,heating,A_structural,binary,binary,-0.004,,-0.485,,,,,high,Gas heating,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-0.4025884302174543,0.8214498881187559,100*(exp(b - se^2/2) - 1),|b/t|,-0.009717048504511726,0.020035151555694283,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.485,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,SOLIDHEAT,heating,A_structural,binary,binary,0.002,,0.144,,,,,high,Solid-fuel heating,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,0.19053622829747763,1.3916694462972228,100*(exp(b - se^2/2) - 1),|b/t|,0.002885186030273357,0.020036014099120536,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.144,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,NOGAR,garage,A_structural,binary,binary,-0.018,,-1.837,,*,,,high,No garage (sign reversed relative to garage presence),ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-1.788611626072989,0.9623788014398156,100*(exp(b - se^2/2) - 1),|b/t|,-0.03678140555733749,0.02002253976991698,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.837,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Air Q Low,air_pollution,E_environment,binary,NO2 band (ug/m3),-0.066,,-3.425,,***,,,high,NO2 band 24.47-29.66 ug/m3 = low air quality,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-6.404292898501329,1.803931008561952,100*(exp(b - se^2/2) - 1),|b/t|,-0.06846262105507887,0.019989086439439085,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.425,2491.0,no2 band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Air Q High,air_pollution,E_environment,binary,NO2 band (ug/m3),0.05,,2.424,,**,,,high,NO2 band 12.98-18.54 ug/m3 = high air quality; stars as printed,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,5.104747500207174,2.1684634826238125,100*(exp(b - se^2/2) - 1),|b/t|,0.04851032089764824,0.020012508621142018,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.424,2491.0,no2 band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Air Q Very High,air_pollution,E_environment,binary,NO2 band (ug/m3),0.349,,6.704,,***,,,high,NO2 band 7.40-12.97 ug/m3 = very high air quality,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,41.57295166608226,7.38006514661923,100*(exp(b - se^2/2) - 1),|b/t|,0.13312640644143678,0.019857757524080668,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.704,2491.0,no2 band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,True
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,PM8_9,air_pollution,E_environment,binary,PM2.5 band (ug/m3),0.061,,2.769,,***,,,high,PM2.5 8.01-9.00 ug/m3,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,6.26410309957941,2.341525235298624,100*(exp(b - se^2/2) - 1),|b/t|,0.05539476621323581,0.020005332688059155,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.769,2491.0,pm2.5 band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,PM10_11,air_pollution,E_environment,binary,PM2.5 band (ug/m3),-0.023,,-1.419,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-2.2865880329143384,1.5840054352914286,100*(exp(b - se^2/2) - 1),|b/t|,-0.028419738336025745,0.020028004465134423,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.419,2491.0,pm2.5 band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,PM11_12,air_pollution,E_environment,binary,PM2.5 band (ug/m3),-0.098,,-4.061,,***,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-9.361505258186165,2.1879239735997107,100*(exp(b - se^2/2) - 1),|b/t|,-0.08109857731549099,0.019970100299308294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.061,2491.0,pm2.5 band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,PM12_13,air_pollution,E_environment,binary,PM2.5 band (ug/m3),-0.101,,-1.982,,**,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-9.723986390343098,4.606318684231699,100*(exp(b - se^2/2) - 1),|b/t|,-0.03968026952789605,0.020020317622550986,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.982,2491.0,pm2.5 band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,PM13_14,air_pollution,E_environment,binary,PM2.5 band (ug/m3),-0.118,,-2.434,,**,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-11.234768411544149,4.308386779314907,100*(exp(b - se^2/2) - 1),|b/t|,-0.048709972127899584,0.020012313939153488,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.434,2491.0,pm2.5 band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,True
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,AQMA Within300,air_pollution,E_environment,binary,binary,0.013,,0.372,,,,,high,Within 300 m of Air Quality Management Area,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,1.2466446586055335,3.540350342924064,100*(exp(b - se^2/2) - 1),|b/t|,0.00745322124348369,0.020035540977106695,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.372,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,AQMA Inside,air_pollution,E_environment,binary,binary,0.037,,2.489,,**,,,high,Inside Air Quality Management Area,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,3.757837228914962,1.542572992005296,100*(exp(b - se^2/2) - 1),|b/t|,0.04980794889550509,0.020011228965650902,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.489,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road Noise V Low,noise,E_environment,binary,dB band,-0.012,,-1.043,,,,,high,Road noise LAeq band,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-1.1993681148741664,1.1368035047308884,100*(exp(b - se^2/2) - 1),|b/t|,-0.020893088054022586,0.02003172392523738,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.043,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road Noise Low,noise,E_environment,binary,dB band,0.026,,1.456,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,2.6177322973832906,1.832751693702575,100*(exp(b - se^2/2) - 1),|b/t|,0.029160152387066273,0.020027577188919145,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.456,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road Noise Moderate,noise,E_environment,binary,dB band,-0.002,,-0.066,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-0.24561156228387615,3.0242484808101002,100*(exp(b - se^2/2) - 1),|b/t|,-0.0013223812782859612,0.020036079974029713,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.066,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road Noise High,noise,E_environment,binary,dB band,0.002,,0.05,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,0.12007202880863765,4.008008005336001,100*(exp(b - se^2/2) - 1),|b/t|,0.0010018043719142535,0.02003608743828507,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.05,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road Noise V High,noise,E_environment,binary,dB band,0.037,,0.863,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,3.673973926740204,4.448973553999052,100*(exp(b - se^2/2) - 1),|b/t|,0.017288567827116456,0.020033102928292534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.863,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road Noise Extreme,noise,E_environment,binary,dB band,0.008,,0.151,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,0.6618357957040022,5.340567340419992,100*(exp(b - se^2/2) - 1),|b/t|,0.0030254368749579987,0.02003600579442383,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.151,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road_25,highway_distance,D_location,binary,m band,-0.023,,-0.711,,,,,high,Within 25 m of main arterial road,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-2.324870827594361,3.161327303345341,100*(exp(b - se^2/2) - 1),|b/t|,-0.014244220036760095,0.020034064749310965,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.711,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road_50,highway_distance,D_location,binary,m band,-0.021,,-0.886,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-2.1056052704021666,2.3209478844197124,100*(exp(b - se^2/2) - 1),|b/t|,-0.01774918592264631,0.02003294122194843,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.886,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road_75,highway_distance,D_location,binary,m band,-0.021,,-1.029,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-2.0984933184008625,1.9984060501417544,100*(exp(b - se^2/2) - 1),|b/t|,-0.020612763886107152,0.020031840511280034,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.029,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road_100,highway_distance,D_location,binary,m band,0.017,,1.025,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,1.700543664566534,1.6869727297101555,100*(exp(b - se^2/2) - 1),|b/t|,0.020532670370887,0.020031873532572686,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.025,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road_125,highway_distance,D_location,binary,m band,0.005,,0.289,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,0.48621189667577003,1.7387759876460225,100*(exp(b - se^2/2) - 1),|b/t|,0.005790335103776199,0.020035761604761938,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.289,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road_150,highway_distance,D_location,binary,m band,0.017,,1.074,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,1.701790893019317,1.6100065623397664,100*(exp(b - se^2/2) - 1),|b/t|,0.02151378822397252,0.02003146017129657,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.074,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road_175,highway_distance,D_location,binary,m band,0.004,,0.204,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,0.3815024995922123,1.9686431581908668,100*(exp(b - se^2/2) - 1),|b/t|,0.004087329746040774,0.020035930127650856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.204,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road_200,highway_distance,D_location,binary,m band,-0.007,,-0.407,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-0.7122417595751052,1.7079044473053182,100*(exp(b - se^2/2) - 1),|b/t|,-0.00815442055357212,0.020035431335558036,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.407,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road_225,highway_distance,D_location,binary,m band,0.055,,2.685,,***,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,5.631897503200212,2.1642358959833214,100*(exp(b - se^2/2) - 1),|b/t|,0.0537192432622232,0.020007166950548678,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.685,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),45,Road_250,highway_distance,D_location,binary,m band,0.037,,2.082,,**,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,3.7529170776745113,1.8441230437565714,100*(exp(b - se^2/2) - 1),|b/t|,0.04167890688040453,0.020018687262442138,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.082,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail_25,transit_distance,D_location,binary,m band,0.073,,1.795,,*,,,high,"Within 25 m of railway line (line, not station)",ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,7.484131377558989,4.3748372810458696,100*(exp(b - se^2/2) - 1),|b/t|,0.03594155791056064,0.02002315203930955,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.795,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail Noise Low,noise,E_environment,binary,dB band,-0.441,,-4.16,,***,,,high,Rail noise LAeq band,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-36.021239140501805,6.82058133650658,100*(exp(b - se^2/2) - 1),|b/t|,-0.08306213822847534,0.019966860151075804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.16,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,True
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail Noise Mod,noise,E_environment,binary,dB band,0.004,,0.032,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-0.38052416489593455,12.550100133466774,100*(exp(b - se^2/2) - 1),|b/t|,0.0006411549879777422,0.020036093374304443,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.032,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail Noise High,noise,E_environment,binary,dB band,-0.365,,-3.445,,***,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-30.968880129349298,7.35505885545609,100*(exp(b - se^2/2) - 1),|b/t|,-0.06886051258751964,0.01998853776125389,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.445,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail Noise V high,noise,E_environment,binary,dB band,0.151,,1.425,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,15.648556233638855,12.323683885638937,100*(exp(b - se^2/2) - 1),|b/t|,0.02853980868936829,0.020027935922363713,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.425,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,True
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail_50,transit_distance,D_location,binary,m band,-0.041,,-1.302,,,,,high,Distance band to railway line,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-4.064664548841501,3.0225034045975234,100*(exp(b - se^2/2) - 1),|b/t|,-0.026078126950821692,0.02002928337236689,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.302,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail_75,transit_distance,D_location,binary,m band,-0.013,,-0.452,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-1.3324037912763265,2.8389587954123314,100*(exp(b - se^2/2) - 1),|b/t|,-0.009055944704156422,0.020035275894151376,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.452,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail_100,transit_distance,D_location,binary,m band,-0.103,,-2.459,,**,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-9.86640777015334,3.778734374485408,100*(exp(b - se^2/2) - 1),|b/t|,-0.04920907460819926,0.02001182375282605,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.459,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail_125,transit_distance,D_location,binary,m band,-0.045,,-0.801,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-4.550997233384379,5.370772369848876,100*(exp(b - se^2/2) - 1),|b/t|,-0.016046847650195716,0.020033517665662564,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.801,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail_150,transit_distance,D_location,binary,m band,0.065,,1.4,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,6.600945347265275,4.954666898926609,100*(exp(b - se^2/2) - 1),|b/t|,0.02803950745936232,0.02002821961383023,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail_175,transit_distance,D_location,binary,m band,0.011,,0.243,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,1.002534761583096,4.5768180851407045,100*(exp(b - se^2/2) - 1),|b/t|,0.004868713984743679,0.020035860019521314,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.243,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail_200,transit_distance,D_location,binary,m band,-0.103,,-2.33,,**,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-9.875405130293757,3.9879432733303086,100*(exp(b - se^2/2) - 1),|b/t|,-0.04663331835120124,0.020014299721545597,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.33,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail_225,transit_distance,D_location,binary,m band,-0.036,,-0.925,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-3.6089991709465585,3.7542757367991815,100*(exp(b - se^2/2) - 1),|b/t|,-0.018530208015191053,0.020032657313720056,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.925,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Rail_250,transit_distance,D_location,binary,m band,-0.027,,-0.635,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-2.751824229353439,4.138701341914503,100*(exp(b - se^2/2) - 1),|b/t|,-0.012721892285623393,0.0200344760403518,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.635,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Airport Noise Low,noise,E_environment,binary,dB band,-0.01,,-0.557,,,,,high,Airport noise LAeq band,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-1.0109710690844098,1.7774682832121507,100*(exp(b - se^2/2) - 1),|b/t|,-0.01115941138393931,0.02003484988139912,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.557,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Airport Noise Mod,noise,E_environment,binary,dB band,-0.032,,-0.959,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-3.203244978626807,3.231721650316405,100*(exp(b - se^2/2) - 1),|b/t|,-0.019211071444158057,0.020032399837495368,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.959,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Airport Noise High,noise,E_environment,binary,dB band,-0.079,,-1.454,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-7.732298070692201,5.0205745551005405,100*(exp(b - se^2/2) - 1),|b/t|,-0.029120131222080636,0.02002760056539246,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.454,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Airport400_1000,airport_distance,D_location,binary,m band,-0.056,,-0.931,,,,,high,400-1000 m from city airport,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-5.616983017028076,5.687453448964789,100*(exp(b - se^2/2) - 1),|b/t|,-0.018650362285270068,0.020032612551310492,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.931,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Airport1001_1500,airport_distance,D_location,binary,m band,-0.026,,-0.527,,,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-2.6849968288986115,4.806966286494778,100*(exp(b - se^2/2) - 1),|b/t|,-0.010558434799311978,0.020034980643855744,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.527,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Airport1501_2000,airport_distance,D_location,binary,m band,-0.086,,-2.196,,**,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-8.310914293131777,3.593492890935017,100*(exp(b - se^2/2) - 1),|b/t|,-0.04395674195205095,0.020016731307855622,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.196,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Airport2001_2500,airport_distance,D_location,binary,m band,-0.076,,-2.637,,***,,,high,,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-7.356863358369859,2.6711426506830884,100*(exp(b - se^2/2) - 1),|b/t|,-0.05276159690316847,0.0200081899519031,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.637,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Industry Noise Base,noise,E_environment,binary,dB band,-0.149,,-2.389,,**,,,high,Industrial noise base band,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-14.010497235584785,5.373536966092289,100*(exp(b - se^2/2) - 1),|b/t|,-0.0478114959557626,0.020013183740377815,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.389,2491.0,db band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Industry Distance400,hazard_site,E_environment,binary,m band,-0.084,,-4.216,,***,,,high,Within 400 m of industrially zoned area,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,-8.075121897358184,1.8318839068308934,100*(exp(b - se^2/2) - 1),|b/t|,-0.08417241259638966,0.019964993500092423,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.216,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TV-c2,V,2 (Log-linear),46,Industry Distance200,hazard_site,E_environment,binary,m band,0.006,,0.166,,,,,high,Within 200 m of industrially zoned area,ln(Price),log,OLS,2501.0,0.815,t,Full sample; t-statistics printed in adjacent column,pct_premium,0.5361104292581187,3.636209768870114,100*(exp(b - se^2/2) - 1),|b/t|,0.0033259737874759107,0.020035986671541633,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.166,2491.0,m band,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c1,VIII,1 (Base No Lag),49,AREA,living_area,A_structural,level,m2,0.01009,,34.729,,***,,,high,,ln(Price),log,OLS,2501.0,0.546,t,Base model without spatial lag,semi_elasticity,1.009,0.029053528751187767,100*b/1 (X per m2->m2),|b/t|,0.5711648560697951,0.0164463375297243,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.729,2491.0,m2,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c2,VIII,2 (Base + Lag),49,AREA,living_area,A_structural,level,m2,0.003986,,23.38,,***,,,high,,ln(Price),log,spatial_lag,2501.0,0.8744,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",semi_elasticity,0.3986,0.017048759623609924,100*b/1 (X per m2->m2),|b/t|,0.4242066481671518,0.018143996927594174,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.38,2491.0,m2,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c3,VIII,3 (NO2),49,AREA,living_area,A_structural,level,m2,0.003905,,23.431,,***,,,high,,ln(Price),log,spatial_lag,2501.0,0.8804,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",semi_elasticity,0.3905,0.016665955358286032,100*b/1 (X per m2->m2),|b/t|,0.4249650283672604,0.018136871169274055,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.431,2491.0,m2,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c4,VIII,4 (PM2.5),49,AREA,living_area,A_structural,level,m2,0.003931,,23.758,,***,,,high,,ln(Price),log,spatial_lag,2501.0,0.8819,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",semi_elasticity,0.39309999999999995,0.016546005556023233,100*b/1 (X per m2->m2),|b/t|,0.42980633845819616,0.018091015172076612,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.758,2491.0,m2,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c5,VIII,5 Rail,49,AREA,living_area,A_structural,level,m2,0.004007,,23.735,,***,,,high,,ln(Price),log,spatial_lag,2501.0,0.8771,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",semi_elasticity,0.4007,0.016882241415630928,100*b/1 (X per m2->m2),|b/t|,0.4294670204866153,0.018094249862507492,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.735,2491.0,m2,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,AREA,living_area,A_structural,level,m2,0.003974,,23.299,,***,,,high,,ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",semi_elasticity,0.39740000000000003,0.017056526031160136,100*b/1 (X per m2->m2),|b/t|,0.42300032536892973,0.018155299599507693,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.299,2491.0,m2,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,AREA,living_area,A_structural,level,m2,0.00398,,23.342,,***,,,high,,ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",semi_elasticity,0.398,0.017050809699254564,100*b/1 (X per m2->m2),|b/t|,0.42364099959431706,0.01814930167056452,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),23.342,2491.0,m2,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c1,VIII,1 (Base No Lag),49,APP,dwelling_type,A_structural,binary,binary,0.366772,,15.078,,***,,,high,Apartment,ln(Price),log,OLS,2501.0,0.546,t,Base model without spatial lag,pct_premium,44.26419898856029,3.5102616568384084,100*(exp(b - se^2/2) - 1),|b/t|,0.28919538960728686,0.019179956864788888,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),15.078,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c2,VIII,2 (Base + Lag),49,APP,dwelling_type,A_structural,binary,binary,0.051301,,3.835,,***,,,high,Apartment,ln(Price),log,spatial_lag,2501.0,0.8744,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,5.254551176391997,1.4081217404006672,100*(exp(b - se^2/2) - 1),|b/t|,0.07661260078216471,0.019977210112689627,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.835,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c3,VIII,3 (NO2),49,APP,dwelling_type,A_structural,binary,binary,-0.00555,,-0.392,,,,,high,Apartment,ln(Price),log,spatial_lag,2501.0,0.8804,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.5634294283669461,1.4079803109755946,100*(exp(b - se^2/2) - 1),|b/t|,-0.007853907976140361,0.02003547953097031,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.392,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c4,VIII,4 (PM2.5),49,APP,dwelling_type,A_structural,binary,binary,-0.00617,,-0.447,,,,,high,Apartment,ln(Price),log,spatial_lag,2501.0,0.8819,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.6245677389554727,1.37182288621665,100*(exp(b - se^2/2) - 1),|b/t|,-0.008955776404358825,0.02003529396948283,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.447,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c5,VIII,5 Rail,49,APP,dwelling_type,A_structural,binary,binary,0.037728,,2.796,,***,,,high,Apartment,ln(Price),log,spatial_lag,2501.0,0.8771,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,3.8354202296407403,1.4012372649165181,100*(exp(b - se^2/2) - 1),|b/t|,0.0559332284751822,0.020004731214299788,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.796,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,APP,dwelling_type,A_structural,binary,binary,0.04626,,3.387,,***,,,high,Apartment,ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,4.7249002228315184,1.43047704990812,100*(exp(b - se^2/2) - 1),|b/t|,0.06770653728517491,0.01999012024953496,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.387,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,APP,dwelling_type,A_structural,binary,binary,0.05144,,3.784,,***,,,high,Apartment,ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,5.268874481782193,1.4311657697310314,100*(exp(b - se^2/2) - 1),|b/t|,0.07559962504609086,0.019978759261651918,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.784,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c1,VIII,1 (Base No Lag),49,TER,dwelling_type,A_structural,binary,binary,-0.10434,,-6.728,,***,,,high,Terraced,ln(Price),log,OLS,2501.0,0.546,t,Base model without spatial lag,pct_premium,-9.91893997294988,1.3971742190741343,100*(exp(b - se^2/2) - 1),|b/t|,-0.13359450165567904,0.01985649548984528,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.728,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c2,VIII,2 (Base + Lag),49,TER,dwelling_type,A_structural,binary,binary,-0.025474,,-3.101,,***,,,high,Terraced,ln(Price),log,spatial_lag,2501.0,0.8744,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-2.518516731797482,0.8008149286818483,100*(exp(b - se^2/2) - 1),|b/t|,-0.06201235805545915,0.019997535651550838,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.101,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c4,VIII,4 (PM2.5),49,TER,dwelling_type,A_structural,binary,binary,-0.0378,,-4.617,,***,,,high,Terraced,ln(Price),log,spatial_lag,2501.0,0.8819,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-3.7126768103282304,0.7883436864496424,100*(exp(b - se^2/2) - 1),|b/t|,-0.09211337243496759,0.019950914540820357,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.617,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c5,VIII,5 Rail,49,TER,dwelling_type,A_structural,binary,binary,-0.03192,,-3.809,,***,,,high,Terraced,ln(Price),log,spatial_lag,2501.0,0.8771,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-3.1449944051214374,0.8116881957811959,100*(exp(b - se^2/2) - 1),|b/t|,-0.07609621122275388,0.019978002421305825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.809,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,TER,dwelling_type,A_structural,binary,binary,-0.02886,,-3.441,,***,,,high,Terraced,ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-2.8481698255471755,0.814850460631963,100*(exp(b - se^2/2) - 1),|b/t|,-0.06878093690376084,0.0199886477488407,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.441,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,TER,dwelling_type,A_structural,binary,binary,-0.0255,,-3.11,,***,,,high,Terraced,ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-2.52103888715548,0.7992916612098521,100*(exp(b - se^2/2) - 1),|b/t|,-0.06219164076143551,0.01999731214194068,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.11,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c1,VIII,1 (Base No Lag),49,DET,dwelling_type,A_structural,binary,binary,0.204127,,8.315,,***,,,high,Detached,ln(Price),log,OLS,2501.0,0.546,t,Base model without spatial lag,pct_premium,22.608438810263245,3.0108521455306585,100*(exp(b - se^2/2) - 1),|b/t|,0.16433514854836176,0.01976369796131831,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.315,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c2,VIII,2 (Base + Lag),49,DET,dwelling_type,A_structural,binary,binary,0.03467,,2.65,,***,,,high,Detached,ln(Price),log,spatial_lag,2501.0,0.8744,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,3.5189412591847047,1.3544561747260864,100*(exp(b - se^2/2) - 1),|b/t|,0.053020973943612555,0.02000791469570285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.65,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c3,VIII,3 (NO2),49,DET,dwelling_type,A_structural,binary,binary,0.048884,,3.767,,***,,,high,Detached,ln(Price),log,spatial_lag,2501.0,0.8804,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,5.001011764167362,1.3627028577186677,100*(exp(b - se^2/2) - 1),|b/t|,0.07526191429055386,0.01997927111509261,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.767,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c4,VIII,4 (PM2.5),49,DET,dwelling_type,A_structural,binary,binary,0.058726,,4.497,,***,,,high,Detached,ln(Price),log,spatial_lag,2501.0,0.8819,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,6.039420680115004,1.3848792588869505,100*(exp(b - se^2/2) - 1),|b/t|,0.0897387976898503,0.019955258547887548,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.497,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c5,VIII,5 Rail,49,DET,dwelling_type,A_structural,binary,binary,0.03604,,2.777,,***,,,high,Detached,ln(Price),log,spatial_lag,2501.0,0.8771,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,3.6610012096338407,1.3454292826968115,100*(exp(b - se^2/2) - 1),|b/t|,0.055554315647235605,0.020005155076426216,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.777,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,DET,dwelling_type,A_structural,binary,binary,0.033414,,2.542,,**,,,high,Detached,ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,3.3889193659157657,1.3591407628677483,100*(exp(b - se^2/2) - 1),|b/t|,0.05086582845292559,0.020010160681717386,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.542,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,DET,dwelling_type,A_structural,binary,binary,0.0344,,2.629,,***,,,high,Detached,ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,3.49099247488156,1.3542772614375174,100*(exp(b - se^2/2) - 1),|b/t|,0.05260197495167921,0.020008358673137775,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.629,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c1,VIII,1 (Base No Lag),49,PRE1919,age,A_structural,binary,binary,-0.06371,,-2.222,,**,,,high,Built pre-1919,ln(Price),log,OLS,2501.0,0.546,t,Base model without spatial lag,pct_premium,-6.210854127969445,2.6902624446371326,100*(exp(b - se^2/2) - 1),|b/t|,-0.04447615349018914,0.020016270697654878,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.222,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c2,VIII,2 (Base + Lag),49,PRE1919,age,A_structural,binary,binary,-0.065664,,-4.356,,***,,,high,Built pre-1919,ln(Price),log,spatial_lag,2501.0,0.8744,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-6.366093434405662,1.4116334824544086,100*(exp(b - se^2/2) - 1),|b/t|,-0.08694671855886081,0.019960220054834898,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.356,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c3,VIII,3 (NO2),49,PRE1919,age,A_structural,binary,binary,-0.08027,,-5.421,,***,,,high,Built pre-1919,ln(Price),log,spatial_lag,2501.0,0.8804,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-7.72340270361489,1.3665107031330141,100*(exp(b - se^2/2) - 1),|b/t|,-0.10798060864054194,0.019918946438026556,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.421,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c4,VIII,4 (PM2.5),49,PRE1919,age,A_structural,binary,binary,-0.08606,,-5.841,,***,,,high,Built pre-1919,ln(Price),log,spatial_lag,2501.0,0.8819,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-8.25604090192118,1.351881896787771,100*(exp(b - se^2/2) - 1),|b/t|,-0.11623754509553287,0.019900281646213467,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.841,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c5,VIII,5 Rail,49,PRE1919,age,A_structural,binary,binary,-0.06855,,-4.579,,***,,,high,Built pre-1919,ln(Price),log,spatial_lag,2501.0,0.8771,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-6.63578565208347,1.3978672459712835,100*(exp(b - se^2/2) - 1),|b/t|,-0.09136159182477824,0.01995230221113305,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.579,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,PRE1919,age,A_structural,binary,binary,-0.06753,,-4.472,,***,,,high,Built pre-1919,ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-6.540688399409933,1.411455038835327,100*(exp(b - se^2/2) - 1),|b/t|,-0.08924390057167697,0.01995614950171667,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.472,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,PRE1919,age,A_structural,binary,binary,-0.0655,,-4.341,,***,,,high,Built pre-1919,ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-6.350756424246063,1.4132051961012584,100*(exp(b - se^2/2) - 1),|b/t|,-0.0866495670767505,0.01996073878754907,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.341,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c1,VIII,1 (Base No Lag),49,INTERWAR,age,A_structural,binary,binary,-0.03624,,-1.355,,,,,high,Interwar cohort,ln(Price),log,OLS,2501.0,0.546,t,Base model without spatial lag,pct_premium,-3.5936059136850496,2.5793487222979996,100*(exp(b - se^2/2) - 1),|b/t|,-0.0271389123947264,0.020028717634484425,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.355,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c2,VIII,2 (Base + Lag),49,INTERWAR,age,A_structural,binary,binary,-0.041892,,-2.978,,***,,,high,Interwar cohort,ln(Price),log,spatial_lag,2501.0,0.8744,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-4.1121534409341525,1.3490030668597703,100*(exp(b - se^2/2) - 1),|b/t|,-0.05956156668040533,0.02000052608475666,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.978,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c3,VIII,3 (NO2),49,INTERWAR,age,A_structural,binary,binary,-0.05072,,-3.683,,***,,,high,Interwar cohort,ln(Price),log,spatial_lag,2501.0,0.8804,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-4.9545345778921,1.3090315377821162,100*(exp(b - se^2/2) - 1),|b/t|,-0.07359284788859606,0.01998176700749282,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.683,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c4,VIII,4 (PM2.5),49,INTERWAR,age,A_structural,binary,binary,-0.05496,,-4.013,,***,,,high,Interwar cohort,ln(Price),log,spatial_lag,2501.0,0.8819,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-5.35657556951371,1.296309606929687,100*(exp(b - se^2/2) - 1),|b/t|,-0.08014620634467026,0.019971643743999568,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.013,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c5,VIII,5 Rail,49,INTERWAR,age,A_structural,binary,binary,-0.03979,,-2.854,,***,,,high,Interwar cohort,ln(Price),log,spatial_lag,2501.0,0.8771,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-3.9102165574895653,1.3397982090880138,100*(exp(b - se^2/2) - 1),|b/t|,-0.05708975957502108,0.020003419612831495,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.854,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,INTERWAR,age,A_structural,binary,binary,-0.04325,,-3.071,,***,,,high,Interwar cohort,ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-4.242302596464964,1.3487239172277172,100*(exp(b - se^2/2) - 1),|b/t|,-0.06141470577695433,0.019998276058923584,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.071,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,INTERWAR,age,A_structural,binary,binary,-0.0419,,-2.981,,***,,,high,Interwar cohort,ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-4.1129050712806485,1.347892038619846,100*(exp(b - se^2/2) - 1),|b/t|,-0.05962135507763308,0.020000454571497173,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.981,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c1,VIII,1 (Base No Lag),49,POSTWAR,age,A_structural,binary,binary,-0.03179,,-1.099,,,,,high,Post-war cohort,ln(Price),log,OLS,2501.0,0.546,t,Base model without spatial lag,pct_premium,-3.1695200080274932,2.802119251713384,100*(exp(b - se^2/2) - 1),|b/t|,-0.0220143347907407,0.020031241847807732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.099,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c2,VIII,2 (Base + Lag),49,POSTWAR,age,A_structural,binary,binary,-0.078489,,-5.157,,***,,,high,Post-war cohort,ln(Price),log,spatial_lag,2501.0,0.8744,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-7.559484370495307,1.4070979325581108,100*(exp(b - se^2/2) - 1),|b/t|,-0.10277896216685788,0.019929990724618554,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.157,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c3,VIII,3 (NO2),49,POSTWAR,age,A_structural,binary,binary,-0.07516,,-5.055,,***,,,high,Post-war cohort,ln(Price),log,spatial_lag,2501.0,0.8804,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-7.2507467141450395,1.379189805200218,100*(exp(b - se^2/2) - 1),|b/t|,-0.10076695081638393,0.019934114899383567,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.055,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c4,VIII,4 (PM2.5),49,POSTWAR,age,A_structural,binary,binary,-0.07323,,-4.956,,***,,,high,Post-war cohort,ln(Price),log,spatial_lag,2501.0,0.8819,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-7.07144050591737,1.3732650001897841,100*(exp(b - se^2/2) - 1),|b/t|,-0.09881293300647584,0.019938041365309894,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.956,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c5,VIII,5 Rail,49,POSTWAR,age,A_structural,binary,binary,-0.07922,,-5.257,,***,,,high,Post-war cohort,ln(Price),log,spatial_lag,2501.0,0.8771,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-7.6268232020831555,1.3921692990011374,100*(exp(b - se^2/2) - 1),|b/t|,-0.10475029856173669,0.01992586999462368,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.257,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,POSTWAR,age,A_structural,binary,binary,-0.07649,,-5.004,,***,,,high,Post-war cohort,ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-7.374604030200449,1.4160160468592926,100*(exp(b - se^2/2) - 1),|b/t|,-0.09976047975326321,0.019936147033026222,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.004,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,POSTWAR,age,A_structural,binary,binary,-0.0785,,-5.154,,***,,,high,Post-war cohort,ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-7.560516682906604,1.408098791319886,100*(exp(b - se^2/2) - 1),|b/t|,-0.10271980324175013,0.01993011316293173,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.154,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c1,VIII,1 (Base No Lag),49,EARLYMODER,age,A_structural,binary,binary,-0.00802,,-0.249,,,,,high,Early modern cohort,ln(Price),log,OLS,2501.0,0.546,t,Base model without spatial lag,pct_premium,-0.8502353337069057,3.19515535609048,100*(exp(b - se^2/2) - 1),|b/t|,-0.004988926188827759,0.020035848147902647,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.249,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c2,VIII,2 (Base + Lag),49,EARLYMODER,age,A_structural,binary,binary,-0.068598,,-4.054,,***,,,high,Early modern cohort,ln(Price),log,spatial_lag,2501.0,0.8744,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-6.643170752464911,1.579923200792304,100*(exp(b - se^2/2) - 1),|b/t|,-0.08095970365371424,0.01997032650560292,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.054,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c3,VIII,3 (NO2),49,EARLYMODER,age,A_structural,binary,binary,-0.06558,,-3.967,,***,,,high,Early modern cohort,ln(Price),log,spatial_lag,2501.0,0.8804,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-6.36038391962932,1.5482039805849044,100*(exp(b - se^2/2) - 1),|b/t|,-0.07923331145445693,0.01997310598801536,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.967,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c4,VIII,4 (PM2.5),49,EARLYMODER,age,A_structural,binary,binary,-0.06552,,-3.99,,***,,,high,Early modern cohort,ln(Price),log,spatial_lag,2501.0,0.8819,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-6.354595141682062,1.5379634645757656,100*(exp(b - se^2/2) - 1),|b/t|,-0.07968978396309202,0.019972376933105766,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.99,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c5,VIII,5 Rail,49,EARLYMODER,age,A_structural,binary,binary,-0.0695,,-4.149,,***,,,high,Early modern cohort,ln(Price),log,spatial_lag,2501.0,0.8771,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-6.727073622668589,1.5626362803139708,100*(exp(b - se^2/2) - 1),|b/t|,-0.0828440121380886,0.019967223942658135,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.149,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,EARLYMODER,age,A_structural,binary,binary,-0.06687,,-3.934,,***,,,high,Early modern cohort,ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-6.4818326567649525,1.5898483321619556,100*(exp(b - se^2/2) - 1),|b/t|,-0.07857828564089689,0.01997414479941456,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.934,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,EARLYMODER,age,A_structural,binary,binary,-0.0685,,-4.051,,***,,,high,Early modern cohort,ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-6.634002919321691,1.5789891882767544,100*(exp(b - se^2/2) - 1),|b/t|,-0.0809001849262062,0.019970423334042506,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.051,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c1,VIII,1 (Base No Lag),49,ELECHEAT,heating,A_structural,binary,binary,0.00069,,0.022,,,,,high,,ln(Price),log,OLS,2501.0,0.546,t,Base model without spatial lag,pct_premium,0.019818079224376284,3.138528474055841,100*(exp(b - se^2/2) - 1),|b/t|,0.0004407941020124436,0.020036095546020167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.022,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c2,VIII,2 (Base + Lag),49,ELECHEAT,heating,A_structural,binary,binary,-0.012883,,-0.794,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8744,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-1.2930308347778308,1.6017749170381868,100*(exp(b - se^2/2) - 1),|b/t|,-0.01590664866527546,0.02003356255072476,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.794,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c3,VIII,3 (NO2),49,ELECHEAT,heating,A_structural,binary,binary,-0.01024,,-0.646,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8804,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-1.0312095300700874,1.5689903162653684,100*(exp(b - se^2/2) - 1),|b/t|,-0.01294223492245693,0.020034419384608253,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.646,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c4,VIII,4 (PM2.5),49,ELECHEAT,heating,A_structural,binary,binary,-0.00894,,-0.567,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8819,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.9023345285839923,1.5626865249095054,100*(exp(b - se^2/2) - 1),|b/t|,-0.011359734257027021,0.02003480468611468,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.567,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c5,VIII,5 Rail,49,ELECHEAT,heating,A_structural,binary,binary,-0.01371,,-0.854,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8771,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-1.374354640794384,1.583526759439776,100*(exp(b - se^2/2) - 1),|b/t|,-0.017108322951003514,0.020033165048013484,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.854,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,ELECHEAT,heating,A_structural,binary,binary,-0.01285,,-0.792,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-1.289772340621409,1.6017593285837668,100*(exp(b - se^2/2) - 1),|b/t|,-0.015866591639754582,0.020033575302720433,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.792,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,ELECHEAT,heating,A_structural,binary,binary,-0.0129,,-0.778,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-1.2952844798781338,1.6368455969106597,100*(exp(b - se^2/2) - 1),|b/t|,-0.015586190332801453,0.020033663666839913,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.778,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c1,VIII,1 (Base No Lag),49,GASHEAT,heating,A_structural,binary,binary,-0.01906,,-0.811,,,,,high,,ln(Price),log,OLS,2501.0,0.546,t,Base model without spatial lag,pct_premium,-1.9150423883874002,2.3058146240802526,100*(exp(b - se^2/2) - 1),|b/t|,-0.016247130270474197,0.02003345286125055,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.811,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c2,VIII,2 (Base + Lag),49,GASHEAT,heating,A_structural,binary,binary,-0.002525,,-0.204,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8744,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.2598219416263481,1.2346237340470938,100*(exp(b - se^2/2) - 1),|b/t|,-0.004087329746040774,0.020035930127650856,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.204,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c3,VIII,3 (NO2),49,GASHEAT,heating,A_structural,binary,binary,-0.00191,,-0.157,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8804,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.19820341446837864,1.2142390966359573,100*(exp(b - se^2/2) - 1),|b/t|,-0.0031456517429019537,0.020035998362432826,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.157,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c4,VIII,4 (PM2.5),49,GASHEAT,heating,A_structural,binary,binary,-0.00047,,-0.039,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8819,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.05424695097222543,1.2045619279573543,100*(exp(b - se^2/2) - 1),|b/t|,-0.0007814075636453681,0.02003609137552226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.039,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c5,VIII,5 Rail,49,GASHEAT,heating,A_structural,binary,binary,-0.00419,,-0.342,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8771,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.42559667551447244,1.2200235756473168,100*(exp(b - se^2/2) - 1),|b/t|,-0.0068521844734144785,0.020035627115247014,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.342,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,GASHEAT,heating,A_structural,binary,binary,-0.0023,,-0.185,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.23744591894652167,1.240387069642521,100*(exp(b - se^2/2) - 1),|b/t|,-0.0037066525724977453,0.020035959851339165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.185,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,GASHEAT,heating,A_structural,binary,binary,-0.0026,,-0.215,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.2669551000216819,1.2061622234365958,100*(exp(b - se^2/2) - 1),|b/t|,-0.00430772099230941,0.02003591159213679,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.215,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c1,VIII,1 (Base No Lag),49,OILHEAT,heating,A_structural,binary,binary,-0.01857,,-0.858,,,,,high,,ln(Price),log,OLS,2501.0,0.546,t,Base model without spatial lag,pct_premium,-1.8628521147239896,2.124514831806657,100*(exp(b - se^2/2) - 1),|b/t|,-0.01718843199179585,0.020033137519575583,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.858,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c2,VIII,2 (Base + Lag),49,OILHEAT,heating,A_structural,binary,binary,-0.002954,,-0.259,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8744,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.3014488912803204,1.1371763551319878,100*(exp(b - se^2/2) - 1),|b/t|,-0.0051892793790844485,0.020035827718472773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.259,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c3,VIII,3 (NO2),49,OILHEAT,heating,A_structural,binary,binary,-0.00241,,-0.217,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8804,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.24686194506852166,1.1079257572080865,100*(exp(b - se^2/2) - 1),|b/t|,-0.004347792061494826,0.02003590811748768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.217,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c4,VIII,4 (PM2.5),49,OILHEAT,heating,A_structural,binary,binary,-0.00062,,-0.056,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8819,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.06810562411506682,1.1064566413203152,100*(exp(b - se^2/2) - 1),|b/t|,-0.001122020753307425,0.02003608488048973,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.056,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c5,VIII,5 Rail,49,OILHEAT,heating,A_structural,binary,binary,-0.0038,,-0.337,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8771,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.38561196884461246,1.1233197036441314,100*(exp(b - se^2/2) - 1),|b/t|,-0.006752010938803448,0.020035640767962756,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.337,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,OILHEAT,heating,A_structural,binary,binary,-0.00291,,-0.256,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.2970186717420442,1.1334157066963815,100*(exp(b - se^2/2) - 1),|b/t|,-0.005129173486527357,0.02003583393174749,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.256,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,OILHEAT,heating,A_structural,binary,binary,-0.0029,,-0.258,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,-0.29587864234141836,1.1207760398141566,100*(exp(b - se^2/2) - 1),|b/t|,-0.005169244087782548,0.020035829797606774,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.258,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c1,VIII,1 (Base No Lag),49,GAR,garage,A_structural,binary,binary,0.003206,,0.219,,,,,high,,ln(Price),log,OLS,2501.0,0.546,t,Base model without spatial lag,pct_premium,0.31036522820337975,1.4686278218971405,100*(exp(b - se^2/2) - 1),|b/t|,0.004387863109736231,0.02003590461066772,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.219,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,ols,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c2,VIII,2 (Base + Lag),49,GAR,garage,A_structural,binary,binary,0.010816,,1.409,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8744,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,1.0844921120916062,0.7759844430545575,100*(exp(b - se^2/2) - 1),|b/t|,0.02821961834928235,0.02002811806194631,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.409,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c3,VIII,3 (NO2),49,GAR,garage,A_structural,binary,binary,0.012548,,1.673,,*,,,high,,ln(Price),log,spatial_lag,2501.0,0.8804,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,1.2598574467585166,0.7595005561638323,100*(exp(b - se^2/2) - 1),|b/t|,0.0335015749258589,0.02002485052352594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.673,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c4,VIII,4 (PM2.5),49,GAR,garage,A_structural,binary,binary,0.012156,,1.632,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8819,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,1.2202105284014886,0.7539626300416469,100*(exp(b - se^2/2) - 1),|b/t|,0.03268144396864691,0.020025394588631684,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.632,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c5,VIII,5 Rail,49,GAR,garage,A_structural,binary,binary,0.009612,,1.264,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8771,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,0.9629151121072876,0.7677876581525704,100*(exp(b - se^2/2) - 1),|b/t|,0.02531750936632713,0.020029675131587914,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.264,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,GAR,garage,A_structural,binary,binary,0.011042,,1.439,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,1.107342102929998,0.7758583322200402,100*(exp(b - se^2/2) - 1),|b/t|,0.028819968034038936,0.020027774867295997,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.439,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,GAR,garage,A_structural,binary,binary,0.0105,,1.378,,,,,high,,ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",pct_premium,1.0525982238419607,0.7700167520807532,100*(exp(b - se^2/2) - 1),|b/t|,0.027599224933440383,0.020028465118606953,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.378,2491.0,binary,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c6,VIII,6 Airport,49,Airport Noise,noise,E_environment,level,db,0.04471,,0.326,,,,,medium,"Scale not stated; spatial-lag interaction (-0.0033, t -0.2737) not extracted",ln(Price),log,spatial_lag,2501.0,0.8746,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",semi_elasticity,4.471,13.714723926380367,100*b/1 (per dB),|b/t|,0.006531628451381448,0.02003567009626211,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.326,2491.0,db,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,True
eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad,eb83365b4894fa9c413cfdff9bdf069881dad3ad:TVIII-c7,VIII,7 Road,49,Road Noise,noise,E_environment,level,db,0.02389,,0.234,,,,,medium,"Scale not stated; spatial-lag interaction (-0.002, t 0.233) not extracted",ln(Price),log,spatial_lag,2501.0,0.8745,t,"Spatial lag model, W = 1/d (inverse distance); column 1 is the non-spatial base",semi_elasticity,2.3890000000000002,10.209401709401709,100*b/1 (per dB),|b/t|,0.004688395284474154,0.02003587728407758,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.234,2491.0,db,,2018.0,United Kingdom,Europe,High income,2013.0,2013.0,mixed,transaction,journal,False,True,unknown,,2013.0,spatial,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-BOST-NHS,2,Panel B: National Historic Sites,47,"National Historic Sites, distance band <=1 km",green_space,E_environment,binary,binary,0.039,,,0.252,,,,medium,"Model 1 distance-band dummy (<=1 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,966983.0,,p,"Model 1 (constant coefficients): Boston National Historic Sites; Boston MA, 1987-2021; block group FE; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,3.9168039443294944,3.5400148134705303,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0011649024103461757,0.001016933446745225,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1455050613926967,966973.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-BOST-NHS,2,Panel B: National Historic Sites,47,"National Historic Sites, distance band 1-2 km",green_space,E_environment,binary,binary,-0.007,,,0.724,,,,medium,"Model 1 distance-band dummy (1-2 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,966983.0,,p,"Model 1 (constant coefficients): Boston National Historic Sites; Boston MA, 1987-2021; block group FE; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-0.7170650977595727,1.9685124100821962,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0003590976968413132,0.0010169340711666452,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.35311797197368927,966973.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-BOST-NHS,2,Panel B: National Historic Sites,47,"National Historic Sites, distance band 2-3 km",green_space,E_environment,binary,binary,-0.01,,,0.516,,,,medium,"Model 1 distance-band dummy (2-3 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,966983.0,,p,"Model 1 (constant coefficients): Boston National Historic Sites; Boston MA, 1987-2021; block group FE; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-1.0067496895998729,1.5242707733537961,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0006605225731385868,0.0010169339148949066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6495235958443252,966973.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-BOST-NHP,2,Panel B: National Historical Parks,47,"National Historical Parks, distance band <=1 km",green_space,E_environment,binary,binary,-0.003,,,0.028,,,,medium,"Model 1 distance-band dummy (<=1 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,966983.0,,p,"Model 1 (constant coefficients): Boston National Historical Parks; Boston MA, 1987-2021; same regression as NHS row; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-0.29964337541844577,0.13612306153203488,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.002234489946223038,0.0010169315979826254,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.197286376641052,966973.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-BOST-NHP,2,Panel B: National Historical Parks,47,"National Historical Parks, distance band 1-2 km",green_space,E_environment,binary,binary,-0.009,,,0.553,,,,medium,"Model 1 distance-band dummy (1-2 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,966983.0,,p,"Model 1 (constant coefficients): Boston National Historical Parks; Boston MA, 1987-2021; same regression as NHS row; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-0.907365029576479,1.5034221842018967,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0006033171236290851,0.0010169339516563295,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5932707061716577,966973.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-BOST-NHP,2,Panel B: National Historical Parks,47,"National Historical Parks, distance band 2-3 km",green_space,E_environment,binary,binary,0.007,,,0.622,,,,medium,"Model 1 distance-band dummy (2-3 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,966983.0,,p,"Model 1 (constant coefficients): Boston National Historical Parks; Boston MA, 1987-2021; same regression as NHS row; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,0.6923058904715784,1.4298006469074684,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0005013665825533918,0.0010169340089214768,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.49301781448446486,966973.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-SAGE,2,Panel B: Saguaro East,47,"Saguaro East, distance band <=2 km",green_space,E_environment,binary,binary,0.113,,,0.003,,,,medium,"Model 1 distance-band dummy (<=2 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Saguaro East; Tucson AZ, 1994-2019; four parks (Saguaro East/West, Coronado NF, Tucson Mountain Park) in one regression; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,11.882061015995182,4.263126044346371,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.00557824969868737,0.0018796301557001344,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9677379253417833,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-SAGE,2,Panel B: Saguaro East,47,"Saguaro East, distance band 2-3 km",green_space,E_environment,binary,binary,0.059,,,0.102,,,,medium,"Model 1 distance-band dummy (2-3 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Saguaro East; Tucson AZ, 1994-2019; four parks (Saguaro East/West, Coronado NF, Tucson Mountain Park) in one regression; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,6.008500690660812,3.8273261572775237,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0030736684697708653,0.0018796505214822964,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.6352340153886502,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-SAGE,2,Panel B: Saguaro East,47,"Saguaro East, distance band 3-5 km",green_space,E_environment,binary,binary,0.022,,,0.48,,,,medium,"Model 1 distance-band dummy (3-5 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Saguaro East; Tucson AZ, 1994-2019; four parks (Saguaro East/West, Coronado NF, Tucson Mountain Park) in one regression; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,2.174801138519711,3.1840976433553467,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0013276070818474827,0.0018796577439972617,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7063025628400874,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-SAGW,2,Panel B: Saguaro West,47,"Saguaro West, distance band <=1 km",green_space,E_environment,binary,binary,-0.11,,,0.063,,,,medium,"Model 1 distance-band dummy (<=1 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Saguaro West; Tucson AZ, 1994-2019; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-10.573245243529318,5.300247724649277,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.003494625430798274,0.0018796479228682013,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8591914944718684,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-SAGW,2,Panel B: Saguaro West,47,"Saguaro West, distance band 1-2 km",green_space,E_environment,binary,binary,-0.062,,,0.197,,,,medium,"Model 1 distance-band dummy (1-2 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Saguaro West; Tucson AZ, 1994-2019; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-6.12017859889562,4.516755681306303,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0024250277694299175,0.001879653873565226,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2901459165086897,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-SAGW,2,Panel B: Saguaro West,47,"Saguaro West, distance band 2-3 km",green_space,E_environment,binary,binary,-0.026,,,0.567,,,,medium,"Model 1 distance-band dummy (2-3 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Saguaro West; Tucson AZ, 1994-2019; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-2.6669266140188497,4.425118666764574,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0010760579972777806,0.0018796583122560719,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5724753218505098,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-SAGW,2,Panel B: Saguaro West,47,"Saguaro West, distance band 3-5 km",green_space,E_environment,binary,binary,-0.006,,,0.87,,,,medium,"Model 1 distance-band dummy (3-5 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Saguaro West; Tucson AZ, 1994-2019; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-0.6649831856289534,3.64423985678774,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0003076221975620631,0.0018796593115485434,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.16365848623314128,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-CORO,2,Panel B: Coronado,47,"Coronado, distance band <=1 km",green_space,E_environment,binary,binary,0.141,,,0.006,,,,medium,"Model 1 distance-band dummy (<=1 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Coronado; Tucson AZ, 1994-2019 (Coronado National Forest, not a national park); hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,14.99097145897641,5.908434936848398,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.005164824223353847,0.0018796343299768818,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7477813854449926,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-CORO,2,Panel B: Coronado,47,"Coronado, distance band 1-2 km",green_space,E_environment,binary,binary,0.099,,,0.008,,,,medium,"Model 1 distance-band dummy (1-2 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Coronado; Tucson AZ, 1994-2019 (Coronado National Forest, not a national park); hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,10.329732077437438,4.1214059799876965,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0049849260075862595,0.0018796360460546727,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6520698079021963,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-CORO,2,Panel B: Coronado,47,"Coronado, distance band 2-3 km",green_space,E_environment,binary,binary,0.083,,,0.003,,,,medium,"Model 1 distance-band dummy (2-3 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Coronado; Tucson AZ, 1994-2019 (Coronado National Forest, not a national park); hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,8.611695757573612,3.0387780989494795,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.00557824969868737,0.0018796301557001344,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9677379253417833,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-CORO,2,Panel B: Coronado,47,"Coronado, distance band 3-5 km",green_space,E_environment,binary,binary,0.051,,,0.01,,,,medium,"Model 1 distance-band dummy (3-5 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Coronado; Tucson AZ, 1994-2019 (Coronado National Forest, not a national park); hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,5.211664865121501,2.083541307783888,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.00484162501639356,0.0018796373694960735,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.575829303548901,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-TUCS,2,Panel B: Tucson,47,"Tucson, distance band <=1 km",green_space,E_environment,binary,binary,-0.021,,,0.615,,,,medium,"Model 1 distance-band dummy (<=1 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Tucson; Tucson AZ, 1994-2019 (Tucson Mountain Park, county park); hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-2.163423558131794,4.088603563625489,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0009453727390209976,0.001879658560532137,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5029491838950579,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-TUCS,2,Panel B: Tucson,47,"Tucson, distance band 1-2 km",green_space,E_environment,binary,binary,-0.033,,,0.426,,,,medium,"Model 1 distance-band dummy (1-2 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Tucson; Tucson AZ, 1994-2019 (Tucson Mountain Park, county park); hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-3.329242567465396,4.010874595747744,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0014963108093853264,0.0018796572962567995,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.7960551172626629,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-TUCS,2,Panel B: Tucson,47,"Tucson, distance band 2-3 km",green_space,E_environment,binary,binary,-0.043,,,0.167,,,,medium,"Model 1 distance-band dummy (2-3 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Tucson; Tucson AZ, 1994-2019 (Tucson Mountain Park, county park); hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-4.255223720056655,2.980675595195537,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.002597507301659213,0.0018796530594027542,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3819078412718098,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-TUCS,2,Panel B: Tucson,47,"Tucson, distance band 3-5 km",green_space,E_environment,binary,binary,-0.021,,,0.372,,,,medium,"Model 1 distance-band dummy (3-5 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,283046.0,,p,"Model 1 (constant coefficients): Tucson; Tucson AZ, 1994-2019 (Tucson Mountain Park, county park); hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-2.1051920357105347,2.3034424386030783,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0016780322226868183,0.0018796567541190152,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.892733324320856,283036.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-GRSM-TN,2,Panel B: Tennessee,47,"Tennessee, distance band <=1 km",green_space,E_environment,binary,binary,-5.535,,,0.249,,,,medium,"Model 1 distance-band dummy (<=1 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,358668.0,,p,"Model 1 (constant coefficients): Great Smoky Mountains NP - Tennessee; Tennessee side, 1994-2021; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-99.99999610840828,1.8947442448184617,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.001924890395408848,0.001669778766978078,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.152781693884193,358658.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,True
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-GRSM-TN,2,Panel B: Tennessee,47,"Tennessee, distance band 1-2 km",green_space,E_environment,binary,binary,-4.067,,,0.398,,,,medium,"Model 1 distance-band dummy (1-2 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,358668.0,,p,"Model 1 (constant coefficients): Great Smoky Mountains NP - Tennessee; Tennessee side, 1994-2021; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-99.99998393646804,8.242136045405674,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.001411295777188309,0.0016697801975216952,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8451985352820499,358658.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-GRSM-TN,2,Panel B: Tennessee,47,"Tennessee, distance band 2-3 km",green_space,E_environment,binary,binary,-6.154,,,0.078,,,,medium,"Model 1 distance-band dummy (2-3 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,358668.0,,p,"Model 1 (constant coefficients): Great Smoky Mountains NP - Tennessee; Tennessee side, 1994-2021; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-99.99952166277536,0.741997135235128,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0029428280031141697,0.0016697746300526597,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.7624102978623897,358658.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-GRSM-TN,2,Panel B: Tennessee,47,"Tennessee, distance band 3-5 km",green_space,E_environment,binary,binary,-5.5,,,0.024,,,,medium,"Model 1 distance-band dummy (3-5 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,358668.0,,p,"Model 1 (constant coefficients): Great Smoky Mountains NP - Tennessee; Tennessee side, 1994-2021; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-99.9790085624328,0.9958332233947331,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0037688867011957793,0.0016697700011652032,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.2571292444862254,358658.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,False
ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7,ebd764414d12429dec7ee666a2f902c6faad3bb7:T2B-GRSM-NC,2,Panel B: North Carolina,47,"North Carolina, distance band 5-10 km",green_space,E_environment,binary,binary,-12.846,,,0.02,,,,medium,"Model 1 distance-band dummy (5-10 km to park) vs houses outside the farthest band; values for Boston and Tucson sites appear to be log-point coefficients (delta2), whereas Great Smoky Mountains values are in percent; table note says 'percent difference in house prices ... (the estimate of delta2 in Model 1)' - scale ambiguous, recorded as printed",log real sale price of single-family home (CPI less shelter deflated),log,FE_panel,49043.0,,p,"Model 1 (constant coefficients): Great Smoky Mountains NP - North Carolina; North Carolina side, 2005-2021; hedonic controls (house characteristics X, distances to lake/river/highway, PROT_5000 share of protected open space within 5 km) and block group + year-month fixed effects included but coefficients not reported; p-value printed next to each estimate",pct_premium,-99.99999999993693,0.0014559496119161716,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.010505251633626502,0.004515769868664997,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3263478740408408,49033.0,binary,,2023.0,United States,North America,High income,1987.0,2021.0,single_family,transaction,journal,True,True,unknown,,2004.0,panel,journal,True,True,True
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c1,B1,1,10,age,age,A_structural,level,years,-0.0068,0.0001,,,,,,high,Age of the building in years,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,-0.6799999999999999,0.01,100*b/1 (per year),reported,-0.3175352087712794,0.0046696354231070495,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-68.0,41236.0,years,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c2,B1,2,10,age,age,A_structural,level,years,-0.0074,0.0001,,,,,,high,Age of the building in years,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,-0.74,0.01,100*b/1 (per year),reported,-0.34238717494183607,0.004626853715430218,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-74.0,41236.0,years,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c3,B1,3,10,age,age,A_structural,level,years,-0.0076,0.0001,,,,,,high,Age of the building in years,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,-0.76,0.01,100*b/1 (per year),reported,-0.35051711504104477,0.0046120673031716415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-76.0,41236.0,years,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c4,B1,4,10,age,age,A_structural,level,years,-0.0049,0.0001,,,,,,high,Age of the building in years,ln asking rent (long-term rental offers),log,OLS,41246.0,0.8184,se,January 2017-December 2020; OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,-0.49,0.01,100*b/1 (per year),reported,-0.2345679310153749,0.004787100632966835,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-48.99999999999999,41236.0,years,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c5,B1,5,10,age,age,A_structural,level,years,-0.007,0.0001,,,,,,high,Age of the building in years,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,-0.7000000000000001,0.01,100*b/1 (per year),reported,-0.3469174567047161,0.00495596366721023,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-70.0,35814.0,years,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c6,B1,6,10,age,age,A_structural,level,years,-0.0073,0.0001,,,,,,high,Age of the building in years,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,-0.73,0.01,100*b/1 (per year),reported,-0.3598942286560665,0.004930057926795431,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-73.0,35814.0,years,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c7,B1,7,10,age,age,A_structural,level,years,-0.0076,0.0001,,,,,,high,Age of the building in years,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,-0.76,0.01,100*b/1 (per year),reported,-0.37266545097522125,0.004903492775989754,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-76.0,35814.0,years,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c8,B1,8,10,age,age,A_structural,level,years,-0.005,0.0001,,,,,,high,Age of the building in years,ln asking rent (long-term rental offers),log,OLS,35824.0,0.817,se,January 2017-March 2020 (before lockdown); OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,-0.5,0.01,100*b/1 (per year),reported,-0.25544138300475255,0.005108827660095051,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-50.0,35814.0,years,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c9,B1,9,10,age,age,A_structural,level,years,-0.0056,0.0003,,,,,,high,Age of the building in years,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,-0.5599999999999999,0.03,100*b/1 (per year),reported,-0.24594544067140883,0.0131756486073969,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-18.666666666666668,5412.0,years,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c10,B1,10,10,age,age,A_structural,level,years,-0.0074,0.0002,,,,,,high,Age of the building in years,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,-0.74,0.02,100*b/1 (per year),reported,-0.4493190705875161,0.012143758664527462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-37.0,5412.0,years,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c11,B1,11,10,age,age,A_structural,level,years,-0.0074,0.0002,,,,,,high,Age of the building in years,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,-0.74,0.02,100*b/1 (per year),reported,-0.4493190705875161,0.012143758664527462,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-37.0,5412.0,years,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c12,B1,12,10,age,age,A_structural,level,years,-0.0046,0.0002,,,,,,high,Age of the building in years,ln asking rent (long-term rental offers),log,OLS,5422.0,0.8156,se,April 2020-December 2020 (after lockdown); OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,-0.45999999999999996,0.02,100*b/1 (per year),reported,-0.2983994785177526,0.012973890370337072,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-23.0,5412.0,years,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c1,B1,1,10,area,living_area,A_structural,level,m2 (unit not stated; 'area of dwelling'),0.0153,0.0001,,,,,,high,,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,1.53,0.01,100*b/1 (X per m2->m2),reported,0.6017608934988574,0.00393307773528665,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),153.0,41236.0,m2,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c2,B1,2,10,area,living_area,A_structural,level,m2 (unit not stated; 'area of dwelling'),0.0167,0.0001,,,,,,high,,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,1.67,0.01,100*b/1 (X per m2->m2),reported,0.6351830480426849,0.003803491305644819,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),167.0,41236.0,m2,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c3,B1,3,10,area,living_area,A_structural,level,m2 (unit not stated; 'area of dwelling'),0.0181,0.0001,,,,,,high,,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,1.81,0.01,100*b/1 (X per m2->m2),reported,0.6653827206191764,0.0036761476277302565,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),181.0,41236.0,m2,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c4,B1,4,10,area,living_area,A_structural,level,m2 (unit not stated; 'area of dwelling'),0.0172,0.0001,,,,,,high,,ln asking rent (long-term rental offers),log,OLS,41246.0,0.8184,se,January 2017-December 2020; OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,1.72,0.01,100*b/1 (X per m2->m2),reported,0.6463243017852776,0.0037576994289841713,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),172.0,41236.0,m2,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c5,B1,5,10,area,living_area,A_structural,level,m2 (unit not stated; 'area of dwelling'),0.015,0.0001,,,,,,high,,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,1.5,0.01,100*b/1 (X per m2->m2),reported,0.6211619473468838,0.004141079648979225,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),150.0,35814.0,m2,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c6,B1,6,10,area,living_area,A_structural,level,m2 (unit not stated; 'area of dwelling'),0.0165,0.0001,,,,,,high,,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,1.6500000000000001,0.01,100*b/1 (X per m2->m2),reported,0.6571723561131936,0.003982862764322385,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),165.0,35814.0,m2,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c7,B1,7,10,area,living_area,A_structural,level,m2 (unit not stated; 'area of dwelling'),0.0179,0.0001,,,,,,high,,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,1.79,0.01,100*b/1 (X per m2->m2),reported,0.687166696961311,0.0038389200947559275,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),178.99999999999997,35814.0,m2,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c8,B1,8,10,area,living_area,A_structural,level,m2 (unit not stated; 'area of dwelling'),0.0169,0.0001,,,,,,high,,ln asking rent (long-term rental offers),log,OLS,35824.0,0.817,se,January 2017-March 2020 (before lockdown); OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,1.69,0.01,100*b/1 (X per m2->m2),reported,0.6660825920390622,0.003941317112657172,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),168.99999999999997,35814.0,m2,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c9,B1,9,10,area,living_area,A_structural,level,m2 (unit not stated; 'area of dwelling'),0.0167,0.0003,,,,,,high,,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,1.67,0.03,100*b/1 (X per m2->m2),reported,0.6034073430838687,0.010839652869770093,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),55.66666666666667,5412.0,m2,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c10,B1,10,10,area,living_area,A_structural,level,m2 (unit not stated; 'area of dwelling'),0.018,0.0003,,,,,,high,,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,1.7999999999999998,0.03,100*b/1 (X per m2->m2),reported,0.6320343161814018,0.010533905269690029,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),60.0,5412.0,m2,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c11,B1,11,10,area,living_area,A_structural,level,m2 (unit not stated; 'area of dwelling'),0.02,0.0003,,,,,,high,,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,2.0,0.03,100*b/1 (X per m2->m2),reported,0.6715039965266848,0.010072559947900272,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),66.66666666666667,5412.0,m2,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c12,B1,12,10,area,living_area,A_structural,level,m2 (unit not stated; 'area of dwelling'),0.0188,0.0003,,,,,,high,,ln asking rent (long-term rental offers),log,OLS,5422.0,0.8156,se,April 2020-December 2020 (after lockdown); OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,semi_elasticity,1.8800000000000001,0.03,100*b/1 (X per m2->m2),reported,0.6484609427337763,0.010347781001070897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),62.66666666666667,5412.0,m2,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c1,B1,1,10,lncc,cbd_distance,D_location,log,m,-0.08,0.0024,,,,,,high,Log distance to the city centre in metres,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.08,0.0024,b (log-log),reported,-0.1619820351151483,0.004859461053454448,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-33.333333333333336,41236.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c2,B1,2,10,lncc,cbd_distance,D_location,log,m,-0.096,0.0021,,,,,,high,Log distance to the city centre in metres,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.096,0.0021,b (log-log),reported,-0.21962342673642132,0.004804262459859216,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-45.714285714285715,41236.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c3,B1,3,10,lncc,cbd_distance,D_location,log,m,-0.1305,0.0025,,,,,,high,Log distance to the city centre in metres,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.1305,0.0025,b (log-log),reported,-0.24896454967928502,0.0047694358176108235,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-52.2,41236.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c4,B1,4,10,lncc,cbd_distance,D_location,log,m,-0.1125,0.0021,,,,,,high,Log distance to the city centre in metres,ln asking rent (long-term rental offers),log,OLS,41246.0,0.8184,se,January 2017-December 2020; OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.1125,0.0021,b (log-log),reported,-0.25508498378091227,0.004761586363910362,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-53.57142857142858,41236.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c5,B1,5,10,lncc,cbd_distance,D_location,log,m,-0.0799,0.0026,,,,,,high,Log distance to the city centre in metres,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0799,0.0026,b (log-log),reported,-0.1602858736668837,0.0052158106574955905,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-30.73076923076923,35814.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c6,B1,6,10,lncc,cbd_distance,D_location,log,m,-0.0944,0.0023,,,,,,high,Log distance to the city centre in metres,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0944,0.0023,b (log-log),reported,-0.2119516597902561,0.005164076456754121,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-41.04347826086956,35814.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c7,B1,7,10,lncc,cbd_distance,D_location,log,m,-0.1302,0.0027,,,,,,high,Log distance to the city centre in metres,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.1302,0.0027,b (log-log),reported,-0.24692234354174475,0.0051205094282850295,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-48.22222222222222,35814.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c8,B1,8,10,lncc,cbd_distance,D_location,log,m,-0.1111,0.0023,,,,,,high,Log distance to the city centre in metres,ln asking rent (long-term rental offers),log,OLS,35824.0,0.817,se,January 2017-March 2020 (before lockdown); OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.1111,0.0023,b (log-log),reported,-0.24731716726520364,0.005119977360125727,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-48.30434782608696,35814.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c9,B1,9,10,lncc,cbd_distance,D_location,log,m,-0.0894,0.0065,,,,,,high,Log distance to the city centre in metres,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0894,0.0065,b (log-log),reported,-0.18377433150935965,0.013361668398331519,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.753846153846153,5412.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c10,B1,10,10,lncc,cbd_distance,D_location,log,m,-0.1088,0.006,,,,,,high,Log distance to the city centre in metres,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.1088,0.006,b (log-log),reported,-0.23932648591671735,0.013198151796877795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-18.133333333333333,5412.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c11,B1,11,10,lncc,cbd_distance,D_location,log,m,-0.1359,0.0063,,,,,,high,Log distance to the city centre in metres,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.1359,0.0063,b (log-log),reported,-0.2813772607441109,0.01304397897489256,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-21.57142857142857,5412.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c12,B1,12,10,lncc,cbd_distance,D_location,log,m,-0.1232,0.0055,,,,,,high,Log distance to the city centre in metres,ln asking rent (long-term rental offers),log,OLS,5422.0,0.8156,se,April 2020-December 2020 (after lockdown); OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.1232,0.0055,b (log-log),reported,-0.29128369200228493,0.013003736250102003,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-22.400000000000002,5412.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c1,B1,1,10,lnsubway,transit_distance,D_location,log,m (unit not stated; presumably metres),-0.0179,0.0014,,,,,,high,Log distance to the nearest subway station,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0179,0.0014,b (log-log),reported,-0.0628387563267251,0.004914763064660065,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.785714285714285,41236.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c2,B1,2,10,lnsubway,transit_distance,D_location,log,m (unit not stated; presumably metres),-0.0168,0.0012,,,,,,high,Log distance to the nearest subway station,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0168,0.0012,b (log-log),reported,-0.0687796698252508,0.004912833558946486,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.0,41236.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c3,B1,3,10,lnsubway,transit_distance,D_location,log,m (unit not stated; presumably metres),-0.0179,0.0012,,,,,,high,Log distance to the nearest subway station,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0179,0.0012,b (log-log),reported,-0.07325966967066262,0.004911262771217606,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.916666666666668,41236.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c4,B1,4,10,lnsubway,transit_distance,D_location,log,m (unit not stated; presumably metres),-0.0123,0.0012,,,,,,high,Log distance to the nearest subway station,ln asking rent (long-term rental offers),log,OLS,41246.0,0.8184,se,January 2017-December 2020; OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0123,0.0012,b (log-log),reported,-0.05041189793539793,0.004918233944916871,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.250000000000002,41236.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c5,B1,5,10,lnsubway,transit_distance,D_location,log,m (unit not stated; presumably metres),-0.0191,0.0015,,,,,,high,Log distance to the nearest subway station,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0191,0.0015,b (log-log),reported,-0.06713281206058405,0.005272210371250056,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-12.733333333333333,35814.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c6,B1,6,10,lnsubway,transit_distance,D_location,log,m (unit not stated; presumably metres),-0.0181,0.0012,,,,,,high,Log distance to the nearest subway station,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0181,0.0012,b (log-log),reported,-0.07945035796268024,0.0052674270472495175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-15.083333333333336,35814.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c7,B1,7,10,lnsubway,transit_distance,D_location,log,m (unit not stated; presumably metres),-0.0191,0.0013,,,,,,high,Log distance to the nearest subway station,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0191,0.0013,b (log-log),reported,-0.07740316229841025,0.0052682780621954636,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-14.692307692307692,35814.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c8,B1,8,10,lnsubway,transit_distance,D_location,log,m (unit not stated; presumably metres),-0.0137,0.0012,,,,,,high,Log distance to the nearest subway station,ln asking rent (long-term rental offers),log,OLS,35824.0,0.817,se,January 2017-March 2020 (before lockdown); OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0137,0.0012,b (log-log),reported,-0.060217685980920505,0.005274541837744861,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-11.416666666666668,35814.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c9,B1,9,10,lnsubway,transit_distance,D_location,log,m (unit not stated; presumably metres),-0.0066,0.0043,,,,,,high,Log distance to the nearest subway station,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0066,0.0043,b (log-log),reported,-0.02085941292855464,0.013590223574664386,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5348837209302326,5412.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c10,B1,10,10,lnsubway,transit_distance,D_location,log,m (unit not stated; presumably metres),-0.006,0.0038,,,,,,high,Log distance to the nearest subway station,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.006,0.0038,b (log-log),reported,-0.02145797586481132,0.013590051381047168,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5789473684210527,5412.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c11,B1,11,10,lnsubway,transit_distance,D_location,log,m (unit not stated; presumably metres),-0.0082,0.0036,,,,,,high,Log distance to the nearest subway station,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0082,0.0036,b (log-log),reported,-0.03094741557507248,0.013586670252470845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.277777777777778,5412.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c12,B1,12,10,lnsubway,transit_distance,D_location,log,m (unit not stated; presumably metres),-0.0024,0.0035,,,,,,high,Log distance to the nearest subway station,ln asking rent (long-term rental offers),log,OLS,5422.0,0.8156,se,April 2020-December 2020 (after lockdown); OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0024,0.0035,b (log-log),reported,-0.009320633646447165,0.013592590734402117,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.6857142857142856,5412.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c1,B1,1,10,lnuga,green_space,E_environment,log,m,-0.0043,0.0012,,,,,,high,Log distance to the nearest urban green area in metres,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0043,0.0012,b (log-log),reported,-0.017643361725734486,0.004923728853693345,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5833333333333335,41236.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c2,B1,2,10,lnuga,green_space,E_environment,log,m,-0.0069,0.0011,,,,,,high,Log distance to the nearest urban green area in metres,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0069,0.0011,b (log-log),reported,-0.030875289505175586,0.004922147602274368,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.2727272727272725,41236.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c3,B1,3,10,lnuga,green_space,E_environment,log,m,-0.013,0.0012,,,,,,high,Log distance to the nearest urban green area in metres,ln asking rent (long-term rental offers),log,quantile,41246.0,,se,January 2017-December 2020; quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.013,0.0012,b (log-log),reported,-0.05327294420411994,0.004917502541918762,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.833333333333334,41236.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c4,B1,4,10,lnuga,green_space,E_environment,log,m,-0.0093,0.0011,,,,,,high,Log distance to the nearest urban green area in metres,ln asking rent (long-term rental offers),log,OLS,41246.0,0.8184,se,January 2017-December 2020; OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0093,0.0011,b (log-log),reported,-0.041598331952356175,0.004920232811569011,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.454545454545453,41236.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c5,B1,5,10,lnuga,green_space,E_environment,log,m,-0.0037,0.0013,,,,,,high,Log distance to the nearest urban green area in metres,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0037,0.0013,b (log-log),reported,-0.01503774954072118,0.00528353362241555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.8461538461538463,35814.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c6,B1,6,10,lnuga,green_space,E_environment,log,m,-0.007,0.0011,,,,,,high,Log distance to the nearest urban green area in metres,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.007,0.0011,b (log-log),reported,-0.03360729395070938,0.005281146192254332,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.363636363636363,35814.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c7,B1,7,10,lnuga,green_space,E_environment,log,m,-0.0139,0.0013,,,,,,high,Log distance to the nearest urban green area in metres,ln asking rent (long-term rental offers),log,quantile,35824.0,,se,January 2017-March 2020 (before lockdown); quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0139,0.0013,b (log-log),reported,-0.05640959218116617,0.00527571725435367,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-10.692307692307692,35814.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c8,B1,8,10,lnuga,green_space,E_environment,log,m,-0.0091,0.0011,,,,,,high,Log distance to the nearest urban green area in metres,ln asking rent (long-term rental offers),log,OLS,35824.0,0.817,se,January 2017-March 2020 (before lockdown); OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0091,0.0011,b (log-log),reported,-0.04367246802221729,0.005279089541147144,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.272727272727273,35814.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c9,B1,9,10,lnuga,green_space,E_environment,log,m,-0.01,0.0035,,,,,,high,Log distance to the nearest urban green area in metres,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.25; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.01,0.0035,b (log-log),reported,-0.03880840299107001,0.013582941046874504,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.857142857142857,5412.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c10,B1,10,10,lnuga,green_space,E_environment,log,m,-0.0066,0.0033,,,,,,high,Log distance to the nearest urban green area in metres,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.50 (median); apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0066,0.0033,b (log-log),reported,-0.0271763212599322,0.013588160629966099,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,5412.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c11,B1,11,10,lnuga,green_space,E_environment,log,m,-0.0065,0.0033,,,,,,high,Log distance to the nearest urban green area in metres,ln asking rent (long-term rental offers),log,quantile,5422.0,,se,April 2020-December 2020 (after lockdown); quantile 0.75; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0065,0.0033,b (log-log),reported,-0.02676485605306519,0.013588311534633099,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9696969696969697,5412.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,quantile,journal,True,True,False
ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501,ede799d5a89d38a16239a4734a2cb00510a8c501:TB1-c12,B1,12,10,lnuga,green_space,E_environment,log,m,-0.0115,0.003,,,,,,high,Log distance to the nearest urban green area in metres,ln asking rent (long-term rental offers),log,OLS,5422.0,0.8156,se,April 2020-December 2020 (after lockdown); OLS; apartments offered for long-term rent in the 7 Warsaw districts with Airbnb activity; district ('area') effects and year-quarter time dummies q2-q16 included,elasticity,-0.0115,0.003,b (log-log),reported,-0.05203659863228437,0.013574764860595922,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.833333333333333,5412.0,m,,2021.0,Poland,Europe,High income,2017.0,2020.0,condo_apartment,rent,journal,True,True,unknown,,2018.5,ols,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.1,A1,0.1,21,Story height,storeys,A_structural,level,count,-0.0575,0.0306,,,*,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-5.75,3.06,100*b/1 (per unit count),reported,-0.042244968725283855,0.022481670312933667,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8790849673202616,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,True
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.2,A1,0.2,21,Story height,storeys,A_structural,level,count,-0.0303,0.0283,,,,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-3.0300000000000002,2.83,100*b/1 (per unit count),reported,-0.02408499952647783,0.022495230580835728,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0706713780918728,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.3,A1,0.3,21,Story height,storeys,A_structural,level,count,-0.046,0.0244,,,*,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-4.6,2.44,100*b/1 (per unit count),reported,-0.042383228417925196,0.022481538552116844,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8852459016393441,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.4,A1,0.4,21,Story height,storeys,A_structural,level,count,-0.0413,0.0192,,,**,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-4.130000000000001,1.92,100*b/1 (per unit count),reported,-0.04834562074971869,0.022475445965970915,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.151041666666667,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.5,A1,0.5,21,Story height,storeys,A_structural,level,count,-0.0323,0.0173,,,*,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-3.2300000000000004,1.73,100*b/1 (per unit count),reported,-0.0419749262029845,0.022481926418316773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8670520231213874,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.6,A1,0.6,21,Story height,storeys,A_structural,level,count,-0.0266,0.0198,,,,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-2.6599999999999997,1.9800000000000002,100*b/1 (per unit count),reported,-0.03021583158358071,0.022491483659958577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.3434343434343432,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.7,A1,0.7,21,Story height,storeys,A_structural,level,count,-0.0092,0.0243,,,,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.7; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.9199999999999999,2.4299999999999997,100*b/1 (per unit count),reported,-0.008518874976330472,0.02250094151356853,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3786008230452675,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.8,A1,0.8,21,Story height,storeys,A_structural,level,count,0.0052,0.0225,,,,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.52,2.25,100*b/1 (per unit count),reported,0.005200335978559193,0.022501453753381122,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2311111111111111,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.9,A1,0.9,21,Story height,storeys,A_structural,level,count,-0.0063,0.0222,,,,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.63,2.22,100*b/1 (per unit count),reported,-0.006385503844929527,0.022501299263085,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.28378378378378377,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.1,A1,0.1,21,Construction material,roof_materials,A_structural,binary,binary,-0.0672,0.0286,,,**,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-6.537414046045431,2.674123397657616,100*(exp(b - se^2/2) - 1),reported,-0.0527975207782204,0.022470373426444992,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.3496503496503496,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.2,A1,0.2,21,Construction material,roof_materials,A_structural,binary,binary,-0.0668,0.0231,,,***,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-6.486727229185007,2.1607330184798705,100*(exp(b - se^2/2) - 1),reported,-0.06493269805578154,0.02245427133366098,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.891774891774892,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.3,A1,0.3,21,Construction material,roof_materials,A_structural,binary,binary,-0.0636,0.0185,,,***,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-6.178029000501139,1.736003511674754,100*(exp(b - se^2/2) - 1),reported,-0.07712696903147646,0.02243473155789803,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.4378378378378383,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.4,A1,0.4,21,Construction material,roof_materials,A_structural,binary,binary,-0.0525,0.0154,,,***,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-5.125818741883026,1.461235654425934,100*(exp(b - se^2/2) - 1),reported,-0.07648582810656243,0.022435842911258313,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.4090909090909087,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.5,A1,0.5,21,Construction material,roof_materials,A_structural,binary,binary,-0.0297,0.0141,,,**,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-2.935978040381859,1.3687387623450147,100*(exp(b - se^2/2) - 1),reported,-0.047344170434756604,0.022476525357914747,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1063829787234045,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.6,A1,0.6,21,Construction material,roof_materials,A_structural,binary,binary,-0.0298,0.016,,,*,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-2.948459185762109,1.5530234273046761,100*(exp(b - se^2/2) - 1),reported,-0.04187276760558521,0.02248202287548199,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8625,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.7,A1,0.7,21,Construction material,roof_materials,A_structural,binary,binary,-0.0285,0.0168,,,*,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.7; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-2.823485102842227,1.6327958541655092,100*(exp(b - se^2/2) - 1),reported,-0.03814484396003178,0.022485381702755575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6964285714285716,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.8,A1,0.8,21,Construction material,roof_materials,A_structural,binary,binary,-0.0256,0.0174,,,,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-2.542264108602277,1.6960213287871213,100*(exp(b - se^2/2) - 1),reported,-0.03308790742036723,0.022489437074780842,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4712643678160922,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.9,A1,0.9,21,Construction material,roof_materials,A_structural,binary,binary,-0.0311,0.0159,,,*,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-3.0743896195688625,1.5413120222818362,100*(exp(b - se^2/2) - 1),reported,-0.04397030504358065,0.022479995183052486,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9559748427672954,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.1,A1,0.1,21,Age,age,A_structural,level,years,-0.0025,0.0007,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.25,0.06999999999999999,100*b/1 (per year),reported,-0.08010516701400018,0.02242944676392005,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5714285714285716,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.2,A1,0.2,21,Age,age,A_structural,level,years,-0.0025,0.0005,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.25,0.05,100*b/1 (per year),reported,-0.11180339887498948,0.022360679774997897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.3,A1,0.3,21,Age,age,A_structural,level,years,-0.0026,0.0005,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.26,0.05,100*b/1 (per year),reported,-0.1162162796335999,0.02234928454492306,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.199999999999999,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.4,A1,0.4,21,Age,age,A_structural,level,years,-0.0024,0.0003,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.24,0.03,100*b/1 (per year),reported,-0.17716640556940677,0.022145800696175846,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.0,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.5,A1,0.5,21,Age,age,A_structural,level,years,-0.0025,0.0004,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.25,0.04,100*b/1 (per year),reported,-0.1392655009388382,0.02228248015021411,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.25,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.6,A1,0.6,21,Age,age,A_structural,level,years,-0.0026,0.0004,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.26,0.04,100*b/1 (per year),reported,-0.14472164640665922,0.022264868677947577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.499999999999999,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.7,A1,0.7,21,Age,age,A_structural,level,years,-0.0025,0.0004,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.7; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.25,0.04,100*b/1 (per year),reported,-0.1392655009388382,0.02228248015021411,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.25,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.8,A1,0.8,21,Age,age,A_structural,level,years,-0.0021,0.0004,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.21,0.04,100*b/1 (per year),reported,-0.11731843575418992,0.0223463687150838,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.249999999999999,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.9,A1,0.9,21,Age,age,A_structural,level,years,-0.0016,0.0003,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.16,0.03,100*b/1 (per year),reported,-0.11915439776336491,0.022341449580630914,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.333333333333334,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.1,A1,0.1,21,Bedrooms,bedrooms,A_structural,level,count,0.0235,0.0264,,,,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,2.35,2.64,100*b/1 (per unit count),reported,0.02002595719101095,0.02249724552522081,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8901515151515151,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.2,A1,0.2,21,Bedrooms,bedrooms,A_structural,level,count,0.0198,0.0212,,,,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,1.9800000000000002,2.12,100*b/1 (per unit count),reported,0.02101115344825426,0.022496790560757086,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9339622641509435,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.3,A1,0.3,21,Bedrooms,bedrooms,A_structural,level,count,0.0411,0.0164,,,**,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.109999999999999,1.6400000000000001,100*b/1 (per unit count),reported,0.05630215116775526,0.02246606518616025,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5060975609756095,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.4,A1,0.4,21,Bedrooms,bedrooms,A_structural,level,count,0.0487,0.015,,,***,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.87,1.5,100*b/1 (per unit count),reported,0.07286153047869028,0.02244194983943232,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2466666666666666,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.5,A1,0.5,21,Bedrooms,bedrooms,A_structural,level,count,0.0518,0.0126,,,***,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,5.18,1.26,100*b/1 (per unit count),reported,0.09211393054213171,0.02240609121295096,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.111111111111111,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.6,A1,0.6,21,Bedrooms,bedrooms,A_structural,level,count,0.0463,0.0158,,,***,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.63,1.58,100*b/1 (per unit count),reported,0.06579581391472535,0.02245299913288684,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9303797468354427,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.7,A1,0.7,21,Bedrooms,bedrooms,A_structural,level,count,0.0319,0.0152,,,**,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.7; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,3.19,1.52,100*b/1 (per unit count),reported,0.04717151462455008,0.022476709162795025,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0986842105263155,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.8,A1,0.8,21,Bedrooms,bedrooms,A_structural,level,count,0.0448,0.014,,,***,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.4799999999999995,1.4000000000000001,100*b/1 (per unit count),reported,0.07181968066622665,0.022443650208195828,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.1999999999999997,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.9,A1,0.9,21,Bedrooms,bedrooms,A_structural,level,count,0.0474,0.0133,,,***,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.74,1.3299999999999998,100*b/1 (per unit count),reported,0.07993760331533249,0.022429749453458273,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.56390977443609,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.1,A1,0.1,21,Total bathrooms,bathrooms,A_structural,level,count,0.0059,0.032,,,,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.59,3.2,100*b/1 (per unit count),reported,0.004148725930420199,0.022501564368380744,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.18437499999999998,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.2,A1,0.2,21,Total bathrooms,bathrooms,A_structural,level,count,0.0258,0.0192,,,,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,2.58,1.92,100*b/1 (per unit count),reported,0.030222924683891112,0.022491478834523616,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3437500000000002,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.3,A1,0.3,21,Total bathrooms,bathrooms,A_structural,level,count,0.0372,0.0153,,,**,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,3.7199999999999998,1.53,100*b/1 (per unit count),reported,0.05462846084960648,0.0224681572849188,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4313725490196076,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.4,A1,0.4,21,Total bathrooms,bathrooms,A_structural,level,count,0.0572,0.0134,,,***,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,5.72,1.34,100*b/1 (per unit count),reported,0.09561223197653544,0.02239866972876879,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.268656716417911,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.5,A1,0.5,21,Total bathrooms,bathrooms,A_structural,level,count,0.034,0.0123,,,***,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,3.4000000000000004,1.23,100*b/1 (per unit count),reported,0.06208000870237194,0.022458356089387493,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7642276422764227,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.6,A1,0.6,21,Total bathrooms,bathrooms,A_structural,level,count,0.028,0.0142,,,**,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,2.8000000000000003,1.4200000000000002,100*b/1 (per unit count),reported,0.04432605353074288,0.022479641433448175,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.971830985915493,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.7,A1,0.7,21,Total bathrooms,bathrooms,A_structural,level,count,0.0279,0.0145,,,*,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.7; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,2.79,1.4500000000000002,100*b/1 (per unit count),reported,0.043255961597428755,0.022480696887552575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9241379310344828,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.8,A1,0.8,21,Total bathrooms,bathrooms,A_structural,level,count,0.0152,0.0149,,,,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,1.52,1.49,100*b/1 (per unit count),reported,0.022948768223110223,0.022495832008180415,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0201342281879195,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.9,A1,0.9,21,Total bathrooms,bathrooms,A_structural,level,count,0.0152,0.0178,,,,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,1.52,1.78,100*b/1 (per unit count),reported,0.01921143812110656,0.02249760516813795,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8539325842696629,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.1,A1,0.1,21,AC,air_conditioning,A_structural,binary,binary,0.2074,0.054,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,22.868193837620332,6.644563181394435,100*(exp(b - se^2/2) - 1),reported,0.08610246696537205,0.02241819294180371,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.840740740740741,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.2,A1,0.2,21,AC,air_conditioning,A_structural,binary,binary,0.2328,0.0335,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,26.142101478696244,4.228132244729097,100*(exp(b - se^2/2) - 1),reported,0.1544930236731349,0.022231599196950252,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.949253731343283,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,True
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.3,A1,0.3,21,AC,air_conditioning,A_structural,binary,binary,0.2202,0.0309,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,24.57311106125033,3.8511472499471857,100*(exp(b - se^2/2) - 1),reported,0.15832969772038955,0.02221792760926447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.12621359223301,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.4,A1,0.4,21,AC,air_conditioning,A_structural,binary,binary,0.2217,0.025,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,24.780686205221002,3.120492156577545,100*(exp(b - se^2/2) - 1),reported,0.195687631359129,0.022066715308877875,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.868,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.5,A1,0.5,21,AC,air_conditioning,A_structural,binary,binary,0.2169,0.0244,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,24.18501449601811,3.031016492411316,100*(exp(b - se^2/2) - 1),reported,0.19614053023201608,0.022064679288433347,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.889344262295081,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.6,A1,0.6,21,AC,air_conditioning,A_structural,binary,binary,0.2099,0.0259,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,23.314102728288756,3.1949066686460346,100*(exp(b - se^2/2) - 1),reported,0.1794012009089977,0.02213668939277294,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.104247104247104,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.7,A1,0.7,21,AC,air_conditioning,A_structural,binary,binary,0.1711,0.0233,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.7; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,18.628734855174066,2.7647999113881885,100*(exp(b - se^2/2) - 1),reported,0.16302759357810512,0.022200718470893333,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.343347639484978,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.8,A1,0.8,21,AC,air_conditioning,A_structural,binary,binary,0.1615,0.0271,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,17.484097146226183,3.184988361609197,100*(exp(b - se^2/2) - 1),reported,0.132907541387981,0.022302132331976997,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.959409594095941,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.9,A1,0.9,21,AC,air_conditioning,A_structural,binary,binary,0.0909,0.0371,,,**,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,9.440604889011507,4.063041685024519,100*(exp(b - se^2/2) - 1),reported,0.0550487408204113,0.02246763789259911,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4501347708894876,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.1,A1,0.1,22,Fire place,fireplace,B_interior,binary,binary,0.1527,0.0362,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,16.421236869473233,4.217211070658037,100*(exp(b - se^2/2) - 1),reported,0.0944929308514448,0.022401074635378534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.218232044198895,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.2,A1,0.2,22,Fire place,fireplace,B_interior,binary,binary,0.1059,0.022,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,11.144169843892083,2.4457635397311694,100*(exp(b - se^2/2) - 1),reported,0.10768542914567668,0.022370910681821406,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.8136363636363635,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.3,A1,0.3,22,Fire place,fireplace,B_interior,binary,binary,0.113,0.0191,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,11.94277251106881,2.1384969919317993,100*(exp(b - se^2/2) - 1),reported,0.13196138196281026,0.02230497695123607,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.916230366492147,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.4,A1,0.4,22,Fire place,fireplace,B_interior,binary,binary,0.1052,0.0138,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,11.082699671083308,1.533087229076988,100*(exp(b - se^2/2) - 1),reported,0.16906585089205012,0.022177839755801253,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.6231884057971016,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.5,A1,0.5,22,Fire place,fireplace,B_interior,binary,binary,0.0905,0.0158,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,9.458487303060625,1.7296599820738017,100*(exp(b - se^2/2) - 1),reported,0.12782928970044333,0.022317157759856408,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.727848101265822,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.6,A1,0.6,22,Fire place,fireplace,B_interior,binary,binary,0.0867,0.015,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,9.044677763657782,1.635854189699706,100*(exp(b - se^2/2) - 1),reported,0.12897389742876822,0.022313823084561975,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.78,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.7,A1,0.7,22,Fire place,fireplace,B_interior,binary,binary,0.0799,0.0163,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.7; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,8.303485906158258,1.7655813533466467,100*(exp(b - se^2/2) - 1),reported,0.10963512899487267,0.02236611517667615,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.901840490797547,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.8,A1,0.8,22,Fire place,fireplace,B_interior,binary,binary,0.0667,0.0176,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,6.880918765778832,1.881395538254554,100*(exp(b - se^2/2) - 1),reported,0.08496816044991524,0.022420384166694285,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.7897727272727266,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.9,A1,0.9,22,Fire place,fireplace,B_interior,binary,binary,0.0553,0.0153,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,5.673393174727548,1.6169921653457382,100*(exp(b - se^2/2) - 1),reported,0.0810622303428218,0.022427705682552857,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6143790849673207,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.1,A1,0.1,22,Basement garage,garage,A_structural,binary,binary,0.0573,0.0263,,,**,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,5.860727743237781,2.785100186079013,100*(exp(b - se^2/2) - 1),reported,0.048965935082826664,0.022474766015328825,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1787072243346004,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.2,A1,0.2,22,Basement garage,garage,A_structural,binary,binary,0.0169,0.0203,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,1.6834077714927398,2.064598534143488,100*(exp(b - se^2/2) - 1),reported,0.018729704593707056,0.022497810843328594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8325123152709359,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.3,A1,0.3,22,Basement garage,garage,A_structural,binary,binary,0.0298,0.0168,,,*,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,3.0103085249393535,1.730817418939464,100*(exp(b - se^2/2) - 1),reported,0.03988207696993092,0.022483855472981186,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.773809523809524,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.4,A1,0.4,22,Basement garage,garage,A_structural,binary,binary,0.0159,0.014,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,1.5927511843224273,1.4224379086652394,100*(exp(b - se^2/2) - 1),reported,0.025547227115240777,0.022494413812161693,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1357142857142857,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.5,A1,0.5,22,Basement garage,garage,A_structural,binary,binary,0.0113,0.0144,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,1.125923337094492,1.4563642840757791,100*(exp(b - se^2/2) - 1),reported,0.017654877446975897,0.022498250905880788,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.7847222222222222,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.6,A1,0.6,22,Basement garage,garage,A_structural,binary,binary,0.0142,0.0144,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,1.4196141606379165,1.4605938704355859,100*(exp(b - se^2/2) - 1),reported,0.02218377304924891,0.02249622055698481,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9861111111111112,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.7,A1,0.7,22,Basement garage,garage,A_structural,binary,binary,0.0085,0.0185,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.7; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,0.8363656576123146,1.865792021008273,100*(exp(b - se^2/2) - 1),reported,0.010338093083900622,0.022500555535548406,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.45945945945945954,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.8,A1,0.8,22,Basement garage,garage,A_structural,binary,binary,0.0032,0.0172,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,0.3056742338233054,1.7255128158010131,100*(exp(b - se^2/2) - 1),reported,0.004186336900709637,0.022501560841314296,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.18604651162790697,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.9,A1,0.9,22,Basement garage,garage,A_structural,binary,binary,-0.0058,0.0179,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-0.5942478214090441,1.779648049675891,100*(exp(b - se^2/2) - 1),reported,-0.007290878642561196,0.022501159948594036,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3240223463687151,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.1,A1,0.1,22,Lot size,lot_size,A_structural,level,acres,-0.0009,0.0075,,,,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-2.223948433204488e-05,0.000185329036100374,100*b/4046.86 (X per acre->m2),reported,-0.002700201118469234,0.02250167598724362,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.12,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.2,A1,0.2,22,Lot size,lot_size,A_structural,level,acres,0.0088,0.0065,,,,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.0002174527356911055,0.00016061849795365746,100*b/4046.86 (X per acre->m2),reported,0.030449792354873283,0.02249132389848595,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.353846153846154,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.3,A1,0.3,22,Lot size,lot_size,A_structural,level,acres,0.0112,0.0044,,,**,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.00027675802724322514,0.00010872636784555275,100*b/4046.86 (X per acre->m2),reported,0.057183478747808276,0.02246493807949611,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.5454545454545454,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.4,A1,0.4,22,Lot size,lot_size,A_structural,level,acres,0.0105,0.005,,,**,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.0002594606505405236,0.00012355269073358266,100*b/4046.86 (X per acre->m2),reported,0.047201023372093365,0.022476677796234936,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.1,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.5,A1,0.5,22,Lot size,lot_size,A_structural,level,acres,0.0117,0.0065,,,*,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.00028911329631658343,0.00016061849795365746,100*b/4046.86 (X per acre->m2),reported,0.040469982405454144,0.022483323558585636,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.8,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.6,A1,0.6,22,Lot size,lot_size,A_structural,level,acres,0.0108,0.0073,,,,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.00026687381198453857,0.00018038692847103068,100*b/4046.86 (X per acre->m2),reported,0.033271840612988574,0.022489299673594126,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.4794520547945207,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.7,A1,0.7,22,Lot size,lot_size,A_structural,level,acres,0.0244,0.0102,,,**,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.7; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.0006029371307798833,0.00025204748909650866,100*b/4046.86 (X per acre->m2),reported,0.0537499230041436,0.02246923010828954,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.392156862745098,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.8,A1,0.8,22,Lot size,lot_size,A_structural,level,acres,0.0212,0.01,,,**,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.0005238634087103906,0.0002471053814671653,100*b/4046.86 (X per acre->m2),reported,0.047649541075213894,0.02247619862038391,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.12,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.9,A1,0.9,22,Lot size,lot_size,A_structural,level,acres,0.0381,0.007,,,***,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.0009414715033898999,0.00017297376702701575,100*b/4046.86 (X per acre->m2),reported,0.12156551596490041,0.022334871699588,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.442857142857143,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.1,A1,0.1,22,Distance to highway exit,highway_distance,D_location,level,miles,-0.0046,0.0116,,,,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.2858307484291736,0.7207905829953073,100*b/1.60934 (X per miles->km),reported,-0.008922755722028166,0.022500862255549287,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.39655172413793105,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.2,A1,0.2,22,Distance to highway exit,highway_distance,D_location,level,miles,-0.007,0.0085,,,,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.4349598345661338,0.5281655134017339,100*b/1.60934 (X per miles->km),reported,-0.018527678682394196,0.02249789554290724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8235294117647058,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.3,A1,0.3,22,Distance to highway exit,highway_distance,D_location,level,miles,-0.0156,0.0072,,,**,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.9693390598902408,0.4473872584108804,100*b/1.60934 (X per miles->km),reported,-0.048695969839064907,0.02247506300264534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1666666666666665,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.4,A1,0.4,22,Distance to highway exit,highway_distance,D_location,level,miles,-0.0204,0.0061,,,***,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-1.2675972321641613,0.3790364272647737,100*b/1.60934 (X per miles->km),reported,-0.07503961255423391,0.022438315518667984,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.3442622950819674,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.5,A1,0.5,22,Distance to highway exit,highway_distance,D_location,level,miles,-0.0139,0.0058,,,**,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.8637059572098941,0.36039529149765365,100*b/1.60934 (X per miles->km),reported,-0.05384838608001197,0.022469110738422258,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.396551724137931,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.6,A1,0.6,22,Distance to highway exit,highway_distance,D_location,level,miles,-0.0103,0.0062,,,*,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.640012328004454,0.385250139187147,100*b/1.60934 (X per miles->km),reported,-0.03735586121477098,0.022486052381706804,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6612903225806452,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.7,A1,0.7,22,Distance to highway exit,highway_distance,D_location,level,miles,-0.0154,0.0064,,,**,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.7; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.9569116360454942,0.3976775630318937,100*b/1.60934 (X per miles->km),reported,-0.054065662017658174,0.022468846552793006,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.40625,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.8,A1,0.8,22,Distance to highway exit,highway_distance,D_location,level,miles,-0.0128,0.0064,,,**,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.7953551260637874,0.3976775630318937,100*b/1.60934 (X per miles->km),reported,-0.04495801196469979,0.0224790059823499,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.9,A1,0.9,22,Distance to highway exit,highway_distance,D_location,level,miles,-0.014,0.0067,,,**,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.8699196691322676,0.41631869879901373,100*b/1.60934 (X per miles->km),reported,-0.04696671170923583,0.022476926317991437,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.08955223880597,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.1,A1,0.1,22,Distance to FSU,university_distance,D_location,level,miles,-0.0093,0.0106,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.5778752087807205,0.658653463771574,100*b/1.60934 (X per miles->km),reported,-0.0197382623227127,0.0224973742602962,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8773584905660377,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.2,A1,0.2,22,Distance to FSU,university_distance,D_location,level,miles,-0.0115,0.0078,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.714576871072934,0.4846695299451204,100*b/1.60934 (X per miles->km),reported,-0.033157426944858195,0.022489385232164684,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.4743589743589745,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.3,A1,0.3,22,Distance to FSU,university_distance,D_location,level,miles,-0.0072,0.006,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.4473872584108804,0.37282271534240036,100*b/1.60934 (X per miles->km),reported,-0.026992271194846446,0.022493559329038706,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.2,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.4,A1,0.4,22,Distance to FSU,university_distance,D_location,level,miles,0.0005,0.0054,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.0310685596118667,0.33554044380816034,100*b/1.60934 (X per miles->km),reported,0.0020834915906581624,0.022501709179108157,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.09259259259259259,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.5,A1,0.5,22,Distance to FSU,university_distance,D_location,level,miles,-0.0016,0.0052,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.09941939075797343,0.32311301996341363,100*b/1.60934 (X per miles->km),reported,-0.006923451910869664,0.02250121871032641,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.3076923076923077,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.6,A1,0.6,22,Distance to FSU,university_distance,D_location,level,miles,-0.0044,0.0052,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.27340332458442695,0.32311301996341363,100*b/1.60934 (X per miles->km),reported,-0.019036498852701242,0.022497680462283287,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8461538461538463,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.7,A1,0.7,22,Distance to FSU,university_distance,D_location,level,miles,-0.0024,0.0056,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.7; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.14912908613696013,0.34796786765290694,100*b/1.60934 (X per miles->km),reported,-0.009643162186485746,0.02250071176846674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.42857142857142855,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.8,A1,0.8,22,Distance to FSU,university_distance,D_location,level,miles,0.0015,0.0061,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.09320567883560009,0.3790364272647737,100*b/1.60934 (X per miles->km),reported,0.005533134482884204,0.0225014135637291,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.2459016393442623,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA1-q0.9,A1,0.9,22,Distance to FSU,university_distance,D_location,level,miles,0.0055,0.0067,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (1) with Days BWNs_year; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.34175415573053364,0.41631869879901373,100*b/1.60934 (X per miles->km),reported,0.018468441958305798,0.022497920203754337,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8208955223880596,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,True
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.1,A2,0.1,23,Story height,storeys,A_structural,level,count,-0.0357,0.0372,,,,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-3.5700000000000003,3.7199999999999998,100*b/1 (per unit count),reported,-0.021589395876154757,0.02249651334994277,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9596774193548389,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.2,A2,0.2,23,Story height,storeys,A_structural,level,count,-0.0317,0.0285,,,,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-3.17,2.85,100*b/1 (per unit count),reported,-0.025020435846255445,0.02249471361571862,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1122807017543859,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.3,A2,0.3,23,Story height,storeys,A_structural,level,count,-0.0466,0.0205,,,**,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-4.66,2.0500000000000003,100*b/1 (per unit count),reported,-0.05108355498337805,0.022472379338181327,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.2731707317073173,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.4,A2,0.4,23,Story height,storeys,A_structural,level,count,-0.0374,0.0197,,,*,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-3.74,1.97,100*b/1 (per unit count),reported,-0.042680147438484334,0.022481254132035857,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8984771573604065,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.5,A2,0.5,23,Story height,storeys,A_structural,level,count,-0.0238,0.0217,,,,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-2.3800000000000003,2.17,100*b/1 (per unit count),reported,-0.02467183520816971,0.022494908572154734,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.0967741935483872,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.6,A2,0.6,23,Story height,storeys,A_structural,level,count,-0.0326,0.0194,,,*,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-3.26,1.94,100*b/1 (per unit count),reported,-0.037785230196385466,0.022485689135272338,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6804123711340204,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.8,A2,0.8,23,Story height,storeys,A_structural,level,count,0.0089,0.0211,,,,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.89,2.11,100*b/1 (per unit count),reported,0.009490835383976682,0.022500744562012134,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.42180094786729855,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.9,A2,0.9,23,Story height,storeys,A_structural,level,count,-0.0044,0.0208,,,,,,high,"Story height (number of storeys, 1-3)","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.44,2.08,100*b/1 (per unit count),reported,-0.004759933349409432,0.022501503106299132,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.21153846153846156,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.1,A2,0.1,23,Construction material,roof_materials,A_structural,binary,binary,-0.078,0.0262,,,***,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-7.5352985272781225,2.423406797544073,100*(exp(b - se^2/2) - 1),reported,-0.06684015670301559,0.02245143725152575,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.9770992366412212,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.2,A2,0.2,23,Construction material,roof_materials,A_structural,binary,binary,-0.0762,0.0235,,,***,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-7.362496877132929,2.1775825253549232,100*(exp(b - se^2/2) - 1),reported,-0.0727697052279855,0.022442100693670065,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2425531914893617,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.3,A2,0.3,23,Construction material,roof_materials,A_structural,binary,binary,-0.0519,0.0202,,,**,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-5.07698772100722,1.9178360850422804,100*(exp(b - se^2/2) - 1),reported,-0.057717544304130126,0.0224642465307019,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.5693069306930694,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.4,A2,0.4,23,Construction material,roof_materials,A_structural,binary,binary,-0.0567,0.0159,,,***,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-5.524193959240442,1.5023552092563248,100*(exp(b - se^2/2) - 1),reported,-0.07998502769182117,0.022429663850087416,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5660377358490565,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.5,A2,0.5,23,Construction material,roof_materials,A_structural,binary,binary,-0.0407,0.0152,,,***,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-3.9993784440433666,1.4593780252627888,100*(exp(b - se^2/2) - 1),reported,-0.06014235136182725,0.022461025570019024,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6776315789473686,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.6,A2,0.6,23,Construction material,roof_materials,A_structural,binary,binary,-0.0311,0.0146,,,**,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-3.0724680502955737,1.4152928003342646,100*(exp(b - se^2/2) - 1),reported,-0.047876860977024184,0.022475954027799134,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1301369863013697,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.8,A2,0.8,23,Construction material,roof_materials,A_structural,binary,binary,-0.0197,0.017,,,,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-1.964889394820668,1.666837720937568,100*(exp(b - se^2/2) - 1),reported,-0.026066706315576504,0.02249411204897465,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.1588235294117646,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.9,A2,0.9,23,Construction material,roof_materials,A_structural,binary,binary,-0.0308,0.0151,,,**,,,high,"1 = Alum/Vinyl siding construction material, 0 otherwise","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-3.0441053287260766,1.4642009262479827,100*(exp(b - se^2/2) - 1),reported,-0.04584935808745915,0.02247809438703354,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.0397350993377485,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.1,A2,0.1,23,Age,age,A_structural,level,years,-0.0021,0.0006,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.21,0.06,100*b/1 (per year),reported,-0.07851303965519903,0.02243229704434258,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.5,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.2,A2,0.2,23,Age,age,A_structural,level,years,-0.0025,0.0005,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.25,0.05,100*b/1 (per year),reported,-0.11180339887498948,0.022360679774997897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.3,A2,0.3,23,Age,age,A_structural,level,years,-0.0024,0.0004,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.24,0.04,100*b/1 (per year),reported,-0.13379664241538733,0.02229944040256456,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.999999999999999,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.4,A2,0.4,23,Age,age,A_structural,level,years,-0.0025,0.0005,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.25,0.05,100*b/1 (per year),reported,-0.11180339887498948,0.022360679774997897,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.0,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.5,A2,0.5,23,Age,age,A_structural,level,years,-0.0026,0.0004,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.26,0.04,100*b/1 (per year),reported,-0.14472164640665922,0.022264868677947577,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.499999999999999,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.6,A2,0.6,23,Age,age,A_structural,level,years,-0.0026,0.0003,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.26,0.03,100*b/1 (per year),reported,-0.19140945801850193,0.022085706694442528,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.666666666666668,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.8,A2,0.8,23,Age,age,A_structural,level,years,-0.0023,0.0004,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.22999999999999998,0.04,100*b/1 (per year),reported,-0.12831553284287514,0.02231574484223916,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.75,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.9,A2,0.9,23,Age,age,A_structural,level,years,-0.0017,0.0003,,,***,,,high,Age of the house in years,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.16999999999999998,0.03,100*b/1 (per year),reported,-0.12648585450796923,0.02232103314846516,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.666666666666667,1975.0,years,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.1,A2,0.1,23,Bedrooms,bedrooms,A_structural,level,count,0.0165,0.0161,,,,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,1.6500000000000001,1.6099999999999999,100*b/1 (per unit count),reported,0.023054678473045803,0.022495777176729535,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0248447204968945,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.2,A2,0.2,23,Bedrooms,bedrooms,A_structural,level,count,0.024,0.0192,,,,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,2.4,1.92,100*b/1 (per unit count),reported,0.028116077855776668,0.022492862284621332,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2500000000000002,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.3,A2,0.3,23,Bedrooms,bedrooms,A_structural,level,count,0.0406,0.0166,,,**,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.06,1.66,100*b/1 (per unit count),reported,0.05495126528084473,0.022467758710887256,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4457831325301203,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.4,A2,0.4,23,Bedrooms,bedrooms,A_structural,level,count,0.0463,0.0165,,,***,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.63,1.6500000000000001,100*b/1 (per unit count),reported,0.063015805254518,0.02245703642979583,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.806060606060606,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.5,A2,0.5,23,Bedrooms,bedrooms,A_structural,level,count,0.0447,0.0154,,,***,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.47,1.54,100*b/1 (per unit count),reported,0.06517467931677591,0.022453916364168887,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.902597402597402,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.6,A2,0.6,23,Bedrooms,bedrooms,A_structural,level,count,0.0481,0.013,,,***,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.81,1.3,100*b/1 (per unit count),reported,0.08296944387137543,0.02242417401929066,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.6999999999999997,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.8,A2,0.8,23,Bedrooms,bedrooms,A_structural,level,count,0.0433,0.0128,,,***,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.33,1.28,100*b/1 (per unit count),reported,0.07589965938154761,0.022436850810249643,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3828124999999996,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.9,A2,0.9,23,Bedrooms,bedrooms,A_structural,level,count,0.047,0.0141,,,***,,,high,,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.7,1.41,100*b/1 (per unit count),reported,0.07479575920067659,0.022438727760202972,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.3333333333333335,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.1,A2,0.1,23,Total bathrooms,bathrooms,A_structural,level,count,-0.0178,0.0211,,,,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-1.78,2.11,100*b/1 (per unit count),reported,-0.018979106599404525,0.022497705013900873,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.8436018957345971,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.2,A2,0.2,23,Total bathrooms,bathrooms,A_structural,level,count,0.021,0.0223,,,,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,2.1,2.23,100*b/1 (per unit count),reported,0.021185240618682374,0.022496707895076993,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9417040358744395,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.3,A2,0.3,23,Total bathrooms,bathrooms,A_structural,level,count,0.0406,0.0148,,,***,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.06,1.48,100*b/1 (per unit count),reported,0.06161052930550961,0.02245901068279661,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.743243243243243,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.4,A2,0.4,23,Total bathrooms,bathrooms,A_structural,level,count,0.0454,0.0168,,,***,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,4.54,1.68,100*b/1 (per unit count),reported,0.06069620907643688,0.02246027120009118,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.7023809523809526,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.5,A2,0.5,23,Total bathrooms,bathrooms,A_structural,level,count,0.0335,0.0118,,,***,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,3.35,1.18,100*b/1 (per unit count),reported,0.06375215822026115,0.02245598408952482,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.838983050847458,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.6,A2,0.6,23,Total bathrooms,bathrooms,A_structural,level,count,0.0273,0.0141,,,*,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,2.73,1.41,100*b/1 (per unit count),reported,0.0435259448120545,0.022480433034797374,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9361702127659577,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.8,A2,0.8,23,Total bathrooms,bathrooms,A_structural,level,count,0.0148,0.0172,,,,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,1.48,1.72,100*b/1 (per unit count),reported,0.019358349580987096,0.02249754140493095,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8604651162790699,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.9,A2,0.9,23,Total bathrooms,bathrooms,A_structural,level,count,0.0143,0.0153,,,,,,high,Total bathrooms (full + half),"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,1.43,1.53,100*b/1 (per unit count),reported,0.02102640534918535,0.022496783345631873,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.934640522875817,1975.0,count,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.1,A2,0.1,23,AC,air_conditioning,A_structural,binary,binary,0.1847,0.0347,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,20.21335723232214,4.173915624710704,100*(exp(b - se^2/2) - 1),reported,0.11892166291716157,0.02234207744031135,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.322766570605187,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.2,A2,0.2,23,AC,air_conditioning,A_structural,binary,binary,0.2161,0.0372,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,24.03679630596787,4.61736256305276,100*(exp(b - se^2/2) - 1),reported,0.12961322094622857,0.022311947335491446,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.809139784946237,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.3,A2,0.3,23,AC,air_conditioning,A_structural,binary,binary,0.2305,0.0272,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,25.876373926749487,3.4251041510170164,100*(exp(b - se^2/2) - 1),reported,0.18731084589696312,0.022103492444240334,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.474264705882353,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.4,A2,0.4,23,AC,air_conditioning,A_structural,binary,binary,0.2244,0.0271,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,25.111204897522278,3.391758894904287,100*(exp(b - se^2/2) - 1),reported,0.18317207105719407,0.022121047797014078,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.280442804428045,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.5,A2,0.5,23,AC,air_conditioning,A_structural,binary,binary,0.2281,0.0268,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,25.575989076795413,3.3666453198580024,100*(exp(b - se^2/2) - 1),reported,0.18809829305967732,0.02210010633055394,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),8.511194029850746,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.6,A2,0.6,23,AC,air_conditioning,A_structural,binary,binary,0.2081,0.0295,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,23.080062836571557,3.632442076215176,100*(exp(b - se^2/2) - 1),reported,0.15677003134583536,0.022223526788573488,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),7.054237288135594,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.8,A2,0.8,23,AC,air_conditioning,A_structural,binary,binary,0.1468,0.0287,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,15.764544672252834,3.3238110452059906,100*(exp(b - se^2/2) - 1),reported,0.11434124626767166,0.022354180980123817,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.114982578397213,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.9,A2,0.9,23,AC,air_conditioning,A_structural,binary,binary,0.0936,0.0334,,,***,,,high,1 = central heating with A/C,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,9.750807108068704,3.667722169038845,100*(exp(b - se^2/2) - 1),reported,0.06293381754258681,0.02245715284105128,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8023952095808387,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.1,A2,0.1,23,Fire place,fireplace,B_interior,binary,binary,0.1368,0.026,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,14.621132091799737,2.981156895146893,100*(exp(b - se^2/2) - 1),reported,0.11757271807582378,0.022345692031954807,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.261538461538462,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.2,A2,0.2,23,Fire place,fireplace,B_interior,binary,binary,0.1306,0.0234,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,13.919995252318685,2.666457811800267,100*(exp(b - se^2/2) - 1),reported,0.12460791950380472,0.022326380676791963,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.581196581196581,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.3,A2,0.3,23,Fire place,fireplace,B_interior,binary,binary,0.1319,0.0204,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,14.075682076384478,2.327628196846946,100*(exp(b - se^2/2) - 1),reported,0.1439735332471638,0.022267324323291447,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.465686274509803,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.4,A2,0.4,23,Fire place,fireplace,B_interior,binary,binary,0.1094,0.0159,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,11.546749492580233,1.7738175221652854,100*(exp(b - se^2/2) - 1),reported,0.15300054211518946,0.022236824676704865,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.880503144654088,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.5,A2,0.5,23,Fire place,fireplace,B_interior,binary,binary,0.0972,0.0149,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,10.195843804851812,1.6421003439242732,100*(exp(b - se^2/2) - 1),reported,0.1452336345768627,0.022263180609004674,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),6.523489932885906,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.6,A2,0.6,23,Fire place,fireplace,B_interior,binary,binary,0.0896,0.0159,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,9.359845646386301,1.7390413554072615,100*(exp(b - se^2/2) - 1),reported,0.12579507317700409,0.022323009637437108,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.635220125786163,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.8,A2,0.8,23,Fire place,fireplace,B_interior,binary,binary,0.077,0.0165,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,7.98950656710955,1.7820694260477907,100*(exp(b - se^2/2) - 1),reported,0.1044340002510476,0.022378714339510202,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.666666666666666,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.9,A2,0.9,23,Fire place,fireplace,B_interior,binary,binary,0.0604,0.0171,,,***,,,high,1 = wood-burning fireplace,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,6.210606955203923,1.8164669360690116,100*(exp(b - se^2/2) - 1),reported,0.07923003759339474,0.022431020576937917,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.5321637426900585,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.1,A2,0.1,23,Basement garage,garage,A_structural,binary,binary,0.0209,0.0253,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,2.0793182499322826,2.583433434381911,100*(exp(b - se^2/2) - 1),reported,0.018585198213287357,0.022497871521347853,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8260869565217391,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.2,A2,0.2,23,Basement garage,garage,A_structural,binary,binary,0.0326,0.0214,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,3.290066102475908,2.210913611635065,100*(exp(b - se^2/2) - 1),reported,0.034258258095237214,0.02248854979257903,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.5233644859813082,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.3,A2,0.3,23,Basement garage,garage,A_structural,binary,binary,0.0232,0.0184,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,2.3297974778154984,1.883187032512153,100*(exp(b - se^2/2) - 1),reported,0.028360369692245015,0.022492706997297773,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.2608695652173911,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.4,A2,0.4,23,Basement garage,garage,A_structural,binary,binary,0.017,0.0179,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,1.6982383611024554,1.8206901269621807,100*(exp(b - se^2/2) - 1),reported,0.021365506524925512,0.022496621576245095,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.9497206703910616,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.5,A2,0.5,23,Basement garage,garage,A_structural,binary,binary,0.0153,0.0151,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,1.5301888129742647,1.5332806427718377,100*(exp(b - se^2/2) - 1),reported,0.02279387084216148,0.02249591174618552,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0132450331125826,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.6,A2,0.6,23,Basement garage,garage,A_structural,binary,binary,0.0081,0.0153,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,0.8014903743807977,1.542443327442323,100*(exp(b - se^2/2) - 1),reported,0.01191185023244971,0.022500161550182786,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5294117647058824,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.8,A2,0.8,23,Basement garage,garage,A_structural,binary,binary,0.0019,0.0165,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,0.17654315425554845,1.6531379801371213,100*(exp(b - se^2/2) - 1),reported,0.0025911028312705104,0.022501682482086015,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.11515151515151514,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.9,A2,0.9,23,Basement garage,garage,A_structural,binary,binary,-0.0104,0.0181,,,,,,high,1 = basement garage,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",pct_premium,-1.050820397033847,1.791273546346463,100*(exp(b - se^2/2) - 1),reported,-0.01292810641674237,0.022499877513753548,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.574585635359116,1975.0,binary,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.1,A2,0.1,24,Lot size,lot_size,A_structural,level,acres,0.0022,0.0049,,,,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,5.436318392277638e-05,0.000121081636918911,100*b/4046.86 (X per acre->m2),reported,0.010102314586555252,0.022500609760963967,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.44897959183673475,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.2,A2,0.2,24,Lot size,lot_size,A_structural,level,acres,0.0088,0.0066,,,,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.0002174527356911055,0.00016308955176832913,100*b/4046.86 (X per acre->m2),reported,0.029988849969241192,0.022491637476930892,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.3333333333333335,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.3,A2,0.3,24,Lot size,lot_size,A_structural,level,acres,0.0122,0.005,,,**,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.0003014685653899417,0.00012355269073358266,100*b/4046.86 (X per acre->m2),reported,0.05482172222242831,0.022467918943618163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.44,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.4,A2,0.4,24,Lot size,lot_size,A_structural,level,acres,0.0111,0.0047,,,**,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.0002742869734285535,0.00011613952928956771,100*b/4046.86 (X per acre->m2),reported,0.053067568030608865,0.022470051328275824,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3617021276595747,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.5,A2,0.5,24,Lot size,lot_size,A_structural,level,acres,0.01,0.0057,,,*,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.0002471053814671653,0.00014085006743628427,100*b/4046.86 (X per acre->m2),reported,0.039446043761315525,0.02248424494394985,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.7543859649122806,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.6,A2,0.6,24,Lot size,lot_size,A_structural,level,acres,0.0112,0.0078,,,,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.00027675802724322514,0.00019274219754438895,100*b/4046.86 (X per acre->m2),reported,0.032293364708325875,0.02249002185044123,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.435897435897436,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.8,A2,0.8,24,Lot size,lot_size,A_structural,level,acres,0.0218,0.0099,,,**,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.0005386897315984205,0.0002446343276524937,100*b/4046.86 (X per acre->m2),reported,0.04948861235081379,0.022474186342800757,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.202020202020202,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.9,A2,0.9,24,Lot size,lot_size,A_structural,level,acres,0.0372,0.0074,,,***,,,high,Lot size in acres,"ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.000919232019057855,0.00018285798228570235,100*b/4046.86 (X per acre->m2),reported,0.11240012670044684,0.022359164988798568,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),5.027027027027026,1975.0,acre,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.1,A2,0.1,24,Distance to highway exit,highway_distance,D_location,level,miles,-0.0158,0.0104,,,,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.9817664837349876,0.6462260399268273,100*b/1.60934 (X per miles->km),reported,-0.03416540545910642,0.022488621314854858,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.5192307692307694,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.2,A2,0.2,24,Distance to highway exit,highway_distance,D_location,level,miles,-0.0151,0.0089,,,*,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.9382705002783742,0.5530203610912272,100*b/1.60934 (X per miles->km),reported,-0.038149348907668516,0.022485377832996672,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.6966292134831462,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.3,A2,0.3,24,Distance to highway exit,highway_distance,D_location,level,miles,-0.02,0.0067,,,***,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-1.242742384474668,0.41631869879901373,100*b/1.60934 (X per miles->km),reported,-0.06701841250816758,0.022451168190236136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.985074626865672,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.4,A2,0.4,24,Distance to highway exit,highway_distance,D_location,level,miles,-0.022,0.0065,,,***,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-1.3670166229221345,0.4038912749542671,100*b/1.60934 (X per miles->km),reported,-0.07593987722070189,0.02243678190611647,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.3846153846153846,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.5,A2,0.5,24,Distance to highway exit,highway_distance,D_location,level,miles,-0.0123,0.0071,,,*,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.7642865664519207,0.44117354648850715,100*b/1.60934 (X per miles->km),reported,-0.038952334266932676,0.02248468075570911,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.732394366197183,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.6,A2,0.6,24,Distance to highway exit,highway_distance,D_location,level,miles,-0.0124,0.0058,,,**,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.770500278374294,0.36039529149765365,100*b/1.60934 (X per miles->km),reported,-0.04805163590074266,0.02247576517937963,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.137931034482759,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.8,A2,0.8,24,Distance to highway exit,highway_distance,D_location,level,miles,-0.0163,0.0061,,,***,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-1.0128350433468543,0.3790364272647737,100*b/1.60934 (X per miles->km),reported,-0.0600192515364106,0.02246119229276716,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.6721311475409832,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.9,A2,0.9,24,Distance to highway exit,highway_distance,D_location,level,miles,-0.0141,0.0076,,,*,,,high,"Distance to nearest I-79 highway interchange, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.8761333810546408,0.4722421061003738,100*b/1.60934 (X per miles->km),reported,-0.04171035236281598,0.022482175741659675,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.8552631578947367,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.1,A2,0.1,24,Distance to FSU,university_distance,D_location,level,miles,-0.0024,0.0094,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.1; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.14912908613696013,0.5840889207030939,100*b/1.60934 (X per miles->km),reported,-0.005745034895847397,0.022501386675402305,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.2553191489361702,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.2,A2,0.2,24,Distance to FSU,university_distance,D_location,level,miles,-0.0072,0.0079,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.2; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.4473872584108804,0.4908832418674938,100*b/1.60934 (X per miles->km),reported,-0.02050362015432846,0.02249702766933262,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.911392405063291,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.3,A2,0.3,24,Distance to FSU,university_distance,D_location,level,miles,-0.0032,0.0064,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.3; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.19883878151594686,0.3976775630318937,100*b/1.60934 (X per miles->km),reported,-0.011250166995905777,0.022500333991811554,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.5,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.4,A2,0.4,24,Distance to FSU,university_distance,D_location,level,miles,0.0014,0.0061,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.4; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.08699196691322673,0.3790364272647737,100*b/1.60934 (X per miles->km),reported,0.005164269039824748,0.0225014579592364,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.22950819672131145,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.5,A2,0.5,24,Distance to FSU,university_distance,D_location,level,miles,-0.0033,0.0061,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.5; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.20505249343832022,0.3790364272647737,100*b/1.60934 (X per miles->km),reported,-0.012172180379383278,0.022500091004314545,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.540983606557377,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.6,A2,0.6,24,Distance to FSU,university_distance,D_location,level,miles,-0.0006,0.0048,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.6; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,-0.03728227153424003,0.29825817227392026,100*b/1.60934 (X per miles->km),reported,-0.0028127086261162345,0.022501669008929876,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.125,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.8,A2,0.8,24,Distance to FSU,university_distance,D_location,level,miles,0.0012,0.0056,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.8; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.07456454306848007,0.34796786765290694,100*b/1.60934 (X per miles->km),reported,0.004821749237640972,0.02250149644232454,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.21428571428571427,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee,eeedb48b06f3660101615bf3de6b27e1951880ee:TA2-q0.9,A2,0.9,24,Distance to FSU,university_distance,D_location,level,miles,0.0043,0.0065,,,,,,high,"Distance to Fairmont State University, miles","ln(sale price), USD",log,quantile,1985.0,,se,"Spatial quantile regression at quantile 0.9; model (2) with BWN dummy; year fixed effects included; no goodness-of-fit reported (qregspiv, McSpatial)",semi_elasticity,0.2671896126620536,0.4038912749542671,100*b/1.60934 (X per miles->km),reported,0.01488412941251288,0.022499265391007845,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.6615384615384615,1975.0,miles,,2021.0,United States,North America,High income,2012.0,2017.0,single_family,transaction,journal,True,False,bootstrap,,2014.5,quantile,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,SQFT2,living_area,A_structural,dummy,binary,0.154,,28.7,0.0,,,,high,"2nd square-footage quintile (1312-1580 sqft); base 0-1311 sqft; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,16.647409387167844,0.6259219392469677,100*(exp(b - se^2/2) - 1),|b/t|,0.15206551349896075,0.00529844994769898,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.7,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,SQFT3,living_area,A_structural,dummy,binary,0.284,,47.61,0.0,,,,high,"3rd square-footage quintile (1581-1930 sqft); base 0-1311 sqft; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,32.840929627064575,0.7924279612135973,100*(exp(b - se^2/2) - 1),|b/t|,0.24729977692328722,0.005194282229012544,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.61,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,SQFT4,living_area,A_structural,dummy,binary,0.449,,63.84,0.0,,,,high,"4th square-footage quintile (1931-2541 sqft); base 0-1311 sqft; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,56.67059073712544,1.1019241088385865,100*(exp(b - se^2/2) - 1),|b/t|,0.32379593147260854,0.005071991407778955,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),63.84,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,SQFT5,living_area,A_structural,dummy,binary,0.666,,74.79,0.0,,,,high,"5th square-footage quintile (2542+ sqft); base 0-1311 sqft; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,94.63588118667975,1.7332883615841368,100*(exp(b - se^2/2) - 1),|b/t|,0.3721377105328211,0.004975768291654246,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),74.79,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,ONEBEDROOM,bedrooms,A_structural,dummy,binary,-0.149,,-8.06,0.0,,,,high,"One bedroom; base three bedrooms; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,-13.85780910888046,1.5927270238206548,100*(exp(b - se^2/2) - 1),|b/t|,-0.043167720818191105,0.005355796627567134,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.06,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,True
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,TWOBEDROOMS,bedrooms,A_structural,dummy,binary,0.02,,2.67,0.008,,,,high,"Two bedrooms; base three bedrooms; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,2.0172718864181594,0.7641957603196673,100*(exp(b - se^2/2) - 1),|b/t|,0.014311853339242828,0.005360244696345629,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.67,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,FOURBEDROOMS,bedrooms,A_structural,dummy,binary,-0.025,,-5.72,0.0,,,,high,"Four bedrooms; base three bedrooms; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,-2.469940330774689,0.42627181469769787,100*(exp(b - se^2/2) - 1),|b/t|,-0.03064933437566218,0.005358275240500381,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.72,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,FIVEBEDROOMS,bedrooms,A_structural,dummy,binary,-0.064,,-6.67,0.0,,,,high,"Five bedrooms; base three bedrooms; printed as 'FIV EBEDROOMS'; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,-6.203817955491475,0.9000347821584211,100*(exp(b - se^2/2) - 1),|b/t|,-0.03573365837355882,0.005357370070998324,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.67,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,SIXPLUSBEDROOMS,bedrooms,A_structural,dummy,binary,-0.105,,-3.26,0.001,,,,high,"Six or more bedrooms; base three bedrooms; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,-10.014235159017716,2.8998182475938004,100*(exp(b - se^2/2) - 1),|b/t|,-0.017473519465634607,0.005359975296206935,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.26,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,TWOFULLBATH,bathrooms,A_structural,dummy,binary,0.16,,19.75,0.0,,,,high,"Two full bathrooms; base one full bath; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,17.347236256638254,0.9506923511832388,100*(exp(b - se^2/2) - 1),|b/t|,0.10528720424589905,0.005330997683336661,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.75,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,THREEFULLBATH,bathrooms,A_structural,dummy,binary,0.298,,29.34,0.0,,,,high,"Three full bathrooms; base one; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,34.70923029104655,1.368282933838129,100*(exp(b - se^2/2) - 1),|b/t|,0.15537552902280397,0.005295689469079889,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.34,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,FOURFULLBATH,bathrooms,A_structural,dummy,binary,0.516,,34.15,0.0,,,,high,"Four full bathrooms; base one; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,67.51217460187662,2.531366021485081,100*(exp(b - se^2/2) - 1),|b/t|,0.18007831074686476,0.0052731569764821315,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.15,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,FIVEPLUSFULLBATH,bathrooms,A_structural,dummy,binary,0.739,,24.97,0.0,,,,high,"Five or more full bathrooms; base one; printed as 'FIV EPLUSFULLBATH'; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,109.29238356369298,6.1968290871294025,100*(exp(b - se^2/2) - 1),|b/t|,0.1326756405667321,0.005313401704714942,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.97,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,ONEHALFBATH,bathrooms,A_structural,dummy,binary,0.089,,21.89,0.0,,,,high,"One half bathroom; base zero half baths; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,9.30716217267602,0.44442292559636076,100*(exp(b - se^2/2) - 1),|b/t|,0.1165480563353456,0.005324260225461197,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.89,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,TWOHALFBATH,bathrooms,A_structural,dummy,binary,0.18,,9.47,0.0,,,,high,"Two half bathrooms; base zero; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,19.700111674566777,2.2755979446877066,100*(exp(b - se^2/2) - 1),|b/t|,0.050701423471159565,0.005353898993786649,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.47,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,THREEHALFBATH,bathrooms,A_structural,dummy,binary,0.425,,3.65,0.0,,,,high,"Three half bathrooms; base zero; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,51.92564759286535,17.81029940703934,100*(exp(b - se^2/2) - 1),|b/t|,0.01956315252991156,0.005359767816414126,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.65,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,FOURPLUSHALFBATH,bathrooms,A_structural,dummy,binary,0.164,,2.83,0.005,,,,high,"Four or more half bathrooms; base zero; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,17.623759782283965,6.827814405484328,100*(exp(b - se^2/2) - 1),|b/t|,0.015169300718867318,0.00536017693246195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.83,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,FIREPLACE,fireplace,B_interior,dummy,binary,0.099,,25.42,0.0,,,,high,"Presence of a fireplace; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,10.405792652578306,0.429986481732216,100*(exp(b - se^2/2) - 1),|b/t|,0.13502345858275874,0.0053117017538457404,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.42,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,ONEGARAGE,garage,A_structural,dummy,binary,0.073,,13.16,0.0,,,,high,"One garage space; base zero; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,7.571398668208307,0.5967198267080042,100*(exp(b - se^2/2) - 1),|b/t|,0.07037313858437586,0.005347502931943454,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.16,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,TWOGARAGE,garage,A_structural,dummy,binary,0.163,,31.66,0.0,,,,high,"Two garage spaces; base zero; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,17.70210901943472,0.6059917258977262,100*(exp(b - se^2/2) - 1),|b/t|,0.16732980536438824,0.005285211792937089,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),31.66,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,THREEPLUSGARAGE,garage,A_structural,dummy,binary,0.316,,31.74,0.0,,,,high,"Three or more garage spaces; base zero; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,37.15622794673272,1.3655802166913344,100*(exp(b - se^2/2) - 1),|b/t|,0.16774074009811157,0.005284837432202634,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),31.74,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,True
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,6-10YEARS,age,A_structural,dummy,binary,-0.02,,-4.53,0.0,,,,high,"House 6-10 years old at sale; base 2-5 years; printed as '6 -10Y EARS'; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,-1.9810879820999716,0.43275879616192287,100*(exp(b - se^2/2) - 1),|b/t|,-0.024277238202337962,0.005359213731200433,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.53,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,11-25YEARS,age,A_structural,dummy,binary,-0.048,,-9.67,0.0,,,,high,"House 11-25 years old; base 2-5 years; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,-4.687795515622028,0.4731170814862485,100*(exp(b - se^2/2) - 1),|b/t|,-0.051769363107411585,0.005353605285151147,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.67,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,26-50YEARS,age,A_structural,dummy,binary,-0.108,,-16.06,0.0,,,,high,"House 26-50 years old; base 2-5 years; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,-10.239269990909373,0.6036349963542154,100*(exp(b - se^2/2) - 1),|b/t|,-0.08577703466314729,0.0053410357822632195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.06,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,51-100YEARS,age,A_structural,dummy,binary,-0.059,,-5.49,0.0,,,,high,"House 51-100 years old; base 2-5 years; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,-5.734766774780587,1.0131092783291236,100*(exp(b - se^2/2) - 1),|b/t|,-0.029418019937671163,0.005358473576989283,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.49,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,101+YEARS,age,A_structural,dummy,binary,0.047,,2.45,0.014,,,,high,"House 101 or more years old; base 2-5 years; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,4.792916538822145,2.0106830378262783,100*(exp(b - se^2/2) - 1),|b/t|,0.013132812022774264,0.005360331437867047,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.45,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,POOL,pool,C_exterior,dummy,binary,0.089,,12.44,0.0,,,,high,"Swimming pool; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,9.305268224014762,0.7820271576611204,100*(exp(b - se^2/2) - 1),|b/t|,0.06654047478014333,0.005348912763677116,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.44,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,WATERFRONT,waterfront,C_exterior,dummy,binary,0.198,,34.6,0.0,,,,high,"Marketed as waterfront property; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,21.894243499807132,0.6975565143834833,100*(exp(b - se^2/2) - 1),|b/t|,0.18237280479717524,0.005270890312057087,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.6,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,CONDO,dwelling_type,A_structural,dummy,binary,-0.092,,-13.38,0.0,,,,high,"Condominium/townhouse vs single-family; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,-8.791641166873942,0.6271575019293596,100*(exp(b - se^2/2) - 1),|b/t|,-0.07154361683566667,0.005347056564698555,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.38,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,SLR1,flood_risk,E_environment,dummy,binary,-0.025,,-1.86,0.062,,,,high,"Inundated with 0-1 ft sea level rise; base NORISK (>6 ft); robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,-2.4778182139371108,1.3109004193929201,100*(exp(b - se^2/2) - 1),|b/t|,-0.009970580733994719,0.005360527276341247,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.86,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,SLR2,flood_risk,E_environment,dummy,binary,-0.077,,-3.45,0.001,,,,high,"Inundated with 1.01-2 ft SLR; base NORISK; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,-7.434072473268428,2.0664788037014534,100*(exp(b - se^2/2) - 1),|b/t|,-0.01849157612926335,0.0053598771389169126,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.45,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,SLR3,flood_risk,E_environment,dummy,binary,-0.022,,-1.42,0.156,,,,high,"Inundated with 2.01-3 ft SLR; base NORISK; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,-2.1877162256627725,1.515583462755396,100*(exp(b - se^2/2) - 1),|b/t|,-0.007612106573798522,0.00536063843225248,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.42,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,SLR5,flood_risk,E_environment,dummy,binary,0.006,,0.69,0.487,,,,high,"Inundated with 4.01-5 ft SLR; base NORISK; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,0.5980002064690959,0.874798292220926,100*(exp(b - se^2/2) - 1),|b/t|,0.00369892238138974,0.005360757074477885,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.69,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M1,3,Model 1,7,SLR6,flood_risk,E_environment,dummy,binary,0.005,,0.63,0.528,,,,high,"Inundated with 5.01-6 ft SLR; base NORISK; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; six SLR inundation-band dummies (SLR1-SLR6); t and p in separate columns,pct_premium,0.49808694139785725,0.7976289848090483,100*(exp(b - se^2/2) - 1),|b/t|,0.0033772808003146343,0.005360763175102594,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.63,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,SQFT2,living_area,A_structural,dummy,binary,0.154,,28.75,0.0,,,,high,"2nd square-footage quintile (1312-1580 sqft); base 0-1311 sqft; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,16.647415223057884,0.624833379352625,100*(exp(b - se^2/2) - 1),|b/t|,0.1523242943029288,0.005298236323580132,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),28.75,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,SQFT3,living_area,A_structural,dummy,binary,0.285,,47.7,0.0,,,,high,"3rd square-footage quintile (1581-1930 sqft); base 0-1311 sqft; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,32.97382929148001,0.7945119035945911,100*(exp(b - se^2/2) - 1),|b/t|,0.24773859609159066,0.0051936812597817746,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),47.7,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,SQFT4,living_area,A_structural,dummy,binary,0.449,,63.93,0.0,,,,high,"4th square-footage quintile (1931-2541 sqft); base 0-1311 sqft; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,56.670601639633624,1.1003728313507801,100*(exp(b - se^2/2) - 1),|b/t|,0.32420446106508277,0.005071241374395162,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),63.93,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,SQFT5,living_area,A_structural,dummy,binary,0.666,,74.9,0.0,,,,high,"5th square-footage quintile (2542+ sqft); base 0-1311 sqft; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,94.63590383709484,1.730742811253372,100*(exp(b - se^2/2) - 1),|b/t|,0.3726091025292622,0.004974754372887346,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),74.9,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,True
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,ONEBEDROOM,bedrooms,A_structural,dummy,binary,-0.149,,-8.08,0.0,,,,high,"One bedroom; base three bedrooms; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,-13.857736331007475,1.5887846301973365,100*(exp(b - se^2/2) - 1),|b/t|,-0.04327463640315941,0.0053557718320741835,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-8.08,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,TWOBEDROOMS,bedrooms,A_structural,dummy,binary,0.02,,2.65,0.008,,,,high,"Two bedrooms; base three bedrooms; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,2.017228522255343,0.7699632754918911,100*(exp(b - se^2/2) - 1),|b/t|,0.014204670157941798,0.005360252889789358,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.65,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,FOURBEDROOMS,bedrooms,A_structural,dummy,binary,-0.025,,-5.71,0.0,,,,high,"Four bedrooms; base three bedrooms; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,-2.469943596430879,0.4270183502751019,100*(exp(b - se^2/2) - 1),|b/t|,-0.030595801826118103,0.005358284032595114,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.71,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,FIVEBEDROOMS,bedrooms,A_structural,dummy,binary,-0.064,,-6.68,0.0,,,,high,"Five bedrooms; base three bedrooms; printed as 'FIV EBEDROOMS'; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,-6.2038050375945115,0.8986874247001001,100*(exp(b - se^2/2) - 1),|b/t|,-0.035787163512592715,0.005357359807274359,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-6.68,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,SIXPLUSBEDROOMS,bedrooms,A_structural,dummy,binary,-0.105,,-3.25,0.001,,,,high,"Six or more bedrooms; base three bedrooms; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,-10.014522833133622,2.9087407652787043,100*(exp(b - se^2/2) - 1),|b/t|,-0.01741993600275667,0.005359980308540514,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.25,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,TWOFULLBATH,bathrooms,A_structural,dummy,binary,0.159,,19.73,0.0,,,,high,"Two full bathrooms; base one full bath; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,17.229987904945745,0.9447629676747799,100*(exp(b - se^2/2) - 1),|b/t|,0.10518176444171382,0.005331057498312915,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),19.73,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,THREEFULLBATH,bathrooms,A_structural,dummy,binary,0.298,,29.32,0.0,,,,high,"Three full bathrooms; base one; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,34.70922080852637,1.3692162782677597,100*(exp(b - se^2/2) - 1),|b/t|,0.15527216960618115,0.0052957765895696165,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),29.32,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,FOURFULLBATH,bathrooms,A_structural,dummy,binary,0.516,,34.14,0.0,,,,high,"Four full bathrooms; base one; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,67.51216339810023,2.532107487806547,100*(exp(b - se^2/2) - 1),|b/t|,0.18002728844020763,0.005273207042771167,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.14,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,FIVEPLUSFULLBATH,bathrooms,A_structural,dummy,binary,0.739,,24.97,0.0,,,,high,"Five or more full bathrooms; base one; printed as 'FIV EPLUSFULLBATH'; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,109.29238356369298,6.1968290871294025,100*(exp(b - se^2/2) - 1),|b/t|,0.1326756405667321,0.005313401704714942,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),24.97,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,ONEHALFBATH,bathrooms,A_structural,dummy,binary,0.089,,21.88,0.0,,,,high,"One half bathroom; base zero half baths; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,9.307161346658944,0.4446260439352988,100*(exp(b - se^2/2) - 1),|b/t|,0.11649553646250638,0.005324293256970127,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),21.88,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,TWOHALFBATH,bathrooms,A_structural,dummy,binary,0.18,,9.44,0.0,,,,high,"Two half bathrooms; base zero; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,19.699974023951363,2.2828297178170107,100*(exp(b - se^2/2) - 1),|b/t|,0.050541217433949355,0.005353942524782771,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),9.44,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,THREEHALFBATH,bathrooms,A_structural,dummy,binary,0.425,,3.65,0.0,,,,high,"Three half bathrooms; base zero; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,51.92564759286535,17.81029940703934,100*(exp(b - se^2/2) - 1),|b/t|,0.01956315252991156,0.005359767816414126,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.65,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,FOURPLUSHALFBATH,bathrooms,A_structural,dummy,binary,0.163,,2.83,0.005,,,,high,"Four or more half bathrooms; base zero; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,17.508593703389018,6.7793986013858705,100*(exp(b - se^2/2) - 1),|b/t|,0.015169300718867318,0.00536017693246195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.83,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,FIREPLACE,fireplace,B_interior,dummy,binary,0.099,,25.42,0.0,,,,high,"Presence of a fireplace; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,10.405792652578306,0.429986481732216,100*(exp(b - se^2/2) - 1),|b/t|,0.13502345858275874,0.0053117017538457404,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),25.42,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,ONEGARAGE,garage,A_structural,dummy,binary,0.073,,13.19,0.0,,,,high,"One garage space; base zero; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,7.571406188125529,0.5953626170945667,100*(exp(b - se^2/2) - 1),|b/t|,0.07053276648130044,0.0053474424928961675,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),13.19,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,TWOGARAGE,garage,A_structural,dummy,binary,0.163,,31.7,0.0,,,,high,"Two garage spaces; base zero; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,17.702112953705786,0.6052270675685177,100*(exp(b - se^2/2) - 1),|b/t|,0.16753528364684456,0.005285024720720648,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),31.7,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,THREEPLUSGARAGE,garage,A_structural,dummy,binary,0.316,,31.77,0.0,,,,high,"Three or more garage spaces; base zero; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,37.156240778155514,1.364290716958859,100*(exp(b - se^2/2) - 1),|b/t|,0.1678948180956017,0.005284696823909403,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),31.77,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,True
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,6-10YEARS,age,A_structural,dummy,binary,-0.02,,-4.52,0.0,,,,high,"House 6-10 years old at sale; base 2-5 years; printed as '6 -10Y EARS'; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,-1.9810922138028708,0.4337162271268829,100*(exp(b - se^2/2) - 1),|b/t|,-0.024223677546937734,0.005359220696225163,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-4.52,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,11-25YEARS,age,A_structural,dummy,binary,-0.048,,-9.7,0.0,,,,high,"House 11-25 years old; base 2-5 years; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,-4.687788263660886,0.47165383278062095,100*(exp(b - se^2/2) - 1),|b/t|,-0.05192953882559311,0.005353560703669393,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-9.7,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,26-50YEARS,age,A_structural,dummy,binary,-0.108,,-16.06,0.0,,,,high,"House 26-50 years old; base 2-5 years; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,-10.239269990909373,0.6036349963542154,100*(exp(b - se^2/2) - 1),|b/t|,-0.08577703466314729,0.0053410357822632195,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-16.06,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,51-100YEARS,age,A_structural,dummy,binary,-0.059,,-5.5,0.0,,,,high,"House 51-100 years old; base 2-5 years; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,-5.734746998107065,1.011267261459434,100*(exp(b - se^2/2) - 1),|b/t|,-0.029471558173474667,0.00535846512244994,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-5.5,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,101+YEARS,age,A_structural,dummy,binary,0.047,,2.45,0.014,,,,high,"House 101 or more years old; base 2-5 years; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,4.792916538822145,2.0106830378262783,100*(exp(b - se^2/2) - 1),|b/t|,0.013132812022774264,0.005360331437867047,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.45,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,POOL,pool,C_exterior,dummy,binary,0.089,,12.47,0.0,,,,high,"Swimming pool; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,9.305281667517917,0.7801457771695539,100*(exp(b - se^2/2) - 1),|b/t|,0.06670022911135165,0.005348855582305666,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),12.47,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,WATERFRONT,waterfront,C_exterior,dummy,binary,0.198,,34.55,0.0,,,,high,"Marketed as waterfront property; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,21.894237718880483,0.698566002826875,100*(exp(b - se^2/2) - 1),|b/t|,0.18211800736904946,0.005271143483908812,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),34.55,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,CONDO,dwelling_type,A_structural,dummy,binary,-0.091,,-13.49,0.0,,,,high,"Condominium/townhouse vs single-family; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,-8.700306228871534,0.6158977886718545,100*(exp(b - se^2/2) - 1),|b/t|,-0.07212874544970381,0.005346830648606658,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-13.49,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,HIRISK,flood_risk,E_environment,dummy,binary,-0.031,,-3.17,0.002,,,,high,"Inundated with 0-3 ft SLR; base NORISK; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,-3.0570782433120613,0.9480675951216657,100*(exp(b - se^2/2) - 1),|b/t|,-0.016991262935096563,0.005360019853342765,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.17,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,f326d0249d4fa4d2ec6af5feb9cf6966a73ca545:T3-M2,3,Model 2,7,LOWRISK,flood_risk,E_environment,dummy,binary,0.004,,0.69,0.493,,,,high,"Inundated with 3.01-6 ft SLR; base NORISK; robust SE (not printed), t and p printed","ln(real sales price, 2012 USD)",log,OLS,34807.0,0.788,t,Full sample; HIRISK and LOWRISK dummies; t and p in separate columns,pct_premium,0.3991140279098637,0.5820336293781694,100*(exp(b - se^2/2) - 1),|b/t|,0.00369892238138974,0.005360757074477885,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.69,34797.0,binary,,2020.0,United States,North America,High income,2007.0,2016.0,mixed,transaction,journal,True,True,robust,,2011.5,ols,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c1,3,1 (OLS),15,NRM,bedrooms,A_structural,level,count,-0.009,,,0.331,,,,high,Number of rooms,LogLP: log listing price per m2,log,OLS,2092.0,0.537,p,complete sample,semi_elasticity,-0.8999999999999999,0.9258291400497722,100*b/1 (per unit count),|b/z(p)| (two-sided normal),-0.02129966457111355,0.021910944592469624,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.9721016125627848,2082.0,count,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,ols,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c2,3,2 (SEM),15,NRM,bedrooms,A_structural,level,count,-0.021,,,0.001,***,,,high,Number of rooms,LogLP: log listing price per m2,log,spatial_error,2092.0,0.754,p,complete sample; lambda=0.797,semi_elasticity,-2.1,0.638195696726001,100*b/1 (per unit count),|b/z(p)| (two-sided normal),-0.07192811842790625,0.02185915031156568,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,2082.0,count,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c2,3,2 (SEM),15,NBT,bathrooms,A_structural,level,count,0.034,,,0.001,***,,,high,Number of bathrooms,LogLP: log listing price per m2,log,spatial_error,2092.0,0.754,p,complete sample; lambda=0.797,semi_elasticity,3.4000000000000004,1.0332692232706682,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.07192811842790625,0.02185915031156568,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,2082.0,count,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c1,3,1 (OLS),15,PNT = 1,dwelling_type,A_structural,dummy,binary,0.092,,,0.014,*,,,high,Penthouse,LogLP: log listing price per m2,log,OLS,2092.0,0.537,p,complete sample,pct_premium,9.559667365310043,4.104792511599759,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.05377525721592513,0.02188420558832698,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.457263390205437,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,ols,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c1,3,1 (OLS),15,CBX = 1,garage,A_structural,dummy,binary,0.019,,,0.293,,,,high,Car box,LogLP: log listing price per m2,log,OLS,2092.0,0.537,p,complete sample,pct_premium,1.9015298696204663,1.8414919201190625,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.023039853641387942,0.021910098877600183,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.0515631978704927,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,ols,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c1,3,1 (OLS),15,CTP = 1,age,A_structural,dummy,binary,0.016,,,0.392,,,,high,"Construction period <=1945 (ref. CTP=3, 1976-now)",LogLP: log listing price per m2,log,OLS,2092.0,0.537,p,complete sample,pct_premium,1.5951194015172643,1.899314861522387,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.01875663628593222,0.021912061042128075,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.8559959854926817,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,ols,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c2,3,2 (SEM),15,CTP = 1,age,A_structural,dummy,binary,-0.034,,,0.013,*,,,high,"Construction period <=1945 (ref. CTP=3, 1976-now)",LogLP: log listing price per m2,log,spatial_error,2092.0,0.754,p,complete sample; lambda=0.797,pct_premium,-3.351905172594749,1.323127363196706,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.05435361328265819,0.02188351930686972,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4837692932505324,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c1,3,1 (OLS),15,MTL = 1,condition,A_structural,dummy,binary,-0.053,,,0.031,*,,,high,Maintenance: to renovate (ref. MTL=2 partially to renovate),LogLP: log listing price per m2,log,OLS,2092.0,0.537,p,complete sample,pct_premium,-5.190621348054025,2.3302015067545874,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.04722148823099137,0.021891468068247898,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.1570727044790092,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,ols,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c2,3,2 (SEM),15,MTL = 1,condition,A_structural,dummy,binary,-0.057,,,0.001,***,,,high,Maintenance: to renovate (ref. MTL=2 partially to renovate),LogLP: log listing price per m2,log,spatial_error,2092.0,0.754,p,complete sample; lambda=0.797,pct_premium,-5.55476409619483,1.6362687906042457,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.07192811842790625,0.02185915031156568,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.290526731491894,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c2,3,2 (SEM),15,BLC = 2,condition,A_structural,dummy,binary,0.1,,,0.001,***,,,high,Building category: economic (ref. BLC=1 tenement),LogLP: log listing price per m2,log,spatial_error,2092.0,0.754,p,complete sample; lambda=0.797,pct_premium,10.466068532128347,3.358644400298105,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.07192811842790625,0.02185915031156568,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c1,3,1 (OLS),15,BLT = 1,dwelling_type,A_structural,dummy,binary,0.088,,,0.005,**,,,high,Building type: detached house/villa (ref. condominium),LogLP: log listing price per m2,log,OLS,2092.0,0.537,p,complete sample,pct_premium,9.145164480809797,3.42336297561461,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.06140263669432942,0.021874562887983343,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8070337683438042,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,ols,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c1,3,1 (OLS),15,ARC = 1,air_conditioning,A_structural,dummy,binary,0.054,,,0.017,*,,,high,Air-conditioning system,LogLP: log listing price per m2,log,OLS,2092.0,0.537,p,complete sample,pct_premium,5.521448300980647,2.3880665274879047,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.052235477860772775,0.021885996808857444,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.3867077344922505,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,ols,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c2,3,2 (SEM),15,ARC = 1,air_conditioning,A_structural,dummy,binary,0.045,,,0.004,**,,,high,Air-conditioning system,LogLP: log listing price per m2,log,spatial_error,2092.0,0.754,p,complete sample; lambda=0.797,pct_premium,4.590001561401391,1.6354624222989391,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.06295243983936984,0.02187244691090704,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.878161739095483,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c1,3,1 (OLS),15,EPC = 3,energy_efficiency,A_structural,dummy,binary,0.025,,,0.585,,,,high,"High EPC labels A-A4/B (ref. EPC=2 C-D, except NZ where ref. is EPC=1)",LogLP: log listing price per m2,log,OLS,2092.0,0.537,p,complete sample,pct_premium,2.4241274569337,4.693841646943766,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.011967335671084108,0.021914347092495432,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.5460959261333559,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,ols,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c2,3,2 (SEM),15,EPC = 3,energy_efficiency,A_structural,dummy,binary,0.062,,,0.05,*,,,high,"High EPC labels A-A4/B (ref. EPC=2 C-D, except NZ where ref. is EPC=1)",LogLP: log listing price per m2,log,spatial_error,2092.0,0.754,p,complete sample; lambda=0.797,pct_premium,6.343014479170561,3.3656570168363724,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.04291483462977536,0.021895726129807537,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9599639845400543,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c1,3,1 (OLS),15,EPC = 1,energy_efficiency,A_structural,dummy,binary,-0.033,,,0.018,*,,,high,Low EPC labels E/F/G (ref. EPC=2 C-D),LogLP: log listing price per m2,log,OLS,2092.0,0.537,p,complete sample,pct_premium,-3.2555576415076337,1.3497010402418894,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.051775153583376664,0.021886522171694036,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.365618126864293,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,ols,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T3-c2,3,2 (SEM),15,EPC = 1,energy_efficiency,A_structural,dummy,binary,-0.027,,,0.005,**,,,high,Low EPC labels E/F/G (ref. EPC=2 C-D),LogLP: log listing price per m2,log,spatial_error,2092.0,0.754,p,complete sample; lambda=0.797,pct_premium,-2.668378477582145,0.9362464327126057,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.06140263669432942,0.021874562887983343,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.8070337683438042,2082.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-CZ,4,Central Zone (SEM),17,NBT,bathrooms,A_structural,level,count,0.043,,,0.001,***,,,high,Number of bathrooms,LogLP: log listing price per m2,log,spatial_error,886.0,0.583,p,Central Zone LISA high-high cluster; stepwise selection; lambda=0.627,semi_elasticity,4.3,1.3067816647246682,100*b/1 (per unit count),|b/z(p)| (two-sided normal),0.11049581540212391,0.0335799780456505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,876.0,count,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-CZ,4,Central Zone (SEM),17,ALL = 2,floor_level,A_structural,dummy,binary,0.06,,,0.001,***,,,high,Allocation level: intermediate floor (ref. lower),LogLP: log listing price per m2,log,spatial_error,886.0,0.583,p,Central Zone LISA high-high cluster; stepwise selection; lambda=0.627,pct_premium,6.166003901887729,1.936170041804704,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.11049581540212391,0.0335799780456505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,876.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-CZ,4,Central Zone (SEM),17,ALL = 3,floor_level,A_structural,dummy,binary,0.054,,,0.001,***,,,high,Allocation level: higher floor (ref. lower),LogLP: log listing price per m2,log,spatial_error,886.0,0.583,p,Central Zone LISA high-high cluster; stepwise selection; lambda=0.627,pct_premium,5.534248407246745,1.7321290227152415,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.11049581540212391,0.0335799780456505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,876.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-CZ,4,Central Zone (SEM),17,PNT = 1,dwelling_type,A_structural,dummy,binary,0.096,,,0.003,**,,,high,Penthouse,LogLP: log listing price per m2,log,spatial_error,886.0,0.583,p,Central Zone LISA high-high cluster; stepwise selection; lambda=0.627,pct_premium,10.0183305912539,3.560721087973158,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.09977027213550016,0.033618289298240504,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.9677379253417833,876.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-CZ,4,Central Zone (SEM),17,BLT = 1,dwelling_type,A_structural,dummy,binary,0.072,,,0.036,*,,,high,Building type: detached house/villa (ref. condominium),LogLP: log listing price per m2,log,spatial_error,886.0,0.583,p,Central Zone LISA high-high cluster; stepwise selection; lambda=0.627,pct_premium,7.402204419025726,3.6899314538238337,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0706714655794949,0.03370238979021729,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.0969274291643423,876.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-CZ,4,Central Zone (SEM),17,CTP = 2,age,A_structural,dummy,binary,-0.069,,,0.001,**,,,high,Construction period 1946-1975 (ref. CTP=3 in Table 3; sole CTP dummy in Tables 4),LogLP: log listing price per m2,log,spatial_error,886.0,0.583,p,Central Zone LISA high-high cluster; stepwise selection; lambda=0.627,pct_premium,-6.687849437273852,1.9571195185579844,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.11049581540212391,0.0335799780456505,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.2905267314918945,876.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-CZ,4,Central Zone (SEM),17,EPC = 3,energy_efficiency,A_structural,dummy,binary,0.039,,,0.544,,,,high,"High EPC labels A-A4/B (ref. EPC=2 C-D, except NZ where ref. is EPC=1)",LogLP: log listing price per m2,log,spatial_error,886.0,0.583,p,Central Zone LISA high-high cluster; stepwise selection; lambda=0.627,pct_premium,3.7624964645435854,6.68304141873796,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.02049673281056913,0.03377977097134937,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.606775363514265,876.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-CZ,4,Central Zone (SEM),17,EPC = 1,energy_efficiency,A_structural,dummy,binary,-0.037,,,0.049,*,,,high,Low EPC labels E/F/G (ref. EPC=2 C-D),LogLP: log listing price per m2,log,spatial_error,886.0,0.583,p,Central Zone LISA high-high cluster; stepwise selection; lambda=0.627,pct_premium,-3.6494062832989282,1.8112449405339477,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.06636591196818671,0.03371238078824572,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.9685916691865943,876.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-CZ,4,Central Zone (SEM),17,ARC = 1,air_conditioning,A_structural,dummy,binary,0.083,,,0.014,*,,,high,Air-conditioning system,LogLP: log listing price per m2,log,spatial_error,886.0,0.583,p,Central Zone LISA high-high cluster; stepwise selection; lambda=0.627,pct_premium,8.592216013314701,3.6700571240742783,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.08273857315292865,0.033671023416830946,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.4572633902054366,876.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-NZ,4,Northern Zone (SEM),17,CBX = 1,garage,A_structural,dummy,binary,0.063,,,0.025,*,,,high,Car box,LogLP: log listing price per m2,log,spatial_error,660.0,0.603,p,Northern Zone LISA low-low cluster; stepwise selection; lambda=0.65,pct_premium,6.4606222939519675,2.9935133943228727,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.08757725475580977,0.03907252082689781,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.241402727604945,650.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-NZ,4,Northern Zone (SEM),17,LTR = 1,terrace_balcony,C_exterior,dummy,binary,0.105,,,0.001,***,,,high,Large terrace present,LogLP: log listing price per m2,log,spatial_error,660.0,0.603,p,Northern Zone LISA low-low cluster; stepwise selection; lambda=0.65,pct_premium,11.014527242119598,3.5442536591846046,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.1280033535074993,0.038900566369039574,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.290526731491895,650.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-NZ,4,Northern Zone (SEM),17,MTL = 1,condition,A_structural,dummy,binary,-0.093,,,0.002,***,,,high,Maintenance: to renovate (ref. MTL=2 partially to renovate),LogLP: log listing price per m2,log,spatial_error,660.0,0.603,p,Northern Zone LISA low-low cluster; stepwise selection; lambda=0.65,pct_premium,-8.92190395729826,2.742220879589085,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.12032819968845838,0.038938237571426136,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.090232306167813,650.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-NZ,4,Northern Zone (SEM),17,MTL = 3,condition,A_structural,dummy,binary,0.089,,,0.001,***,,,high,Maintenance: good (ref. MTL=2),LogLP: log listing price per m2,log,spatial_error,660.0,0.603,p,Northern Zone LISA low-low cluster; stepwise selection; lambda=0.65,pct_premium,9.268090312125965,2.956492572510895,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.1280033535074993,0.038900566369039574,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,650.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-NZ,4,Northern Zone (SEM),17,BLC = 5,condition,A_structural,dummy,binary,0.281,,,0.001,***,,,high,Building category: prestigious (ref. BLC=1),LogLP: log listing price per m2,log,spatial_error,660.0,0.603,p,Northern Zone LISA low-low cluster; stepwise selection; lambda=0.65,pct_premium,31.963304935214243,11.310391711574646,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.1280033535074993,0.038900566369039574,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,650.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-NZ,4,Northern Zone (SEM),17,BLC = 2,condition,A_structural,dummy,binary,0.125,,,0.009,**,,,high,Building category: economic (ref. BLC=1 tenement),LogLP: log listing price per m2,log,spatial_error,660.0,0.603,p,Northern Zone LISA low-low cluster; stepwise selection; lambda=0.65,pct_premium,13.18516803337455,5.42268838909646,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.10191968100734164,0.039018977209781903,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.6120541412292777,650.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-NZ,4,Northern Zone (SEM),17,CTP = 2,age,A_structural,dummy,binary,-0.045,,,0.015,*,,,high,Construction period 1946-1975 (ref. CTP=3 in Table 3; sole CTP dummy in Tables 4),LogLP: log listing price per m2,log,spatial_error,660.0,0.603,p,Northern Zone LISA low-low cluster; stepwise selection; lambda=0.65,pct_premium,-4.416610641757835,1.7686341497910059,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),-0.0949744939863757,0.03904592651839688,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.4323790585844467,650.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-NZ,4,Northern Zone (SEM),17,EPC = 3,energy_efficiency,A_structural,dummy,binary,0.079,,,0.054,.,,,high,"High EPC labels A-A4/B (ref. EPC=2 C-D, except NZ where ref. is EPC=1)",LogLP: log listing price per m2,log,spatial_error,660.0,0.603,p,Northern Zone LISA low-low cluster; stepwise selection; lambda=0.65,pct_premium,8.129511837792736,4.43702089890968,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.07536182728611503,0.0391116861345734,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.9268365732639108,650.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-NZ,4,Northern Zone (SEM),17,EPC = 2,energy_efficiency,A_structural,dummy,binary,0.031,,,0.034,*,,,high,Medium EPC labels C-D (ref. EPC=1 E-G in NZ model),LogLP: log listing price per m2,log,spatial_error,660.0,0.603,p,Northern Zone LISA low-low cluster; stepwise selection; lambda=0.65,pct_premium,3.1375240274801097,1.5082532715849442,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.08287002663032582,0.03908831339585724,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.120071689742151,650.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T4-NZ,4,Northern Zone (SEM),17,ARC = 1,air_conditioning,A_structural,dummy,binary,0.024,,,0.245,,,,high,Air-conditioning system,LogLP: log listing price per m2,log,spatial_error,660.0,0.603,p,Northern Zone LISA low-low cluster; stepwise selection; lambda=0.65,pct_premium,2.4072083251617027,2.1145185944906837,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.0455527983507734,0.039182510669987874,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.1625798748436225,650.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T5-LEE,5,SEM,18,LTR = 1,terrace_balcony,C_exterior,dummy,binary,0.149,,,0.001,***,,,high,Large terrace present,LogLP: log listing price per m2,log,spatial_error,234.0,0.718,p,"Low energy-efficient sub-sample (EPC E-G, built 1946-1990); lambda=0.739",pct_premium,15.94836685290053,5.255701883137238,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.21472909057873477,0.06525675312820771,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,224.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T5-LEE,5,SEM,18,CBX = 1,garage,A_structural,dummy,binary,0.114,,,0.004,**,,,high,Car box,LogLP: log listing price per m2,log,spatial_error,234.0,0.718,p,"Low energy-efficient sub-sample (EPC E-G, built 1946-1990); lambda=0.739",pct_premium,11.987332788953765,4.439143933479786,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.18884509995302962,0.06561309511826732,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.878161739095483,224.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T5-LEE,5,SEM,18,LFT = 1,accessibility,B_interior,dummy,binary,0.09,,,0.016,*,,,high,Lift,LogLP: log listing price per m2,log,spatial_error,234.0,0.718,p,"Low energy-efficient sub-sample (EPC E-G, built 1946-1990); lambda=0.739",pct_premium,9.341089306092808,4.0879675381119736,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.15890729916228175,0.06596632224750278,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.408915545815461,224.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T5-LEE,5,SEM,18,BLC = 5,condition,A_structural,dummy,binary,0.387,,,0.001,***,,,high,Building category: prestigious (ref. BLC=1),LogLP: log listing price per m2,log,spatial_error,234.0,0.718,p,"Low energy-efficient sub-sample (EPC E-G, built 1946-1990); lambda=0.739",pct_premium,46.24072843630556,17.318788407603222,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.21472909057873477,0.06525675312820771,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.2905267314918945,224.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215,fb9d007b500b1eff5cd9c2ed633d123752bd4215:T5-LEE,5,SEM,18,ARC = 1,air_conditioning,A_structural,dummy,binary,0.143,,,0.005,**,,,high,Air-conditioning system,LogLP: log listing price per m2,log,spatial_error,234.0,0.718,p,"Low energy-efficient sub-sample (EPC E-G, built 1946-1990); lambda=0.739",pct_premium,15.223367221458407,5.877498286583933,100*(exp(b - se^2/2) - 1),|b/z(p)| (two-sided normal),0.18433869858773683,0.06567028179945968,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.8070337683438042,224.0,binary,,2021.0,Italy,Europe,High income,2015.0,2018.0,mixed,listing,journal,False,False,unknown,,2016.5,spatial,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c1,3,1 (Full Model),7,LnLANDSIZE,lot_size,A_structural,log,m2,0.397,,4.381,,***,,,high,"plot area in m2, log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,full specification; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,0.397,0.09061858023282356,b (log-log),|b/t|,0.27212064024127575,0.06211381881791275,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.381,240.0,m2,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c1,3,1 (Full Model),7,LnBUILDSIZE,living_area,A_structural,log,m2,0.353,,3.404,,***,,,high,"building area in m2, log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,full specification; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,0.353,0.10370152761457109,b (log-log),|b/t|,0.21460768349018486,0.06304573545540097,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.404,240.0,m2,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c1,3,1 (Full Model),7,LnNUMROOM,bedrooms,A_structural,log,count,0.116,,1.121,,,,,high,"number of rooms (all rooms, not bedrooms specifically), log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,full specification; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,0.116,0.10347903657448707,b (log-log),|b/t|,0.0721715402929194,0.06438139187593168,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.121,240.0,count,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c1,3,1 (Full Model),7,WSTRUCTDUM,roof_materials,A_structural,dummy,binary,-0.081,,-1.012,,,,,high,"dummy for wall structure (coding not described; mean 1.15); values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,full specification; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),pct_premium,-8.07555191932673,7.381194565910399,100*(exp(b - se^2/2) - 1),|b/t|,-0.06518538545373372,0.06441243621910446,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-1.012,240.0,binary,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c1,3,1 (Full Model),7,LnDISSCHOOL,school_distance,D_location,log,m,-0.046,,-0.895,,,,,high,"distance from residence to nearest school, metres, log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,full specification; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,-0.046,0.05139664804469274,b (log-log),|b/t|,-0.05767583220895913,0.06444227062453534,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-0.895,240.0,m,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c1,3,1 (Full Model),7,LnDISHPITAL,hospital_distance,D_location,log,m,-0.163,,-2.936,,***,,,high,"distance to nearest hospital, metres, log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,full specification; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,-0.163,0.055517711171662126,b (log-log),|b/t|,-0.18620354130518238,0.06342082469522561,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.936,240.0,m,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,True
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c1,3,1 (Full Model),7,LnDISSPMARKET,commercial_distance,D_location,log,m,0.103,,1.918,,*,,,high,"distance to nearest supermarket, metres, log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,full specification; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,0.103,0.053701772679874867,b (log-log),|b/t|,0.12286828513812273,0.06406062833061664,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.918,240.0,m,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c1,3,1 (Full Model),7,LnDISREST,neighbourhood_amenities,F_neighbourhood,log,m,-0.155,,-3.606,,***,,,high,"distance to nearest restaurant, metres, log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,full specification; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,-0.155,0.04298391569606212,b (log-log),|b/t|,-0.2267058277769953,0.06286905928369255,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.606,240.0,m,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c1,3,1 (Full Model),7,LnDISCITY,cbd_distance,D_location,log,m,0.039,,0.68,,,,,high,"distance from city (centre), metres, log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,full specification; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,0.039,0.057352941176470586,b (log-log),|b/t|,0.04385158788848748,0.0644876292477757,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),0.68,240.0,m,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c1,3,1 (Full Model),7,LnDISMSTREET,highway_distance,D_location,log,m,0.091,,3.089,,***,,,high,"distance to main street, metres, log (positive = farther from main road is dearer); values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,full specification; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,0.091,0.02945937196503723,b (log-log),|b/t|,0.19554474586855783,0.06330357587198376,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.089,240.0,m,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c1,3,1 (Full Model),7,GARDENDUM,green_space,E_environment,dummy,binary,0.261,,2.637,,***,,,high,"dummy for being close to a garden (coded 1/2 in Table 2, mean 1.79); values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,full specification; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),pct_premium,29.18843189073048,12.849352319992153,100*(exp(b - se^2/2) - 1),|b/t|,0.16780399667203355,0.0636344318058527,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.637,240.0,binary,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c1,3,1 (Full Model),7,LnPM10,air_pollution,E_environment,log,ppm,-1.355,,-2.355,,**,,,medium,"PM10 concentration (printed unit 'ppm', mean 1,223.12), log; 2010 ambient monitoring data, kriged; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%; Full-model LnPM10 elasticity -1.355 differs sharply from fit-model -0.320 and text quotes -0.32",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,full specification; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,-1.355,0.5753715498938429,b (log-log),|b/t|,-0.15028805276549081,0.06381658291528272,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.355,240.0,ppm,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c2,3,2 (Fit Model),7,LnLANDSIZE,lot_size,A_structural,log,m2,0.396,,4.432,,***,,,high,"plot area in m2, log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,'fit model': insignificant variables dropped; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,0.396,0.08935018050541516,b (log-log),|b/t|,0.27505006818436345,0.06206003343510006,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),4.432,240.0,m2,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c2,3,2 (Fit Model),7,LnBUILDSIZE,living_area,A_structural,log,m2,0.393,,3.915,,***,,,high,"building area in m2, log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,'fit model': insignificant variables dropped; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,0.393,0.10038314176245211,b (log-log),|b/t|,0.24500965783928996,0.06258228808155554,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.915,240.0,m2,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c2,3,2 (Fit Model),7,LnDISHPITAL,hospital_distance,D_location,log,m,-0.16,,-3.115,,***,,,high,"distance to nearest hospital, metres, log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,'fit model': insignificant variables dropped; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,-0.16,0.051364365971107544,b (log-log),|b/t|,-0.19712693766703612,0.06328312605683341,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.115,240.0,m,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c2,3,2 (Fit Model),7,LnDISSPMARKET,commercial_distance,D_location,log,m,0.103,,1.975,,**,,,high,"distance to nearest supermarket, metres, log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,'fit model': insignificant variables dropped; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,0.103,0.05215189873417721,b (log-log),|b/t|,0.12646217397138265,0.06403148049183932,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),1.975,240.0,m,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c2,3,2 (Fit Model),7,LnDISREST,neighbourhood_amenities,F_neighbourhood,log,m,-0.16,,-3.999,,***,,,high,"distance to nearest restaurant, metres, log; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,'fit model': insignificant variables dropped; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,-0.16,0.040010002500625155,b (log-log),|b/t|,-0.24994140487678768,0.06250097646331275,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-3.999,240.0,m,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,True
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c2,3,2 (Fit Model),7,LnDISMSTREET,highway_distance,D_location,log,m,0.092,,3.153,,***,,,high,"distance to main street, metres, log (positive = farther from main road is dearer); values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,'fit model': insignificant variables dropped; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,0.092,0.02917856010149064,b (log-log),|b/t|,0.1994366009994507,0.0632529657467335,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),3.153,240.0,m,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,True
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c2,3,2 (Fit Model),7,GARDENDUM,green_space,E_environment,dummy,binary,0.232,,2.377,,**,,,high,"dummy for being close to a garden (coded 1/2 in Table 2, mean 1.79); values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,'fit model': insignificant variables dropped; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),pct_premium,25.51272011042631,12.308783217844864,100*(exp(b - se^2/2) - 1),|b/t|,0.1516598714244429,0.06380305907633274,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),2.377,240.0,binary,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False
fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366,fdf3432efb95e96e6e45a3ba105603f17a38d366:T3-c2,3,2 (Fit Model),7,LnPM10,air_pollution,E_environment,log,ppm,-0.32,,-2.806,,***,,,medium,"PM10 concentration (printed unit 'ppm', mean 1,223.12), log; 2010 ambient monitoring data, kriged; values in parentheses are t-statistics (no legend printed; consistent with coef/SE, e.g. constant 17.181 (17.689)); stars legend not printed, text implies *** 1%, ** 5%, * 10%; Full-model LnPM10 elasticity -1.355 differs sharply from fit-model -0.320 and text quotes -0.32",ln(PPRICE) sales price of house (Rupiah),log,OLS,250.0,0.606,t,'fit model': insignificant variables dropped; 250 household observations in Yogyakarta Special Territory; adjusted R2 printed (0.606),elasticity,-0.32,0.11404133998574484,b (log-log),|b/t|,-0.1782265900651508,0.06351624735037448,t/sqrt(t^2+df); se=sqrt((1-r^2)/df),-2.806,240.0,ppm,,2012.0,Indonesia,Asia,Upper middle income,2010.0,2010.0,single_family,transaction,journal,False,False,unknown,,2010.0,ols,journal,True,True,False